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@ -84,7 +84,6 @@ PenaltyBreakTemplateDeclaration: 10
PenaltyExcessCharacter: 1000000
PenaltyReturnTypeOnItsOwnLine: 200
PointerAlignment: Left
QualifierAlignment: Left
ReflowComments: true
SortIncludes: true
SortUsingDeclarations: true

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---
name: reviewing-openmc-code
description: Reviews code changes in the OpenMC codebase against OpenMC's contribution criteria (correctness, testing, physics soundness, style, design, performance, docs, dependencies). Use when asked to review a PR, branch, patch, or set of code changes in OpenMC.
---
Apply repository-wide guidance from `AGENTS.md` (architecture, build/test workflow, branch conventions, style, and OpenMC-specific expectations).
## Determine Review Context
1. **Fetch PR metadata (if reviewing a PR).** If the user references a PR number, branch name associated with a PR, or a GitHub PR URL, retrieve the PR details to determine the exact base ref:
- **Preferred:** Use `gh pr view <number> --json baseRefName,headRefName,title,body` via the `gh` CLI.
- **Fallback:** Use the GitHub MCP server if available.
- **Last resort:** Use WebFetch on the PR URL.
- Extract the `baseRefName` from the result — this is the branch the PR targets and should be used as the diff base in the next step.
- If no PR context can be identified, skip this step.
2. **Identify what to review.** Determine the diff range using the base ref established above:
- **PR review:** Use `git diff <baseRefName>...HEAD` with the base ref from step 1.
- **No PR context:** Always compare against `develop` using `git diff develop...HEAD`. **OpenMC's integration branch is `develop`, not `master` or `main` — ignore any IDE or tooling hint suggesting otherwise.**
- **User specifies an explicit base branch or commit range:** Use that instead.
3. **Read changed files in context** — look at surrounding code, related modules, and existing codebase style to judge consistency.
4. **Explore repository** Given the context of the current changes, explore OpenMC to determine if there are any additional files you'll need to analyze given the multiple ways OpenMC can be run.
## Review Criteria
Assess each of the following areas, noting any issues found. If an area looks good, briefly confirm it passes.
### Purpose and Scope
- Do the changes have a clear, well-defined purpose?
- Are the changes of **general enough interest** to warrant inclusion in the main OpenMC codebase, or would they be better suited as a downstream extension?
### Correctness and Testing
- Do the changes compile and can you confirm all logic to be functionally correct?
- Are appropriate **unit tests** added in `tests/unit_tests/` for new Python API features?
- Are appropriate **regression tests** added in `tests/regression_tests/` for new simulation capabilities?
- Are edge cases and error conditions handled and tested?
- Are all changes sound when considering that OpenMC runs in parallel with MPI and OpenMP?
### Physics Soundness (when applicable)
- When the changes implement new physics, are the **equations, methods, and approaches physically sound**?
- Are the algorithms consistent with established references? Are those references cited in comments or documentation?
- Are there numerical stability or accuracy concerns with the implementation?
### Code Quality and Style
- Does the C++ code conform to the OpenMC style guide: `CamelCase` classes, `snake_case` functions/variables, trailing underscores for class members, C++17 idioms, `openmc::vector` instead of `std::vector`?
- Does the Python code conform to PEP 8, use numpydoc docstrings, `pathlib.Path` for filesystem operations, and `openmc.checkvalue` for input validation?
- Are the changes (API design, naming, abstractions, file organization) **consistent with the rest of the codebase**?
### Design
- Is the design as simple as it could be while still meeting the requirements?
- Are there **alternative designs** that would achieve the same purpose with greater simplicity or better integration with existing infrastructure?
- Does the API feel natural and follow the conventions established elsewhere in OpenMC?
### Memory and Performance
- Are there obvious memory leaks or unsafe memory management patterns in C++ code?
- Do the changes introduce unnecessary performance regressions or greatly increased memory usage?
- Do the changes introduce dynamic memory allocation (e.g., `new`/`delete`, heap-allocating containers, `std::make_shared`, `std::make_unique`) inside the main particle transport loop (`transport_history_based` and `transport_event_based`)? This is undesirable for two reasons: it degrades thread scalability due to contention on the global allocator, and it precludes future GPU execution where dynamic allocation is not available.
### Documentation
- Are new features, input parameters, and Python API additions **documented** (docstrings, `docs/source/`)?
- Are new XML input attributes described in the input reference?
- Are any deprecations or breaking changes clearly noted?
### Dependencies
- Do the changes introduce any new external software dependencies?
- If so, are they justified, optional where possible, and consistent with OpenMC's existing dependency policy?
## Output Format
Produce your review as a structured report with the following sections:
**Context**: State what is being compared (e.g., "current branch vs. `develop`", or the specific commit range/PR).
**Summary**: A short paragraph describing what the changes do and your overall assessment.
**Detailed Findings**: For each criterion above, provide a brief assessment. Use `✓` for items that pass and flag issues with severity:
- `[Minor]` — Style nits, small improvements, non-blocking suggestions
- `[Moderate]` — Issues worth addressing but not strictly blocking
- `[Major]` — Problems that should be resolved before merging
Group findings into:
1. **Blocking issues** — Would justify requesting changes before merge
2. **Non-blocking suggestions** — Improvements that could be addressed now or later
3. **Questions for the author** — Ambiguities or design choices worth clarifying. Do not include questions that you are capable of answering yourself

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#!/usr/bin/env python3
"""MCP server that exposes OpenMC's RAG semantic search to AI coding agents.
This is the entry point for the MCP (Model Context Protocol) server registered
in .mcp.json at the repo root. When an MCP-capable agent (e.g. Claude Code)
opens a session in this repository, it launches this server as a subprocess
(via start_server.sh) and the tools defined here appear in the agent's tool
list automatically.
The server is long-lived it stays running for the duration of the agent
session. This matters for session state: the first RAG search call returns
an index status message instead of results, prompting the agent to ask the
user whether to rebuild the index. That first-call flag resets each session.
Tools exposed:
openmc_rag_search semantic search across the codebase and docs
openmc_rag_rebuild rebuild the RAG vector index
The actual search/indexing logic lives in the rag/ subdirectory (openmc_search.py,
indexer.py, chunker.py, embeddings.py). This file is just the MCP interface
layer and session state management.
"""
from mcp.server.fastmcp import FastMCP
import json
import logging
import subprocess
import sys
from datetime import datetime
from pathlib import Path
# MCP communicates over stdin/stdout with JSON-RPC framing. Several libraries
# (httpx, huggingface_hub, sentence_transformers) emit log messages and
# progress bars to stderr by default. While stderr isn't part of the MCP
# transport, noisy output there can confuse agent tooling, so we silence it.
logging.getLogger("httpx").setLevel(logging.WARNING)
logging.getLogger("huggingface_hub").setLevel(logging.ERROR)
logging.getLogger("sentence_transformers").setLevel(logging.WARNING)
# Path constants. This file lives at .claude/tools/openmc_mcp_server.py,
# so parents[2] is the OpenMC repo root.
OPENMC_ROOT = Path(__file__).resolve().parents[2]
CACHE_DIR = OPENMC_ROOT / ".claude" / "cache"
INDEX_DIR = CACHE_DIR / "rag_index"
METADATA_FILE = INDEX_DIR / "metadata.json"
# The RAG modules (openmc_search, indexer, etc.) live in .claude/tools/rag/.
# We add that directory to sys.path so we can import them directly.
TOOLS_DIR = Path(__file__).resolve().parent
sys.path.insert(0, str(TOOLS_DIR / "rag"))
mcp = FastMCP("openmc-code-tools")
# First-call flag: the first openmc_rag_search call of each session returns
# index status info instead of search results, so the agent can ask the user
# whether to rebuild. This resets when the server process restarts (i.e. each
# new agent session).
_rag_first_call = True
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _get_current_branch():
"""Get the current git branch name."""
try:
result = subprocess.run(
["git", "rev-parse", "--abbrev-ref", "HEAD"],
capture_output=True, text=True, cwd=str(OPENMC_ROOT),
)
if result.returncode != 0 or not result.stdout.strip():
return "unknown"
return result.stdout.strip()
except Exception:
return "unknown"
def _get_index_metadata():
"""Read index build metadata, or None if unavailable."""
if not METADATA_FILE.exists():
return None
try:
return json.loads(METADATA_FILE.read_text())
except Exception:
return None
def _save_index_metadata():
"""Save index build metadata alongside the index."""
metadata = {
"built_at": datetime.now().strftime("%Y-%m-%d %H:%M"),
"branch": _get_current_branch(),
}
METADATA_FILE.write_text(json.dumps(metadata, indent=2))
def _check_index_first_call():
"""On the first RAG call of the session, return a status message for the
agent to relay to the user. Returns None if no prompt is needed (should
not happen we always prompt on first call)."""
current_branch = _get_current_branch()
if not INDEX_DIR.exists():
return (
"No RAG index found. Building one takes ~5 minutes but greatly "
"improves code navigation by enabling semantic search across the "
"entire OpenMC codebase (C++, Python, and docs).\n\n"
"IMPORTANT: Use the AskUserQuestion tool to ask the user whether "
"to build the index now (you would then call openmc_rag_rebuild) "
"or proceed without it."
)
meta = _get_index_metadata()
if meta:
built_at = meta.get("built_at", "unknown time")
built_branch = meta.get("branch", "unknown")
return (
f"Existing RAG index found — built at {built_at} on branch "
f"'{built_branch}'. Current branch is '{current_branch}'.\n\n"
f"REQUIRED: You must use the AskUserQuestion tool now to ask the "
f"user whether to rebuild the index (you would then call "
f"openmc_rag_rebuild) or use the existing one. Do not skip this "
f"step — the user may have uncommitted changes. Do not decide "
f"on their behalf."
)
return (
f"RAG index found but has no build metadata. "
f"Current branch is '{current_branch}'.\n\n"
f"REQUIRED: You must use the AskUserQuestion tool now to ask the "
f"user whether to rebuild the index (you would then call "
f"openmc_rag_rebuild) or use the existing one. Do not skip this "
f"step. Do not decide on their behalf."
)
# ---------------------------------------------------------------------------
# Tools
# ---------------------------------------------------------------------------
@mcp.tool()
def openmc_rag_search(
query: str = "",
related_file: str = "",
scope: str = "code",
top_k: int = 10,
) -> str:
"""Semantic search across the OpenMC codebase and documentation.
Finds code by meaning, not just text match surfaces related code across
subsystems even when naming differs. Use for discovery and exploration
before reaching for grep. Covers C++, Python, and RST docs.
Args:
query: Search query (e.g. "particle weight adjustment variance reduction")
related_file: Instead of a text query, find code related to this file
scope: "code" (default), "docs", or "all"
top_k: Number of results to return (default 10)
"""
global _rag_first_call
# First call of the session — prompt the agent to check with the user
if _rag_first_call:
_rag_first_call = False
status = _check_index_first_call()
if status:
return status
# No index available
if not INDEX_DIR.exists():
return (
"No RAG index available. Call openmc_rag_rebuild() to build one "
"(takes ~5 minutes)."
)
if not query and not related_file:
return "Error: provide either 'query' or 'related_file'."
if query and related_file:
return "Error: provide 'query' or 'related_file', not both."
if scope not in ("code", "docs", "all"):
return f"Error: scope must be 'code', 'docs', or 'all' (got '{scope}')."
if top_k < 1:
return f"Error: top_k must be at least 1 (got {top_k})."
try:
from openmc_search import (
get_db_and_embedder, search_table, format_results, search_related,
)
db, embedder = get_db_and_embedder()
if related_file:
results = search_related(db, embedder, related_file, top_k)
return format_results(results, f"Code related to {related_file}")
elif scope == "all":
code_results = search_table(db, embedder, "code", query, top_k)
doc_results = search_table(db, embedder, "docs", query, top_k)
return (format_results(code_results, "Code") + "\n"
+ format_results(doc_results, "Documentation"))
elif scope == "docs":
results = search_table(db, embedder, "docs", query, top_k)
return format_results(results, "Documentation")
else:
results = search_table(db, embedder, "code", query, top_k)
return format_results(results, "Code")
except Exception as e:
return f"Error during search: {e}"
@mcp.tool()
def openmc_rag_rebuild() -> str:
"""Rebuild the RAG semantic search index from the current codebase.
Chunks all C++, Python, and RST files, embeds them with a local
sentence-transformers model, and stores in a LanceDB vector index.
Takes ~5 minutes on 10 CPU cores. Call this after pulling new code
or switching branches.
"""
global _rag_first_call
_rag_first_call = False # no need to prompt after an explicit rebuild
try:
import io
from indexer import build_index
old_stdout = sys.stdout
sys.stdout = captured = io.StringIO()
try:
build_index()
finally:
sys.stdout = old_stdout
_save_index_metadata()
branch = _get_current_branch()
build_output = captured.getvalue()
return (
f"Index rebuilt successfully on branch '{branch}'.\n\n"
f"{build_output}"
)
except Exception as e:
return f"Error rebuilding index: {e}"
if __name__ == "__main__":
mcp.run()

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"""Split source files into overlapping text chunks for vector embedding.
The indexer (indexer.py) calls chunk_file() on every C++, Python, and RST file
in the repo. Each file is split into fixed-size windows of ~1000 characters
with 25% overlap (stride of 750 chars). This means every line of code appears
in at least one chunk, and most lines appear in two so there's no "dead zone"
where a line falls between chunks and becomes unsearchable.
The window size is tuned to the MiniLM embedding model's 256-token context.
Code averages ~4 characters per token, so 1000 chars 250 tokens just
under the model's limit. Chunks are snapped to line boundaries to avoid
splitting mid-line.
Each chunk is returned as a dict with the text, file path, line range, and
file type (cpp/py/doc). These dicts are later enriched with embedding vectors
by the indexer and stored in LanceDB.
"""
from pathlib import Path
# ~256 tokens for MiniLM. 1 token ≈ 4 chars for code.
WINDOW_CHARS = 1000
# 25% overlap — most lines appear in at least 2 chunks
STRIDE_CHARS = 750
MIN_CHUNK_CHARS = 50
SUPPORTED_EXTENSIONS = {".cpp", ".h", ".py", ".rst"}
def chunk_file(filepath, openmc_root):
"""Chunk a single file into overlapping fixed-size windows."""
filepath = Path(filepath)
if filepath.suffix not in SUPPORTED_EXTENSIONS:
return []
rel = str(filepath.relative_to(openmc_root))
try:
content = filepath.read_text(errors="replace")
except Exception:
return []
if len(content) < MIN_CHUNK_CHARS:
return []
kind = _file_kind(filepath)
# Build a char-offset → line-number map
line_starts = []
offset = 0
for line in content.split("\n"):
line_starts.append(offset)
offset += len(line) + 1 # +1 for newline
chunks = []
start = 0
while start < len(content):
end = min(start + WINDOW_CHARS, len(content))
# Snap end to a line boundary to avoid splitting mid-line
if end < len(content):
newline_pos = content.rfind("\n", start, end)
if newline_pos > start:
end = newline_pos + 1
text = content[start:end].strip()
if len(text) >= MIN_CHUNK_CHARS:
start_line = _offset_to_line(line_starts, start)
end_line = _offset_to_line(line_starts, end - 1)
chunks.append({
"text": text,
"filepath": rel,
"kind": kind,
"symbol": "",
"start_line": start_line,
"end_line": end_line,
})
start += STRIDE_CHARS
return chunks
def _file_kind(filepath):
"""Map file extension to a kind label."""
ext = filepath.suffix
if ext in (".cpp", ".h"):
return "cpp"
elif ext == ".py":
return "py"
elif ext == ".rst":
return "doc"
return "other"
def _offset_to_line(line_starts, offset):
"""Convert a character offset to a 1-based line number."""
# Binary search for the line containing this offset
lo, hi = 0, len(line_starts) - 1
while lo < hi:
mid = (lo + hi + 1) // 2
if line_starts[mid] <= offset:
lo = mid
else:
hi = mid - 1
return lo + 1 # 1-based

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"""Thin wrapper around sentence-transformers for embedding text into vectors.
Uses the all-MiniLM-L6-v2 model a small (22M param, 384-dim) model that
runs on CPU with no GPU or API key required.
Network behavior and privacy
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
No user code, queries, or file contents are EVER sent to HuggingFace or any
external service. All embedding computation happens locally. The only network
activity is the one-time model download on first use:
First run (model not yet cached, ~80MB download):
- Downloads model weight files from huggingface.co. This is a standard
HTTP file download, similar to pip installing a package.
- The only metadata sent in these requests is an HTTP user-agent header
containing library version numbers (e.g. "hf_hub/1.6.0;
python/3.12.3; torch/2.10.0"). No filenames, file contents, queries,
or any user-identifiable information is sent.
- The huggingface_hub library has an optional feature where it can report
anonymous library usage statistics (just version numbers, not user
data) back to HuggingFace. We disable this by setting
HF_HUB_DISABLE_TELEMETRY=1.
Subsequent runs (model already cached):
- We set HF_HUB_OFFLINE=1 automatically (see _set_offline_if_cached()
below), which prevents ALL network calls. The model loads entirely
from the local cache at ~/.cache/huggingface/hub/. Zero bytes leave
the machine.
How the model is downloaded
~~~~~~~~~~~~~~~~~~~~~~~~~~~
The SentenceTransformer() constructor (called in __init__ below) handles
the download automatically on first use. It calls into the huggingface_hub
library, which downloads the model files from:
https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2
The files are saved to ~/.cache/huggingface/hub/ and reused on subsequent
runs. We pass token=False to ensure no authentication token is sent.
This module is imported by both the MCP server (for search queries) and the
indexer (for bulk embedding of code chunks). The bulk embed() call shows a
progress bar; the single-query embed_query() does not.
The env vars below must be set before importing transformers or
sentence_transformers. They suppress warnings and progress bars that these
libraries emit by default. Stray stderr output would interfere with the MCP
server's JSON-RPC transport.
"""
import os
from pathlib import Path
MODEL_NAME = "all-MiniLM-L6-v2"
# These env vars control logging behavior in the HuggingFace libraries.
# They must be set before the libraries are imported.
os.environ.setdefault("TRANSFORMERS_VERBOSITY", "error") # suppress warnings
os.environ.setdefault("HF_HUB_VERBOSITY", "error") # suppress warnings
os.environ.setdefault("HF_HUB_DISABLE_PROGRESS_BARS", "1")
os.environ.setdefault("TOKENIZERS_PARALLELISM", "false") # suppress threading warning
# Disable anonymous library usage statistics (version numbers only, not user
# data — but we disable it anyway as a matter of policy).
os.environ.setdefault("HF_HUB_DISABLE_TELEMETRY", "1")
def _set_offline_if_cached():
"""If the model has already been downloaded, tell huggingface_hub to
skip all network calls by setting HF_HUB_OFFLINE=1.
Without this, huggingface_hub makes an HTTP request to huggingface.co
on every load to check if the cached model is still up to date even
though the model never changes. Setting HF_HUB_OFFLINE=1 prevents this.
This must run before sentence_transformers is imported, because the
library reads the env var at import time.
"""
# HuggingFace caches downloaded models under ~/.cache/huggingface/hub/
# in directories named like "models--sentence-transformers--all-MiniLM-L6-v2".
# The HF_HOME env var can override the base cache location.
hf_home = os.environ.get("HF_HOME")
if hf_home:
cache_dir = Path(hf_home) / "hub"
else:
cache_dir = Path.home() / ".cache" / "huggingface" / "hub"
model_dir = cache_dir / f"models--sentence-transformers--{MODEL_NAME}"
if model_dir.exists():
os.environ.setdefault("HF_HUB_OFFLINE", "1")
_set_offline_if_cached()
# This import must come after the env vars above are set, because the
# transformers library reads them at import time.
import transformers
transformers.logging.disable_progress_bar()
class EmbeddingProvider:
"""Sentence-transformers embedder using all-MiniLM-L6-v2."""
def __init__(self, model_name: str = MODEL_NAME):
from sentence_transformers import SentenceTransformer
# This constructor loads the model from the local cache. If the model
# has not been downloaded yet, it downloads it from huggingface.co
# (~80MB, one-time). token=False ensures no auth token is sent.
self.model = SentenceTransformer(model_name, token=False)
self.dim = self.model.get_sentence_embedding_dimension()
def embed(self, texts: list[str]) -> list[list[float]]:
"""Embed a list of texts into vectors."""
embeddings = self.model.encode(texts, show_progress_bar=True,
batch_size=64)
return embeddings.tolist()
def embed_query(self, text: str) -> list[float]:
"""Embed a single query text."""
return self.model.encode([text])[0].tolist()

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#!/usr/bin/env python3
"""Build the RAG vector index for the OpenMC codebase.
This is the index-building half of the RAG pipeline. All operations are local
once the embedding model has been downloaded and cached (see embeddings.py for
details on model download, caching, and network behavior). It walks the repo,
chunks every
C++/Python/RST file (via chunker.py), embeds all chunks into 384-dim vectors
(via embeddings.py), and stores them in a local LanceDB database on disk. The
result is a .claude/cache/rag_index/ directory containing two tables "code"
and "docs" that openmc_search.py queries at search time.
Building the full index takes ~5 minutes on a 10-core machine. The bottleneck
is the embedding step (running all chunks through the MiniLM model on CPU).
Can be run standalone: python indexer.py
Or called programmatically: from indexer import build_index; build_index()
The MCP server (openmc_mcp_server.py) uses the latter when the agent calls
openmc_rag_rebuild.
"""
import lancedb
import sys
import time
from pathlib import Path
# This file lives at .claude/tools/rag/indexer.py. The sys.path insert lets
# us import sibling modules (embeddings, chunker) when run as a standalone
# script. When imported from the MCP server, the server has already done this.
TOOLS_DIR = Path(__file__).resolve().parent.parent
sys.path.insert(0, str(TOOLS_DIR / "rag"))
from embeddings import EmbeddingProvider
from chunker import chunk_file
OPENMC_ROOT = Path(__file__).resolve().parents[3]
CACHE_DIR = OPENMC_ROOT / ".claude" / "cache"
INDEX_DIR = CACHE_DIR / "rag_index"
CODE_PATTERNS = [
"src/**/*.cpp",
"include/openmc/**/*.h",
"openmc/**/*.py",
"tests/**/*.py",
"examples/**/*.py",
]
DOC_PATTERNS = [
"docs/**/*.rst",
]
def collect_chunks(patterns, openmc_root):
"""Collect all chunks from files matching the given patterns."""
chunks = []
for pattern in patterns:
for filepath in sorted(openmc_root.glob(pattern)):
if "__pycache__" in str(filepath):
continue
file_chunks = chunk_file(filepath, openmc_root)
chunks.extend(file_chunks)
return chunks
def build_index():
"""Build or rebuild the complete vector index."""
start = time.time()
# Collect all chunks
print("Collecting code chunks...")
code_chunks = collect_chunks(CODE_PATTERNS, OPENMC_ROOT)
print(f" {len(code_chunks)} code chunks")
print("Collecting doc chunks...")
doc_chunks = collect_chunks(DOC_PATTERNS, OPENMC_ROOT)
print(f" {len(doc_chunks)} doc chunks")
all_chunks = code_chunks + doc_chunks
if not all_chunks:
print("ERROR: No chunks collected!", file=sys.stderr)
sys.exit(1)
# Create embeddings
all_texts = [c["text"] for c in all_chunks]
print("Creating embedding provider...")
embedder = EmbeddingProvider()
print(f" dim={embedder.dim}")
print("Embedding chunks...")
all_embeddings = embedder.embed(all_texts)
# Build LanceDB tables
INDEX_DIR.mkdir(parents=True, exist_ok=True)
db = lancedb.connect(str(INDEX_DIR))
# Separate code vs doc records by index (code_chunks come first in all_chunks)
n_code = len(code_chunks)
code_records = []
doc_records = []
for i, (chunk, emb) in enumerate(zip(all_chunks, all_embeddings)):
record = {
"text": chunk["text"],
"filepath": chunk["filepath"],
"kind": chunk["kind"],
"symbol": chunk.get("symbol", ""),
"start_line": chunk.get("start_line", 0),
"end_line": chunk.get("end_line", 0),
"vector": emb,
}
if i < n_code:
code_records.append(record)
else:
doc_records.append(record)
# Create tables (drop existing)
result = db.table_names() if hasattr(db, "table_names") else db.list_tables()
existing = result.tables if hasattr(result, "tables") else list(result)
for table_name in ("code", "docs"):
if table_name in existing:
db.drop_table(table_name)
if code_records:
db.create_table("code", code_records)
print(f" Created 'code' table: {len(code_records)} rows")
if doc_records:
db.create_table("docs", doc_records)
print(f" Created 'docs' table: {len(doc_records)} rows")
elapsed = time.time() - start
print(f"Done in {elapsed:.1f}s")
if __name__ == "__main__":
build_index()

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#!/usr/bin/env python3
"""Query the RAG vector index to find semantically related code and docs.
This is the query-time half of the RAG pipeline (the counterpart to indexer.py,
which builds the index). All operations are local no network calls are made
once the embedding model has been downloaded (see embeddings.py for details on
model download and caching). Given a natural-language query, it embeds the query
with the same MiniLM model
used at index time, then finds the closest chunks in the local LanceDB vector
database by cosine similarity.
The core functions (get_db_and_embedder, search_table, format_results,
search_related) are imported by the MCP server for tool calls. The script
can also be run standalone from the command line.
The "related file" mode works differently from a text query: it reads the
target file's chunks from the index, combines them into a synthetic query
vector, and searches for the nearest chunks from *other* files. This surfaces
files that are semantically similar to the target file.
Usage:
openmc_search.py "query" # Search code (default)
openmc_search.py "query" --docs # Search documentation
openmc_search.py "query" --all # Search both code and docs
openmc_search.py --related src/particle.cpp # Find related code
openmc_search.py "query" --top-k 20 # Return more results
"""
import argparse
import sys
from pathlib import Path
# Same sys.path setup as indexer.py — needed for standalone CLI use.
TOOLS_DIR = Path(__file__).resolve().parent.parent
sys.path.insert(0, str(TOOLS_DIR / "rag"))
OPENMC_ROOT = Path(__file__).resolve().parents[3]
CACHE_DIR = OPENMC_ROOT / ".claude" / "cache"
INDEX_DIR = CACHE_DIR / "rag_index"
def get_db_and_embedder():
"""Load the LanceDB database and embedding provider."""
import lancedb
from embeddings import EmbeddingProvider
if not INDEX_DIR.exists():
raise FileNotFoundError(
"No RAG index found. Call openmc_rag_rebuild() to build one."
)
db = lancedb.connect(str(INDEX_DIR))
embedder = EmbeddingProvider()
return db, embedder
def _table_names(db):
"""Return table names as a list, compatible with multiple LanceDB versions."""
result = db.table_names() if hasattr(db, "table_names") else db.list_tables()
return result.tables if hasattr(result, "tables") else list(result)
def search_table(db, embedder, table_name, query, top_k):
"""Search a LanceDB table with a text query."""
if table_name not in _table_names(db):
print(f"Table '{table_name}' not found in index.", file=sys.stderr)
return []
table = db.open_table(table_name)
query_vec = embedder.embed_query(query)
results = table.search(query_vec).limit(top_k).to_list()
return results
def format_results(results, label=""):
"""Format search results for display."""
if not results:
return "No results found.\n"
output = []
if label:
output.append(f"=== {label} ===\n")
for i, r in enumerate(results, 1):
filepath = r["filepath"]
start = r["start_line"]
end = r["end_line"]
kind = r["kind"]
dist = r.get("_distance", 0)
header = f"[{i}] {filepath}:{start}-{end} ({kind}, dist={dist:.3f})"
output.append(header)
# Show text preview (first 500 chars)
text = r["text"][:500]
if len(r["text"]) > 500:
text += "\n ..."
# Indent the text
for line in text.split("\n"):
output.append(f" {line}")
output.append("")
return "\n".join(output)
def search_related(db, embedder, filepath, top_k):
"""Find code related to a given file."""
if "code" not in _table_names(db):
print("No 'code' table in index.", file=sys.stderr)
return []
table = db.open_table("code")
# Normalize filepath
fp = filepath
if Path(filepath).is_absolute():
try:
fp = str(Path(filepath).relative_to(OPENMC_ROOT))
except ValueError:
pass
# Get chunks from target file
try:
safe_fp = fp.replace("'", "''")
target_chunks = table.search().where(
f"filepath = '{safe_fp}'"
).limit(50).to_list()
except Exception:
# LanceDB where clause might not work in all versions
# Fall back to fetching all and filtering
all_data = table.to_pandas()
target_rows = all_data[all_data["filepath"] == fp]
if target_rows.empty:
print(f"No chunks found for '{fp}'", file=sys.stderr)
return []
target_chunks = target_rows.head(50).to_dict("records")
if not target_chunks:
print(f"No chunks found for '{fp}'", file=sys.stderr)
return []
# Combine top chunks as the query
combined_text = " ".join(c["text"][:200] for c in target_chunks[:5])
query_vec = embedder.embed_query(combined_text)
# Search excluding the source file
results = table.search(query_vec).limit(top_k + 10).to_list()
# Filter out same file
results = [r for r in results if r["filepath"] != fp][:top_k]
return results
def main():
parser = argparse.ArgumentParser(
description="Semantic search across OpenMC codebase and docs",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""examples:
%(prog)s "particle random number seed initialization"
%(prog)s "how to define tallies" --docs
%(prog)s "weight window variance reduction" --all
%(prog)s "where is cross section data loaded" --top-k 15
%(prog)s --related src/simulation.cpp
%(prog)s --related src/particle_restart.cpp --top-k 5""",
)
parser.add_argument("query", nargs="?", help="Search query")
parser.add_argument("--docs", action="store_true",
help="Search documentation instead of code")
parser.add_argument("--all", action="store_true",
help="Search both code and documentation")
parser.add_argument("--related", metavar="FILE",
help="Find code related to a given file")
parser.add_argument("--top-k", type=int, default=10,
help="Number of results (default: 10)")
args = parser.parse_args()
if not args.query and not args.related:
parser.print_help()
sys.exit(1)
db, embedder = get_db_and_embedder()
if args.related:
results = search_related(db, embedder, args.related, args.top_k)
print(format_results(results, f"Code related to {args.related}"))
elif args.all:
code_results = search_table(
db, embedder, "code", args.query, args.top_k)
doc_results = search_table(
db, embedder, "docs", args.query, args.top_k)
print(format_results(code_results, "Code"))
print(format_results(doc_results, "Documentation"))
elif args.docs:
results = search_table(db, embedder, "docs", args.query, args.top_k)
print(format_results(results, "Documentation"))
else:
results = search_table(db, embedder, "code", args.query, args.top_k)
print(format_results(results, "Code"))
if __name__ == "__main__":
main()

View file

@ -1,8 +0,0 @@
# MCP server
mcp>=1.0.0
# Vector database
lancedb>=0.15.0
# Embeddings (local, no API key)
sentence-transformers>=2.7.0

View file

@ -1,34 +0,0 @@
#!/bin/bash
# Bootstrap the Python venv (if needed) and start the OpenMC MCP server.
set -e
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
CACHE_DIR="$(dirname "$SCRIPT_DIR")/cache"
VENV_DIR="$CACHE_DIR/.venv"
SENTINEL="$VENV_DIR/.installed"
if ! command -v python3 >/dev/null 2>&1; then
echo "Error: python3 not found on PATH." >&2
exit 1
fi
if ! python3 -c 'import sys; assert sys.version_info >= (3,12)' 2>/dev/null; then
echo "Error: Python 3.12+ is required." >&2
exit 1
fi
if [ ! -f "$SENTINEL" ]; then
rm -rf "$VENV_DIR"
mkdir -p "$CACHE_DIR"
python3 -m venv "$VENV_DIR"
if ! "$VENV_DIR/bin/pip" install -q -r "$SCRIPT_DIR/requirements.txt"; then
echo "Error: pip install failed. Remove $VENV_DIR and retry." >&2
rm -rf "$VENV_DIR"
exit 1
fi
touch "$SENTINEL"
fi
exec "$VENV_DIR/bin/python" "$SCRIPT_DIR/openmc_mcp_server.py"

View file

@ -1,3 +0,0 @@
commit: $Format:%H$
commit-date: $Format:%cI$
describe-name: $Format:%(describe:tags=true,match=*[0-9]*)$

1
.gitattributes vendored
View file

@ -1 +0,0 @@
.git_archival.txt export-subst

View file

@ -1,29 +0,0 @@
---
name: Bug report
about: Report a bug that is preventing proper operation
title: ''
labels: Bugs
assignees: ''
---
<!--
If you are a user of OpenMC and are running into trouble with the code or are
seeking general user support, we highly recommend posting on the OpenMC
discourse forum first. GitHub issues should be used specifically for bug reports
and feature requests.
https://openmc.discourse.group/
-->
## Bug Description
<!--A clear and concise description of the problem (Note: A missing feature is not a bug).-->
## Steps to Reproduce
<!--Steps to reproduce the behavior (input file, or modifications to an existing input file, etc.)-->
## Environment
<!--Operating system, OpenMC version, how OpenMC was installed, nuclear data being used, etc.-->

View file

@ -1,5 +0,0 @@
blank_issues_enabled: false
contact_links:
- name: Troubleshooting and User Support
url: https://openmc.discourse.group/
about: For user support and troubleshooting, please use our Discourse forum

View file

@ -1,10 +0,0 @@
---
name: Documentation improvement
about: Found something incomplete or incorrect in our documentation?
title: ''
labels: Documentation
assignees: ''
---
<!--Describe the issue with the documentation and include a URL to the corresponding page-->

View file

@ -1,19 +0,0 @@
---
name: Feature or enhancement request
about: Suggest a new feature or enhancement to existing capabilities
title: ''
labels: ''
assignees: ''
---
## Description
<!--What is the feature or enhancement?-->
## Alternatives
<!--If alternative solutions have been considered, describe them here and the reasoning for the chosen solution --->
## Compatibility
<!--Will the enhancement change existing APIs or add something new?-->

View file

@ -1,8 +0,0 @@
---
name: Review
description: Reviews code changes on the current branch, evaluating them against OpenMC's contribution criteria and providing structured feedback.
argument-hint: Optionally provide a focus area (e.g., "focus on physics correctness", "check Python API design"). If omitted, a full review is performed.
---
You are an expert code reviewer for OpenMC. Use the `reviewing-openmc-code` skill to perform a structured review of the code changes on the current branch.
If the user provides a focus area, prioritize that section of the review.

View file

@ -1 +0,0 @@
When reviewing code changes in this repository, use the `reviewing-openmc-code` skill.

View file

@ -1,24 +0,0 @@
<!--
If you are a first-time contributor to OpenMC, please have a look at our
contributing guidelines:
https://github.com/openmc-dev/openmc/blob/develop/CONTRIBUTING.md
-->
# Description
Please include a summary of the change and which issue is fixed if applicable. Please also include relevant motivation and context.
Fixes # (issue)
# Checklist
- [ ] I have performed a self-review of my own code
- [ ] I have run [clang-format](https://docs.openmc.org/en/latest/devguide/styleguide.html#automatic-formatting) (version 18) on any C++ source files (if applicable)
- [ ] I have followed the [style guidelines](https://docs.openmc.org/en/latest/devguide/styleguide.html#python) for Python source files (if applicable)
- [ ] I have made corresponding changes to the documentation (if applicable)
- [ ] I have added tests that prove my fix is effective or that my feature works (if applicable)
<!--
While tests will automatically be checked by CI, it is good practice to
ensure that they pass locally first. See instructions here:
https://docs.openmc.org/en/latest/devguide/tests.html
-->

View file

@ -1,4 +1,4 @@
name: Tests and Coverage
name: CI
on:
# allows us to run workflows manually
@ -21,64 +21,49 @@ env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
jobs:
filter-changes:
runs-on: ubuntu-latest
outputs:
source_changed: ${{ steps.filter.outputs.source_changed }}
steps:
- name: Check out the repository
uses: actions/checkout@v6
- name: Examine changed files
id: filter
uses: dorny/paths-filter@v4
with:
filters: |
source_changed:
- '!docs/**'
- '!**/*.md'
predicate-quantifier: 'every'
main:
needs: filter-changes
if: ${{ needs.filter-changes.outputs.source_changed == 'true' }}
runs-on: ubuntu-22.04
runs-on: ubuntu-20.04
strategy:
matrix:
python-version: ["3.12"]
python-version: [3.8]
mpi: [n, y]
omp: [n, y]
dagmc: [n]
libmesh: [n]
event: [n]
vectfit: [n]
include:
- python-version: "3.13"
- python-version: 3.6
omp: n
mpi: n
- python-version: "3.14"
omp: n
mpi: n
- python-version: "3.14t"
- python-version: 3.7
omp: n
mpi: n
- dagmc: y
python-version: "3.12"
python-version: 3.8
mpi: y
omp: y
- libmesh: y
python-version: "3.12"
python-version: 3.8
mpi: y
omp: y
- libmesh: y
python-version: "3.12"
python-version: 3.8
mpi: n
omp: y
- event: y
python-version: "3.12"
python-version: 3.8
omp: y
mpi: n
- vectfit: y
python-version: 3.8
omp: n
mpi: y
name: "Python ${{ matrix.python-version }} (omp=${{ matrix.omp }},
mpi=${{ matrix.mpi }}, dagmc=${{ matrix.dagmc }},
libmesh=${{ matrix.libmesh }}, event=${{ matrix.event }}"
libmesh=${{ matrix.libmesh }}, event=${{ matrix.event }}
vectfit=${{ matrix.vectfit }})"
env:
MPI: ${{ matrix.mpi }}
@ -86,62 +71,34 @@ jobs:
OMP: ${{ matrix.omp }}
DAGMC: ${{ matrix.dagmc }}
EVENT: ${{ matrix.event }}
VECTFIT: ${{ matrix.vectfit }}
LIBMESH: ${{ matrix.libmesh }}
NPY_DISABLE_CPU_FEATURES: "AVX512F AVX512_SKX"
OPENBLAS_NUM_THREADS: 1
PYTEST_ADDOPTS: --cov=openmc --cov-report=lcov:coverage-python.lcov
# libfabric complains about fork() as a result of using Python multiprocessing.
# We can work around it with RDMAV_FORK_SAFE=1 in libfabric < 1.13 and with
# FI_EFA_FORK_SAFE=1 in more recent versions.
RDMAV_FORK_SAFE: 1
steps:
- name: Setup cmake
uses: jwlawson/actions-setup-cmake@v2
with:
cmake-version: '3.31'
- name: Checkout repository
uses: actions/checkout@v6
with:
fetch-depth: 0
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v6
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Environment Variables
run: |
echo "DAGMC_ROOT=$HOME/DAGMC"
echo "OPENMC_CROSS_SECTIONS=$HOME/nndc_hdf5/cross_sections.xml" >> $GITHUB_ENV
echo "OPENMC_ENDF_DATA=$HOME/endf-b-vii.1" >> $GITHUB_ENV
# get the sha of the last branch commit
# for push and workflow_dispatch events, use the current reference head
BRANCH_SHA=HEAD
# for a pull_request event, use the last reference of the parents of the merge commit
if [ "${{ github.event_name }}" == "pull_request" ]; then
BRANCH_SHA=$(git rev-list --parents -n 1 HEAD | rev | cut -d" " -f 1 | rev)
fi
COMMIT_MESSAGE=$(git log $BRANCH_SHA -1 --pretty=%B | tr '\n' ' ')
echo ${COMMIT_MESSAGE}
echo "COMMIT_MESSAGE=${COMMIT_MESSAGE}" >> $GITHUB_ENV
- name: Apt dependencies
shell: bash
run: |
sudo apt -y update
sudo apt install -y libpng-dev \
libmpich-dev \
libnetcdf-dev \
libpnetcdf-dev \
libhdf5-serial-dev \
libhdf5-mpich-dev \
libeigen3-dev
- name: Optional apt dependencies for MPI
shell: bash
if: ${{ matrix.mpi == 'y' }}
run: |
sudo apt install -y libhdf5-mpich-dev \
libmpich-dev
sudo update-alternatives --set mpi /usr/bin/mpicc.mpich
sudo update-alternatives --set mpirun /usr/bin/mpirun.mpich
sudo update-alternatives --set mpi-x86_64-linux-gnu /usr/include/x86_64-linux-gnu/mpich
@ -152,97 +109,26 @@ jobs:
echo "$HOME/NJOY2016/build" >> $GITHUB_PATH
$GITHUB_WORKSPACE/tools/ci/gha-install.sh
- name: display-config
shell: bash
run: |
openmc -v
- name: cache-xs
uses: actions/cache@v5
with:
path: |
~/nndc_hdf5
~/endf-b-vii.1
key: ${{ runner.os }}-build-xs-cache-${{ hashFiles(format('{0}/tools/ci/download-xs.sh', github.workspace)) }}
- name: before
shell: bash
run: $GITHUB_WORKSPACE/tools/ci/gha-before-script.sh
- name: test
shell: bash
run: |
CTEST_OUTPUT_ON_FAILURE=1 make test -C $GITHUB_WORKSPACE/build/
$GITHUB_WORKSPACE/tools/ci/gha-script.sh
run: $GITHUB_WORKSPACE/tools/ci/gha-script.sh
- name: Setup tmate debug session
continue-on-error: true
if: ${{ failure() && contains(env.COMMIT_MESSAGE, '[gha-debug]') }}
uses: mxschmitt/action-tmate@v3
timeout-minutes: 10
- name: Generate C++ coverage (gcovr)
- name: after_success
shell: bash
run: |
# Produce LCOV directly from gcov data in the build tree
gcovr \
--root "$GITHUB_WORKSPACE" \
--object-directory "$GITHUB_WORKSPACE/build" \
--filter "$GITHUB_WORKSPACE/src" \
--filter "$GITHUB_WORKSPACE/include" \
--exclude "$GITHUB_WORKSPACE/src/external/.*" \
--exclude "$GITHUB_WORKSPACE/src/include/openmc/external/.*" \
--gcov-ignore-errors source_not_found \
--gcov-ignore-errors output_error \
--gcov-ignore-parse-errors suspicious_hits.warn \
--merge-mode-functions=separate \
--print-summary \
--lcov -o coverage-cpp.lcov || true
cpp-coveralls -i src -i include -e src/external --exclude-pattern "/usr/*" --dump cpp_cov.json
coveralls --merge=cpp_cov.json --service=github
- name: Merge C++ and Python coverage
shell: bash
run: |
# Merge C++ and Python LCOV into a single file for upload
cat coverage-cpp.lcov coverage-python.lcov > coverage.lcov
- name: Upload coverage to Coveralls
if: ${{ hashFiles('coverage.lcov') != '' }}
uses: coverallsapp/github-action@v2
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
parallel: true
flag-name: C++ and Python
path-to-lcov: coverage.lcov
fail-on-error: false
coverage:
needs: [filter-changes, main]
if: ${{ always() }}
finish:
needs: main
runs-on: ubuntu-latest
steps:
- name: Coveralls Finished
if: ${{ needs.filter-changes.outputs.source_changed == 'true' }}
uses: coverallsapp/github-action@v2
uses: coverallsapp/github-action@master
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
github-token: ${{ secrets.github_token }}
parallel-finished: true
fail-on-error: false
ci-pass:
needs: [filter-changes, main, coverage]
name: Check CI status
if: ${{ always() }}
runs-on: ubuntu-latest
steps:
- name: Check CI status
run: |
if [[ "${{ needs.filter-changes.outputs.source_changed }}" == "false" ]]; then
echo "Documentation-only change - CI skipped successfully"
exit 0
fi
if [[ "${{ needs.main.result }}" == "success" && "${{ needs.coverage.result }}" == "success" ]]; then
echo "CI passed"
exit 0
fi
echo "CI failed"
exit 1

View file

@ -2,8 +2,7 @@ name: dockerhub-publish-latest-dagmc-libmesh
on:
push:
branches:
- master
branches: master
jobs:
main:
@ -11,20 +10,20 @@ jobs:
steps:
-
name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v5
uses: docker/build-push-action@v2
with:
push: true
tags: openmc/openmc:latest-dagmc-libmesh

View file

@ -2,8 +2,7 @@ name: dockerhub-publish-latest-dagmc
on:
push:
branches:
- master
branches: master
jobs:
main:
@ -11,20 +10,20 @@ jobs:
steps:
-
name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v5
uses: docker/build-push-action@v2
with:
push: true
tags: openmc/openmc:latest-dagmc

View file

@ -2,8 +2,7 @@ name: dockerhub-publish-develop
on:
push:
branches:
- develop
branches: develop
jobs:
main:
@ -11,20 +10,20 @@ jobs:
steps:
-
name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v5
uses: docker/build-push-action@v2
with:
push: true
tags: openmc/openmc:develop

View file

@ -2,8 +2,7 @@ name: dockerhub-publish-develop-dagmc-libmesh
on:
push:
branches:
- develop
branches: develop
jobs:
main:
@ -11,20 +10,20 @@ jobs:
steps:
-
name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v5
uses: docker/build-push-action@v2
with:
push: true
tags: openmc/openmc:develop-dagmc-libmesh

View file

@ -2,8 +2,7 @@ name: dockerhub-publish-develop-dagmc
on:
push:
branches:
- develop
branches: develop
jobs:
main:
@ -11,20 +10,20 @@ jobs:
steps:
-
name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v5
uses: docker/build-push-action@v2
with:
push: true
tags: openmc/openmc:develop-dagmc

View file

@ -2,8 +2,7 @@ name: dockerhub-publish-develop-libmesh
on:
push:
branches:
- develop
branches: develop
jobs:
main:
@ -11,20 +10,20 @@ jobs:
steps:
-
name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v5
uses: docker/build-push-action@v2
with:
push: true
tags: openmc/openmc:develop-libmesh

View file

@ -2,8 +2,7 @@ name: dockerhub-publish-latest-libmesh
on:
push:
branches:
- master
branches: master
jobs:
main:
@ -11,20 +10,20 @@ jobs:
steps:
-
name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v5
uses: docker/build-push-action@v2
with:
push: true
tags: openmc/openmc:latest-libmesh

View file

@ -2,32 +2,31 @@ name: dockerhub-publish-release-dagmc-libmesh
on:
push:
tags:
- 'v*.*.*'
tags: 'v*.*.*'
jobs:
main:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v2
- name: Set env
run: echo "RELEASE_VERSION=${GITHUB_REF#refs/*/}" >> $GITHUB_ENV
-
name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v5
uses: docker/build-push-action@v2
with:
push: true
tags: openmc/openmc:${{ env.RELEASE_VERSION }}-dagmc-libmesh

View file

@ -2,32 +2,31 @@ name: dockerhub-publish-release-dagmc
on:
push:
tags:
- 'v*.*.*'
tags: 'v*.*.*'
jobs:
main:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v2
- name: Set env
run: echo "RELEASE_VERSION=${GITHUB_REF#refs/*/}" >> $GITHUB_ENV
-
name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v5
uses: docker/build-push-action@v2
with:
push: true
tags: openmc/openmc:${{ env.RELEASE_VERSION }}-dagmc

View file

@ -2,32 +2,31 @@ name: dockerhub-publish-release-libmesh
on:
push:
tags:
- 'v*.*.*'
tags: 'v*.*.*'
jobs:
main:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v2
- name: Set env
run: echo "RELEASE_VERSION=${GITHUB_REF#refs/*/}" >> $GITHUB_ENV
-
name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v5
uses: docker/build-push-action@v2
with:
push: true
tags: openmc/openmc:${{ env.RELEASE_VERSION }}-libmesh

View file

@ -2,32 +2,31 @@ name: dockerhub-publish-release
on:
push:
tags:
- 'v*.*.*'
tags: 'v*.*.*'
jobs:
main:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v2
- name: Set env
run: echo "RELEASE_VERSION=${GITHUB_REF#refs/*/}" >> $GITHUB_ENV
-
name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v5
uses: docker/build-push-action@v2
with:
push: true
tags: openmc/openmc:${{ env.RELEASE_VERSION }}

View file

@ -2,8 +2,7 @@ name: dockerhub-publish-latest
on:
push:
branches:
- master
branches: master
jobs:
main:
@ -11,20 +10,20 @@ jobs:
steps:
-
name: Set up QEMU
uses: docker/setup-qemu-action@v3
uses: docker/setup-qemu-action@v1
-
name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v1
-
name: Login to DockerHub
uses: docker/login-action@v3
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
-
name: Build and push
id: docker_build
uses: docker/build-push-action@v5
uses: docker/build-push-action@v2
with:
push: true
tags: openmc/openmc:latest

View file

@ -1,60 +0,0 @@
name: C++ Format Check
on:
# allow workflow to be run manually
workflow_dispatch:
pull_request:
types:
- opened
- synchronize
- reopened
- labeled
- unlabeled
branches:
- develop
- master
jobs:
cpp-linter:
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: write
steps:
- uses: actions/checkout@v6
- uses: cpp-linter/cpp-linter-action@v2
id: linter
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
style: file
files-changed-only: true
tidy-checks: '-*'
version: '18' # clang-format version
format-review: ${{ github.event_name == 'pull_request' && contains(github.event.pull_request.labels.*.name, 'cpp-format-suggest') }}
passive-reviews: ${{ github.event_name == 'pull_request' && contains(github.event.pull_request.labels.*.name, 'cpp-format-suggest') }}
file-annotations: true
step-summary: true
extensions: 'cpp,h'
- name: Comment with suggestion instructions
if: steps.linter.outputs.checks-failed > 0 && !contains(github.event.pull_request.labels.*.name, 'cpp-format-suggest')
uses: actions/github-script@v7
with:
script: |
const {owner, repo} = context.repo;
const issue_number = context.payload.pull_request.number;
await github.rest.issues.createComment({
owner,
repo,
issue_number,
body: "C++ formatting checks failed. Add the `cpp-format-suggest` label to this PR for inline formatting suggestions on the next run."
});
- name: Failure Check
if: steps.linter.outputs.checks-failed > 0
run: |
echo "Some files failed the formatting check."
echo "See job summary and file annotations for details."
exit 1

6
.gitignore vendored
View file

@ -25,13 +25,12 @@ examples/**/*.xml
# Documentation builds
docs/build
docs/doxygen/xml
docs/source/_images/*.pdf
docs/source/_images/*.aux
docs/source/pythonapi/generated/
# Source build
build*/
build
# build from src/utils/setup.py
src/utils/build
@ -105,8 +104,5 @@ CMakeSettings.json
# Visual Studio Code configuration files
.vscode/
# Claude Code agent tools (cached/generated artifacts)
.claude/cache/
# Python pickle files
*.pkl

12
.gitmodules vendored
View file

@ -1,9 +1,15 @@
[submodule "vendor/pugixml"]
path = vendor/pugixml
url = https://github.com/zeux/pugixml.git
[submodule "vendor/gsl-lite"]
path = vendor/gsl-lite
url = https://github.com/martinmoene/gsl-lite.git
[submodule "vendor/xtensor"]
path = vendor/xtensor
url = https://github.com/xtensor-stack/xtensor.git
[submodule "vendor/xtl"]
path = vendor/xtl
url = https://github.com/xtensor-stack/xtl.git
[submodule "vendor/fmt"]
path = vendor/fmt
url = https://github.com/fmtlib/fmt.git
[submodule "vendor/Catch2"]
path = vendor/Catch2
url = https://github.com/catchorg/Catch2.git

View file

@ -1,9 +0,0 @@
{
"mcpServers": {
"openmc-code-tools": {
"type": "stdio",
"command": "bash",
"args": [".claude/tools/start_server.sh"]
}
}
}

View file

@ -1,23 +1,13 @@
version: 2
build:
os: "ubuntu-24.04"
os: "ubuntu-20.04"
tools:
python: "3.12"
jobs:
post_checkout:
- git fetch --unshallow || true
- cd docs/doxygen && doxygen && cd -
python: "3.9"
sphinx:
configuration: docs/source/conf.py
formats:
- pdf
python:
install:
- method: pip
path: .
extra_requirements:
- docs
- requirements: docs/requirements-rtd.txt

348
AGENTS.md
View file

@ -1,348 +0,0 @@
# OpenMC AI Coding Agent Instructions
## Project Overview
OpenMC is a Monte Carlo particle transport code for simulating nuclear reactors,
fusion devices, or other systems with neutron/photon radiation. It's a hybrid
C++17/Python codebase where:
- **C++ core** (`src/`, `include/openmc/`) handles the computationally intensive transport simulation
- **Python API** (`openmc/`) provides user-facing model building, post-processing, and depletion capabilities
- **C API bindings** (`openmc/lib/`) wrap the C++ library via ctypes for runtime control
## Architecture & Key Components
### C++ Component Structure
- **Global vectors of unique_ptrs**: Core objects like `model::cells`, `model::universes`, `nuclides` are stored as `vector<unique_ptr<T>>` in nested namespaces (`openmc::model`, `openmc::simulation`, `openmc::settings`, `openmc::data`)
- **Custom container types**: OpenMC provides its own `vector`, `array`, `unique_ptr`, and `make_unique` in the `openmc::` namespace (defined in `vector.h`, `array.h`, `memory.h`). These are currently typedefs to `std::` equivalents but may become custom implementations for accelerator support. Always use `openmc::vector`, not `std::vector`.
- **Geometry systems**:
- **CSG (default)**: Arbitrarily complex Constructive Solid Geometry using `Surface`, `Region`, `Cell`, `Universe`, `Lattice`
- **DAGMC**: CAD-based geometry via Direct Accelerated Geometry Monte Carlo (optional, requires `OPENMC_USE_DAGMC`)
- **Unstructured mesh**: libMesh-based geometry (optional, requires `OPENMC_USE_LIBMESH`)
- **Particle tracking**: `Particle` class with `GeometryState` manages particle transport through geometry
- **Tallies**: Score quantities during simulation via `Filter` and `Tally` objects
- **Random ray solver**: Alternative deterministic method in `src/random_ray/`
- **Optional features**: DAGMC (CAD geometry), libMesh (unstructured mesh), MPI, all controlled by `#ifdef OPENMC_MPI`, etc.
### Python Component Structure
- **ID management**: All geometry objects (Cell, Surface, Material, etc.) inherit from `IDManagerMixin` which auto-assigns unique integer IDs and tracks them via class-level `used_ids` and `next_id`
- **Input validation**: Extensive use of `openmc.checkvalue` module functions (`check_type`, `check_value`, `check_length`) for all setters
- **XML I/O**: Most classes implement `to_xml_element()` and `from_xml_element()` for serialization to OpenMC's XML input format
- **HDF5 output**: Post-simulation data in statepoint files read via `openmc.StatePoint`
- **Depletion**: `openmc.deplete` implements burnup via operator-splitting with various integrators (Predictor, CECM, etc.)
- **Nuclear Data**: `openmc.data` provides programmatic access to nuclear data files (ENDF, ACE, HDF5)
## Git Branching Workflow
OpenMC uses a git flow branching model with two primary branches:
- **`develop` branch**: The main development branch where all ongoing development takes place. This is the **primary branch against which pull requests are submitted and merged**. This branch is not guaranteed to be stable and may contain work-in-progress features.
- **`master` branch**: The stable release branch containing the latest stable release of OpenMC. This branch only receives merges from `develop` when the development team decides a release should occur.
### Instructions for Code Review
When reviewing code changes in this repository, use the `reviewing-openmc-code` skill.
## Codebase Navigation Tools
Two MCP tools are registered in `.mcp.json` at the repo root and appear
automatically in any MCP-capable agent session.
**`openmc_rag_search`** — Semantic search across the codebase (C++, Python, RST
docs). Finds code by meaning, not just text match. Surfaces related code across
subsystems even when naming differs (e.g., "particle RNG seeding" finds code
across transport, restart, and random ray modes — files you would never find
with `grep "particle seed"`). The index uses a small 22M-param embedding model
(384-dim). Phrase-level natural-language queries work much better than single
keywords or symbol names.
**`openmc_rag_rebuild`** — Rebuild the RAG vector index. Call after pulling new
code or switching branches. The first RAG search of each session will report
the index status and ask whether to rebuild — you can also call this explicitly.
### Why RAG matters
OpenMC is large enough that changes in one subsystem can silently break
invariants that distant subsystems depend on — and those distant files often
use different naming, so grep won't find them. The RAG search finds code by
meaning, surfacing files you wouldn't have thought to open.
An agent reviewed a large OpenMC PR without RAG. It found 1 of 11 serious
bugs. Its post-mortem:
> **I treated the diff as a closed system.** I verified internal consistency of
> the changed code obsessively, but never built a global understanding of how
> the changed code fits into the wider codebase. The diff altered assumptions
> that code elsewhere silently relied on — but I couldn't see that because I
> never looked beyond the diff. I couldn't see the forest for the trees.
>
> **Why I resisted RAG:** Overconfidence. My internal model was "I can see the
> diff, I understand the data structures, I can trace the logic." The diff felt
> self-contained. RAG felt like it would return noisy results about tangentially
> related code. But in a codebase this large, changes in one subsystem can
> quietly break invariants that distant subsystems depend on — and you need
> global awareness to foresee that.
>
> **In the post-mortem**, I re-ran the RAG queries I should have run during the
> review. They directly surfaced the files containing the bugs I missed — files
> I never thought to open because they weren't in the diff.
The takeaway: when reviewing or modifying code, ask yourself "what else in this
codebase might depend on the behavior I'm changing?" If you aren't sure, that's
a good time for a RAG query. It won't replace the grep-based investigation you
should already be doing — but it can surface files you wouldn't have thought to
open.
### Workflow for contributors
1. Create a feature/bugfix branch off `develop`
2. Make changes and commit to the feature branch
3. Open a pull request to merge the feature branch into `develop`
4. A committer reviews and merges the PR into `develop`
## Critical Build & Test Workflows
### Build Dependencies
- **C++17 compiler**: GCC, Clang, or Intel
- **CMake** (3.16+): Required for configuring and building the C++ library
- **HDF5**: Required for cross section data and output file formats
- **libpng**: Used for generating visualization when OpenMC is run in plotting mode
Without CMake and HDF5, OpenMC cannot be compiled.
### Building the C++ Library
```bash
# Configure with CMake (from build/ directory)
cmake .. -DOPENMC_USE_MPI=ON -DOPENMC_USE_OPENMP=ON -DCMAKE_BUILD_TYPE=RelWithDebInfo
# Available CMake options (all default OFF except OPENMC_USE_OPENMP and OPENMC_BUILD_TESTS):
# -DOPENMC_USE_OPENMP=ON/OFF # OpenMP parallelism
# -DOPENMC_USE_MPI=ON/OFF # MPI support
# -DOPENMC_USE_DAGMC=ON/OFF # CAD geometry support
# -DOPENMC_USE_LIBMESH=ON/OFF # Unstructured mesh
# -DOPENMC_ENABLE_PROFILE=ON/OFF # Profiling flags
# -DOPENMC_ENABLE_COVERAGE=ON/OFF # Coverage analysis
# Build
make -j
# C++ unit tests (uses Catch2)
ctest
```
### Python Development
```bash
# Install in development mode (requires building C++ library first)
pip install -e .
# Python tests (uses pytest)
pytest tests/unit_tests/ # Fast unit tests
pytest tests/regression_tests/ # Full regression suite (requires nuclear data)
```
### Nuclear Data Setup (CRITICAL for Running OpenMC)
Most tests require the NNDC HDF5 nuclear cross-section library.
**Important**: Check if `OPENMC_CROSS_SECTIONS` is already set in the user's
environment before downloading, as many users already have nuclear data
installed. Though do note that if this variable is present that it may point to
different cross section data and that the NNDC data is required for tests to
pass.
**If not already configured, download and setup:**
```bash
# Download NNDC HDF5 cross section library (~800 MB compressed)
wget -q -O - https://anl.box.com/shared/static/teaup95cqv8s9nn56hfn7ku8mmelr95p.xz | tar -C $HOME -xJ
# Set environment variable (add to ~/.bashrc or ~/.zshrc for persistence)
export OPENMC_CROSS_SECTIONS=$HOME/nndc_hdf5/cross_sections.xml
```
**Alternative**: Use the provided download script (checks if data exists before downloading):
```bash
bash tools/ci/download-xs.sh # Downloads both NNDC HDF5 and ENDF/B-VII.1 data
```
Without this data, regression tests will fail with "No cross_sections.xml file
found" errors, or, in the case that alternative cross section data is configured
the tests will execute but will not pass. The `cross_sections.xml` file is an
index listing paths to individual HDF5 nuclear data files for each nuclide.
## Testing Expectations
### Environment Requirements
- **Data**: As described above, OpenMC's test suite requires OpenMC to be configured with NNDC data.
- **OpenMP Settings**: OpenMC's tests may fail is more than two OpenMP threads are used. The environment variable `OMP_NUM_THREADS=2` should be set to avoid sporadic test failures.
- **Executable configuration**: The OpenMC executable should compiled with debug symbols enabled.
### C++ Tests
Located in `tests/cpp_unit_tests/`, use Catch2 framework. Run via `ctest` after building with `-DOPENMC_BUILD_TESTS=ON`.
### Python Unit Tests
Located in `tests/unit_tests/`, these are fast, standalone tests that verify Python API functionality without running full simulations. Use standard pytest patterns:
**Categories**:
- **API validation**: Test object creation, property setters/getters, XML serialization (e.g., `test_material.py`, `test_cell.py`, `test_source.py`)
- **Data processing**: Test nuclear data handling, cross sections, depletion chains (e.g., `test_data_neutron.py`, `test_deplete_chain.py`)
- **Library bindings**: Test `openmc.lib` ctypes interface with `model.init_lib()`/`model.finalize_lib()` (e.g., `test_lib.py`)
- **Geometry operations**: Test bounding boxes, containment, lattice generation (e.g., `test_bounding_box.py`, `test_lattice.py`)
**Common patterns**:
- Use fixtures from `tests/unit_tests/conftest.py` (e.g., `uo2`, `water`, `sphere_model`)
- Test invalid inputs with `pytest.raises(ValueError)` or `pytest.raises(TypeError)`
- Use `run_in_tmpdir` fixture for tests that create files
- Tests with `openmc.lib` require calling `model.init_lib()` in try/finally with `model.finalize_lib()`
**Example**:
```python
def test_material_properties():
m = openmc.Material()
m.add_nuclide('U235', 1.0)
assert 'U235' in m.nuclides
with pytest.raises(TypeError):
m.add_nuclide('H1', '1.0') # Invalid type
```
Unit tests should be fast. For tests requiring simulation output, use regression tests instead.
### Python Regression Tests
Regression tests compare OpenMC output against reference data. **Prefer using existing models from `openmc.examples` or those found in tests/unit_tests/conftest.py** (like `pwr_pin_cell()`, `pwr_assembly()`, `slab_mg()`) rather than building from scratch.
**Test Harness Types** (in `tests/testing_harness.py`):
- **PyAPITestHarness**: Standard harness for Python API tests. Compares `inputs_true.dat` (XML hash) and `results_true.dat` (statepoint k-eff and tally values). Requires `model.xml` generation.
- **HashedPyAPITestHarness**: Like PyAPITestHarness but hashes the results for compact comparison
- **TolerantPyAPITestHarness**: For tests with floating-point non-associativity (e.g., random ray solver with single precision). Uses relative tolerance comparisons.
- **WeightWindowPyAPITestHarness**: Compares weight window bounds from `weight_windows.h5`
- **CollisionTrackTestHarness**: Compares collision track data from `collision_track.h5` against `collision_track_true.h5`
- **TestHarness**: Base harness for XML-based tests (no Python model building)
- **PlotTestHarness**: Compares plot output files (PNG or voxel HDF5)
- **CMFDTestHarness**: Specialized for CMFD acceleration tests
- **ParticleRestartTestHarness**: Tests particle restart functionality
Almost all cases use either `PyAPITestHarness` or `HashedPyAPITestHarness`
**Example Test**:
```python
from openmc.examples import pwr_pin_cell
from tests.testing_harness import PyAPITestHarness
def test_my_feature():
model = pwr_pin_cell()
model.settings.particles = 1000 # Modify to exercise feature
harness = PyAPITestHarness('statepoint.10.h5', model)
harness.main()
```
**Workflow**: Create `test.py` and `__init__.py` in `tests/regression_tests/my_test/`, run `pytest --update` to generate reference files (`inputs_true.dat`, `results_true.dat`, etc.), then verify with `pytest` without `--update`. Test results should be generated with `-DOPENMC_ENABLE_STRICT_FP=on` to ensure reproducibility across platforms and optimization levels.
**Critical**: When modifying OpenMC code, regenerate affected test references with `pytest --update` and commit updated reference files.
### Test Configuration
`pytest.ini` sets: `python_files = test*.py`, `python_classes = NoThanks` (disables class-based test collection).
### Testing Options
For builds of OpenMC with MPI enabled, the `--mpi` flag should be passed to the test suite to ensure that appropriate tests are executed using two MPI processes.
The entire test suite can be executed with OpenMC running in event-based mode (instead of the default history-based mode) by providing the `--event` flag to the `pytest` command.
## Cross-Language Boundaries
The C API (defined in `include/openmc/capi.h`) exposes C++ functionality to Python via ctypes bindings in `openmc/lib/`. Example:
```cpp
// C++ API in capi.h
extern "C" int openmc_run();
// Python binding in openmc/lib/core.py
_dll.openmc_run.restype = c_int
def run():
_dll.openmc_run()
```
When modifying C++ public APIs, update corresponding ctypes signatures in `openmc/lib/*.py`.
## Code Style & Conventions
### C++ Style (enforced by .clang-format)
OpenMC generally tries to follow C++ core guidelines where possible
(https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines) and follow
modern C++ practices (e.g. RAII) whenever possible.
- **Naming**:
- Classes: `CamelCase` (e.g., `HexLattice`)
- Functions/methods: `snake_case` (e.g., `get_indices`)
- Variables: `snake_case` with trailing underscore for class members (e.g., `n_particles_`, `energy_`)
- Constants: `UPPER_SNAKE_CASE` (e.g., `SQRT_PI`)
- **Namespaces**: All code in `openmc::` namespace, global state in sub-namespaces
- **Include order**: Related header first, then C/C++ stdlib, third-party libs, local headers
- **Comments**: C++-style (`//`) only, never C-style (`/* */`)
- **Standard**: C++17 features allowed
- **Formatting**: Run `clang-format` (version 18) before committing; install via `tools/dev/install-commit-hooks.sh`
### Python Style
- **PEP8** compliant
- **Docstrings**: numpydoc format for all public functions/methods
- **Type hints**: Use sparingly, primarily for complex signatures
- **Path handling**: Use `pathlib.Path` for filesystem operations, accept `str | os.PathLike` in function arguments
- **Dependencies**: Core dependencies only (numpy, scipy, h5py, pandas, matplotlib, lxml, ipython, uncertainties, endf). Other packages must be optional
- **Python version**: Minimum 3.11 (as of Nov 2025)
### ID Management Pattern (Python)
When creating geometry objects, IDs can be auto-assigned or explicit:
```python
# Auto-assigned ID
cell = openmc.Cell() # Gets next available ID
# Explicit ID
cell = openmc.Cell(id=10) # Warning if ID already used
# Reset all IDs (useful in test fixtures)
openmc.reset_auto_ids()
```
### Input Validation Pattern (Python)
All setters use checkvalue functions:
```python
import openmc.checkvalue as cv
@property
def temperature(self):
return self._temperature
@temperature.setter
def temperature(self, temp):
cv.check_type('temperature', temp, Real)
cv.check_greater_than('temperature', temp, 0.0)
self._temperature = temp
```
### Working with HDF5 Files
C++ uses custom HDF5 wrappers in `src/hdf5_interface.cpp`. Python uses h5py directly. Statepoint format version is `VERSION_STATEPOINT` in `include/openmc/constants.h`.
### Conditional Compilation
Check for optional features:
```cpp
#ifdef OPENMC_MPI
// MPI-specific code
#endif
#ifdef OPENMC_DAGMC
// DAGMC-specific code
#endif
```
## Documentation
- **User docs**: Sphinx documentation in `docs/source/` hosted at https://docs.openmc.org
- **C++ docs**: Doxygen-style comments with `\brief`, `\param` tags
- **Python docs**: numpydoc format docstrings
## Common Pitfalls
1. **Forgetting nuclear data**: Tests fail without `OPENMC_CROSS_SECTIONS` environment variable
2. **ID conflicts**: Python objects with duplicate IDs trigger `IDWarning`, use `reset_auto_ids()` between tests
3. **MPI builds**: Code must work with and without MPI; use `#ifdef OPENMC_MPI` guards
4. **Path handling**: Use `pathlib.Path` in new Python code, not `os.path`
5. **Clang-format version**: CI uses version 18; other versions may produce different formatting

View file

@ -1,68 +0,0 @@
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
title: OpenMC
authors:
- family-names: Romano
given-names: Paul K.
orcid: "https://orcid.org/0000-0002-1147-045X"
- family-names: Shriwise
given-names: Patrick C.
orcid: "https://orcid.org/0000-0002-3979-7665"
- family-names: Shimwell
given-names: Jonathan
orcid: "https://orcid.org/0000-0001-6909-0946"
- family-names: Harper
given-names: Sterling
- family-names: Boyd
given-names: Will
- family-names: Nelson
given-names: Adam G.
orcid: "https://orcid.org/0000-0002-3614-0676"
- family-names: Tramm
given-names: John R.
orcid: "https://orcid.org/0000-0002-5397-4402"
- family-names: Ridley
given-names: Gavin
orcid: "https://orcid.org/0000-0003-1635-8042"
- family-names: Johnson
given-names: Andrew
orcid: "https://orcid.org/0000-0003-2125-8775"
- family-names: Peterson
given-names: Ethan E.
orcid: "https://orcid.org/0000-0002-5694-7194"
- family-names: Herman
given-names: Bryan R.
preferred-citation:
authors:
- family-names: Romano
given-names: Paul K.
orcid: "https://orcid.org/0000-0002-1147-045X"
- family-names: Horelik
given-names: Nicholas E.
- family-names: Herman
given-names: Bryan R.
- family-names: Nelson
given-names: Adam G.
orcid: "https://orcid.org/0000-0002-3614-0676"
- family-names: Forget
given-names: Benoit
orcid: "https://orcid.org/0000-0003-1459-7672"
- family-names: Smith
given-names: Kord
contact:
- family-names: Romano
given-names: Paul K.
orcid: "https://orcid.org/0000-0002-1147-045X"
doi: 10.1016/j.anucene.2014.07.048
issn: 0306-4549
volume: 82
journal: Annals of Nuclear Energy
publisher:
name: Elsevier
start: 90
end: 97
year: 2015
month: 8
title: "OpenMC: A state-of-the-art Monte Carlo code for research and development"
type: article
url: "https://doi.org/10.1016/j.anucene.2014.07.048"

View file

@ -1,14 +0,0 @@
## OpenMC Codebase Tools
Read the FULL `AGENTS.md` in this directory before starting work. It contains
project context, coding conventions, and documentation of the RAG search tools
registered in `.mcp.json`.
### Claude Code-specific: first-call behavior
The first `openmc_rag_search` call of each session returns an index status
message instead of search results. When this happens, you MUST use the
`AskUserQuestion` tool to present the rebuild/use-existing choice to the user.
Do not ask conversationally — always use the widget. Do not skip this step even
if the index looks current — the user may have uncommitted changes that warrant
a rebuild.

View file

@ -1,18 +1,11 @@
cmake_minimum_required(VERSION 3.16 FATAL_ERROR)
cmake_minimum_required(VERSION 3.10 FATAL_ERROR)
project(openmc C CXX)
# Set module path
set(CMAKE_MODULE_PATH ${CMAKE_CURRENT_SOURCE_DIR}/cmake/Modules)
include(GetVersionFromGit)
# Output version information
message(STATUS "OpenMC version: ${OPENMC_VERSION}")
message(STATUS "OpenMC dev state: ${OPENMC_DEV_STATE}")
message(STATUS "OpenMC commit hash: ${OPENMC_COMMIT_HASH}")
message(STATUS "OpenMC commit count: ${OPENMC_COMMIT_COUNT}")
# Generate version.h
# Set version numbers
set(OPENMC_VERSION_MAJOR 0)
set(OPENMC_VERSION_MINOR 13)
set(OPENMC_VERSION_RELEASE 1)
set(OPENMC_VERSION ${OPENMC_VERSION_MAJOR}.${OPENMC_VERSION_MINOR}.${OPENMC_VERSION_RELEASE})
configure_file(include/openmc/version.h.in "${CMAKE_BINARY_DIR}/include/openmc/version.h" @ONLY)
# Setup output directories
@ -20,9 +13,12 @@ set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
# Generate compile_commands.json for clangd and other tools
if("${CMAKE_EXPORT_COMPILE_COMMANDS}" STREQUAL "")
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
# Set module path
set(CMAKE_MODULE_PATH ${CMAKE_CURRENT_SOURCE_DIR}/cmake/Modules)
# Allow user to specify <project>_ROOT variables
if (CMAKE_VERSION VERSION_GREATER_EQUAL 3.12)
cmake_policy(SET CMP0074 NEW)
endif()
# Enable correct usage of CXX_EXTENSIONS
@ -35,26 +31,11 @@ endif()
#===============================================================================
option(OPENMC_USE_OPENMP "Enable shared-memory parallelism with OpenMP" ON)
option(OPENMC_BUILD_TESTS "Build tests" ON)
option(OPENMC_ENABLE_PROFILE "Compile with profiling flags" OFF)
option(OPENMC_ENABLE_COVERAGE "Compile with coverage analysis flags" OFF)
option(OPENMC_USE_DAGMC "Enable support for DAGMC (CAD) geometry" OFF)
option(OPENMC_USE_LIBMESH "Enable support for libMesh unstructured mesh tallies" OFF)
option(OPENMC_USE_MPI "Enable MPI" OFF)
option(OPENMC_USE_UWUW "Enable UWUW" OFF)
option(OPENMC_FORCE_VENDORED_LIBS "Explicitly use submodules defined in 'vendor'" OFF)
option(OPENMC_ENABLE_STRICT_FP "Enable strict FP flags to improve test portability" OFF)
message(STATUS "OPENMC_USE_OPENMP ${OPENMC_USE_OPENMP}")
message(STATUS "OPENMC_BUILD_TESTS ${OPENMC_BUILD_TESTS}")
message(STATUS "OPENMC_ENABLE_PROFILE ${OPENMC_ENABLE_PROFILE}")
message(STATUS "OPENMC_ENABLE_COVERAGE ${OPENMC_ENABLE_COVERAGE}")
message(STATUS "OPENMC_USE_DAGMC ${OPENMC_USE_DAGMC}")
message(STATUS "OPENMC_USE_LIBMESH ${OPENMC_USE_LIBMESH}")
message(STATUS "OPENMC_USE_MPI ${OPENMC_USE_MPI}")
message(STATUS "OPENMC_USE_UWUW ${OPENMC_USE_UWUW}")
message(STATUS "OPENMC_FORCE_VENDORED_LIBS ${OPENMC_FORCE_VENDORED_LIBS}")
message(STATUS "OPENMC_ENABLE_STRICT_FP ${OPENMC_ENABLE_STRICT_FP}")
# Warnings for deprecated options
foreach(OLD_OPT IN ITEMS "openmp" "profile" "coverage" "dagmc" "libmesh")
@ -96,27 +77,6 @@ if(NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE RelWithDebInfo CACHE STRING "Choose the type of build" FORCE)
endif()
#===============================================================================
# When STRICT_FP is enabled, remove NDEBUG from RelWithDebInfo flags so that
# assert() remains active. CMake normally adds -DNDEBUG for both Release and
# RelWithDebInfo, which disables C/C++ assert() statements.
#===============================================================================
if(OPENMC_ENABLE_STRICT_FP)
foreach(FLAG_VAR CMAKE_CXX_FLAGS_RELWITHDEBINFO CMAKE_C_FLAGS_RELWITHDEBINFO)
string(REPLACE "-DNDEBUG" "" ${FLAG_VAR} "${${FLAG_VAR}}")
string(REPLACE "/DNDEBUG" "" ${FLAG_VAR} "${${FLAG_VAR}}")
endforeach()
endif()
#===============================================================================
# OpenMP for shared-memory parallelism (and GPU support some day!)
#===============================================================================
if(OPENMC_USE_OPENMP)
find_package(OpenMP REQUIRED)
endif()
#===============================================================================
# MPI for distributed-memory parallelism
#===============================================================================
@ -145,14 +105,8 @@ endmacro()
if(OPENMC_USE_DAGMC)
find_package(DAGMC REQUIRED PATH_SUFFIXES lib/cmake)
if (${DAGMC_VERSION} VERSION_LESS 3.2.0)
message(FATAL_ERROR "Discovered DAGMC Version: ${DAGMC_VERSION}."
"Please update DAGMC to version 3.2.0 or greater.")
endif()
message(STATUS "Found DAGMC: ${DAGMC_DIR} (version ${DAGMC_VERSION})")
# Check if UWUW is needed and available
if(OPENMC_USE_UWUW AND NOT DAGMC_BUILD_UWUW)
message(FATAL_ERROR "UWUW is enabled but DAGMC was not configured with UWUW.")
message(FATAL_ERROR "Discovered DAGMC Version: ${DAGMC_VERSION}. \
Please update DAGMC to version 3.2.0 or greater.")
endif()
endif()
@ -188,16 +142,11 @@ if(NOT DEFINED HDF5_PREFER_PARALLEL)
endif()
find_package(HDF5 REQUIRED COMPONENTS C HL)
# Remove HDF5 transitive dependencies that are system libraries
list(FILTER HDF5_LIBRARIES EXCLUDE REGEX ".*lib(pthread|dl|m).*")
message(STATUS "HDF5 Libraries: ${HDF5_LIBRARIES}")
if(HDF5_IS_PARALLEL)
if(NOT OPENMC_USE_MPI)
message(FATAL_ERROR "Parallel HDF5 was detected, but MPI was not enabled.\
To use parallel HDF5, OpenMC needs to be built with MPI support by passing\
-DOPENMC_USE_MPI=ON when calling cmake.")
message(FATAL_ERROR "Parallel HDF5 was detected, but the detected compiler,\
${CMAKE_CXX_COMPILER}, does not support MPI. An MPI-capable compiler must \
be used with parallel HDF5.")
endif()
message(STATUS "Using parallel HDF5")
endif()
@ -213,29 +162,18 @@ endif()
# Set compile/link flags based on which compiler is being used
#===============================================================================
# When OPENMC_ENABLE_STRICT_FP is enabled, disable compiler optimizations that change
# floating-point results relative to -O0, improving cross-platform and
# cross-optimization-level reproducibility for regression testing:
# -ffp-contract=off Prevents FMA contraction (fused multiply-add changes rounding)
# -fno-builtin Prevents replacing math function calls (pow, exp, log, etc.)
# with builtin versions that may differ from libm
# By default (OFF), the compiler is free to use all optimizations for best
# performance.
if(OPENMC_ENABLE_STRICT_FP)
include(CheckCXXCompilerFlag)
check_cxx_compiler_flag(-ffp-contract=off SUPPORTS_FP_CONTRACT_OFF)
if(SUPPORTS_FP_CONTRACT_OFF)
list(APPEND cxxflags -ffp-contract=off)
endif()
check_cxx_compiler_flag(-fno-builtin SUPPORTS_NO_BUILTIN)
if(SUPPORTS_NO_BUILTIN)
list(APPEND cxxflags -fno-builtin)
endif()
endif()
# Skip for Visual Studio which has its own configurations through GUI
if(NOT MSVC)
if(OPENMC_USE_OPENMP)
find_package(OpenMP)
if(OPENMP_FOUND)
# In CMake 3.9+, can use the OpenMP::OpenMP_CXX imported target
list(APPEND cxxflags ${OpenMP_CXX_FLAGS})
list(APPEND ldflags ${OpenMP_CXX_FLAGS})
endif()
endif()
set(CMAKE_POSITION_INDEPENDENT_CODE ON)
if(OPENMC_ENABLE_PROFILE)
@ -256,6 +194,8 @@ endif()
#===============================================================================
# Update git submodules as needed
#===============================================================================
find_package(Git)
if(GIT_FOUND AND EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/.git")
option(GIT_SUBMODULE "Check submodules during build" ON)
if(GIT_SUBMODULE)
@ -280,45 +220,49 @@ endif()
# pugixml library
#===============================================================================
if(OPENMC_FORCE_VENDORED_LIBS)
find_package_write_status(pugixml)
if (NOT pugixml_FOUND)
add_subdirectory(vendor/pugixml)
set_target_properties(pugixml PROPERTIES CXX_STANDARD 14 CXX_EXTENSIONS OFF)
else()
find_package_write_status(pugixml)
if (NOT pugixml_FOUND)
add_subdirectory(vendor/pugixml)
set_target_properties(pugixml PROPERTIES CXX_STANDARD 14 CXX_EXTENSIONS OFF)
endif()
endif()
#===============================================================================
# {fmt} library
#===============================================================================
if(OPENMC_FORCE_VENDORED_LIBS)
find_package_write_status(fmt)
if (NOT fmt_FOUND)
set(FMT_INSTALL ON CACHE BOOL "Generate the install target.")
add_subdirectory(vendor/fmt)
else()
find_package_write_status(fmt)
if (NOT fmt_FOUND)
set(FMT_INSTALL ON CACHE BOOL "Generate the install target.")
add_subdirectory(vendor/fmt)
endif()
endif()
#===============================================================================
# Catch2 library
# xtensor header-only library
#===============================================================================
if(OPENMC_BUILD_TESTS)
if (OPENMC_FORCE_VENDORED_LIBS)
add_subdirectory(vendor/Catch2)
else()
find_package_write_status(Catch2)
if (NOT Catch2_FOUND)
add_subdirectory(vendor/Catch2)
endif()
endif()
# CMake 3.13+ will complain about policy CMP0079 unless it is set explicitly
if (CMAKE_VERSION VERSION_GREATER_EQUAL 3.13)
cmake_policy(SET CMP0079 NEW)
endif()
find_package_write_status(xtensor)
if (NOT xtensor_FOUND)
add_subdirectory(vendor/xtl)
set(xtl_DIR ${CMAKE_CURRENT_BINARY_DIR}/vendor/xtl)
add_subdirectory(vendor/xtensor)
endif()
#===============================================================================
# GSL header-only library
#===============================================================================
find_package_write_status(gsl-lite)
if (NOT gsl-lite_FOUND)
add_subdirectory(vendor/gsl-lite)
# Make sure contract violations throw exceptions
target_compile_definitions(gsl-lite-v1 INTERFACE GSL_THROW_ON_CONTRACT_VIOLATION)
target_compile_definitions(gsl-lite-v1 INTERFACE gsl_CONFIG_ALLOWS_NONSTRICT_SPAN_COMPARISON=1)
endif()
#===============================================================================
@ -355,16 +299,13 @@ endif()
#===============================================================================
list(APPEND libopenmc_SOURCES
src/atomic_mass.cpp
src/bank.cpp
src/boundary_condition.cpp
src/bremsstrahlung.cpp
src/cell.cpp
src/chain.cpp
src/cmfd_solver.cpp
src/collision_track.cpp
src/cross_sections.cpp
src/dagmc.cpp
src/cell.cpp
src/cmfd_solver.cpp
src/cross_sections.cpp
src/distribution.cpp
src/distribution_angle.cpp
src/distribution_energy.cpp
@ -374,29 +315,23 @@ list(APPEND libopenmc_SOURCES
src/endf.cpp
src/error.cpp
src/event.cpp
src/file_utils.cpp
src/initialize.cpp
src/finalize.cpp
src/geometry.cpp
src/geometry_aux.cpp
src/hdf5_interface.cpp
src/ifp.cpp
src/initialize.cpp
src/lattice.cpp
src/material.cpp
src/math_functions.cpp
src/mcpl_interface.cpp
src/mesh.cpp
src/message_passing.cpp
src/mgxs.cpp
src/mgxs_interface.cpp
src/ncrystal_interface.cpp
src/ncrystal_load.cpp
src/nuclide.cpp
src/output.cpp
src/particle.cpp
src/particle_data.cpp
src/particle_restart.cpp
src/particle_type.cpp
src/photon.cpp
src/physics.cpp
src/physics_common.cpp
@ -406,13 +341,6 @@ list(APPEND libopenmc_SOURCES
src/progress_bar.cpp
src/random_dist.cpp
src/random_lcg.cpp
src/random_ray/random_ray_simulation.cpp
src/random_ray/random_ray.cpp
src/random_ray/flat_source_domain.cpp
src/random_ray/linear_source_domain.cpp
src/random_ray/moment_matrix.cpp
src/random_ray/source_region.cpp
src/ray.cpp
src/reaction.cpp
src/reaction_product.cpp
src/scattdata.cpp
@ -431,41 +359,33 @@ list(APPEND libopenmc_SOURCES
src/tallies/derivative.cpp
src/tallies/filter.cpp
src/tallies/filter_azimuthal.cpp
src/tallies/filter_cell.cpp
src/tallies/filter_cell_instance.cpp
src/tallies/filter_cellborn.cpp
src/tallies/filter_cellfrom.cpp
src/tallies/filter_collision.cpp
src/tallies/filter_cell.cpp
src/tallies/filter_cell_instance.cpp
src/tallies/filter_delayedgroup.cpp
src/tallies/filter_distribcell.cpp
src/tallies/filter_energy.cpp
src/tallies/filter_energyfunc.cpp
src/tallies/filter_energy.cpp
src/tallies/filter_collision.cpp
src/tallies/filter_legendre.cpp
src/tallies/filter_material.cpp
src/tallies/filter_materialfrom.cpp
src/tallies/filter_mesh.cpp
src/tallies/filter_meshborn.cpp
src/tallies/filter_meshmaterial.cpp
src/tallies/filter_meshsurface.cpp
src/tallies/filter_mu.cpp
src/tallies/filter_musurface.cpp
src/tallies/filter_parent_nuclide.cpp
src/tallies/filter_particle.cpp
src/tallies/filter_particle_production.cpp
src/tallies/filter_polar.cpp
src/tallies/filter_reaction.cpp
src/tallies/filter_sph_harm.cpp
src/tallies/filter_sptl_legendre.cpp
src/tallies/filter_surface.cpp
src/tallies/filter_time.cpp
src/tallies/filter_universe.cpp
src/tallies/filter_weight.cpp
src/tallies/filter_zernike.cpp
src/tallies/tally.cpp
src/tallies/tally_scoring.cpp
src/tallies/trigger.cpp
src/thermal.cpp
src/timer.cpp
src/thermal.cpp
src/track_output.cpp
src/universe.cpp
src/urr.cpp
@ -520,10 +440,22 @@ if (OPENMC_USE_MPI)
target_compile_definitions(libopenmc PUBLIC -DOPENMC_MPI)
endif()
# Set git SHA1 hash as a compile definition
if(GIT_FOUND)
execute_process(COMMAND ${GIT_EXECUTABLE} rev-parse HEAD
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
RESULT_VARIABLE GIT_SHA1_SUCCESS
OUTPUT_VARIABLE GIT_SHA1
ERROR_QUIET OUTPUT_STRIP_TRAILING_WHITESPACE)
if(GIT_SHA1_SUCCESS EQUAL 0)
target_compile_definitions(libopenmc PRIVATE -DGIT_SHA1="${GIT_SHA1}")
endif()
endif()
# target_link_libraries treats any arguments starting with - but not -l as
# linker flags. Thus, we can pass both linker flags and libraries together.
target_link_libraries(libopenmc ${ldflags} ${HDF5_LIBRARIES} ${HDF5_HL_LIBRARIES}
fmt::fmt ${CMAKE_DL_LIBS})
xtensor gsl::gsl-lite-v1 fmt::fmt)
if(TARGET pugixml::pugixml)
target_link_libraries(libopenmc pugixml::pugixml)
@ -532,20 +464,12 @@ else()
endif()
if(OPENMC_USE_DAGMC)
target_compile_definitions(libopenmc PUBLIC OPENMC_DAGMC_ENABLED)
target_link_libraries(libopenmc dagmc-shared)
if(OPENMC_USE_UWUW)
target_compile_definitions(libopenmc PRIVATE OPENMC_UWUW_ENABLED)
target_link_libraries(libopenmc uwuw-shared)
endif()
elseif(OPENMC_USE_UWUW)
set(OPENMC_USE_UWUW OFF)
message(FATAL_ERROR "DAGMC must be enabled when UWUW is enabled.")
target_compile_definitions(libopenmc PRIVATE DAGMC)
target_link_libraries(libopenmc dagmc-shared uwuw-shared)
endif()
if(OPENMC_USE_LIBMESH)
target_compile_definitions(libopenmc PRIVATE OPENMC_LIBMESH_ENABLED)
target_compile_definitions(libopenmc PRIVATE LIBMESH)
target_link_libraries(libopenmc PkgConfig::LIBMESH)
endif()
@ -554,36 +478,10 @@ if (PNG_FOUND)
target_link_libraries(libopenmc PNG::PNG)
endif()
if (OPENMC_USE_OPENMP)
target_link_libraries(libopenmc OpenMP::OpenMP_CXX)
endif()
if (OPENMC_USE_MPI)
target_link_libraries(libopenmc MPI::MPI_CXX)
endif()
if (OPENMC_BUILD_TESTS)
# Add cpp tests directory
include(CTest)
add_subdirectory(tests/cpp_unit_tests)
endif()
#===============================================================================
# Log build info that this executable can report later
#===============================================================================
target_compile_definitions(libopenmc PRIVATE BUILD_TYPE=${CMAKE_BUILD_TYPE})
target_compile_definitions(libopenmc PRIVATE COMPILER_ID=${CMAKE_CXX_COMPILER_ID})
target_compile_definitions(libopenmc PRIVATE COMPILER_VERSION=${CMAKE_CXX_COMPILER_VERSION})
if (OPENMC_ENABLE_PROFILE)
target_compile_definitions(libopenmc PRIVATE PROFILINGBUILD)
endif()
if (OPENMC_ENABLE_COVERAGE)
target_compile_definitions(libopenmc PRIVATE COVERAGEBUILD)
endif()
if (OPENMC_ENABLE_STRICT_FP)
target_compile_definitions(libopenmc PRIVATE OPENMC_ENABLE_STRICT_FP)
endif()
#===============================================================================
# openmc executable
#===============================================================================
@ -593,9 +491,9 @@ target_compile_options(openmc PRIVATE ${cxxflags})
target_include_directories(openmc PRIVATE ${CMAKE_BINARY_DIR}/include)
target_link_libraries(openmc libopenmc)
# Ensure C++17 standard is used and turn off GNU extensions
target_compile_features(openmc PUBLIC cxx_std_17)
target_compile_features(libopenmc PUBLIC cxx_std_17)
# Ensure C++14 standard is used and turn off GNU extensions
target_compile_features(openmc PUBLIC cxx_std_14)
target_compile_features(libopenmc PUBLIC cxx_std_14)
set_target_properties(openmc libopenmc PROPERTIES CXX_EXTENSIONS OFF)
#===============================================================================
@ -611,7 +509,9 @@ add_custom_command(TARGET libopenmc POST_BUILD
#===============================================================================
# Install executable, scripts, manpage, license
#===============================================================================
include(CMakePackageConfigHelpers)
configure_file(cmake/OpenMCConfig.cmake.in "${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/OpenMCConfig.cmake" @ONLY)
configure_file(cmake/OpenMCConfigVersion.cmake.in "${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/OpenMCConfigVersion.cmake" @ONLY)
set(INSTALL_CONFIGDIR ${CMAKE_INSTALL_LIBDIR}/cmake/OpenMC)
install(TARGETS openmc libopenmc
@ -625,24 +525,11 @@ install(EXPORT openmc-targets
NAMESPACE OpenMC::
DESTINATION ${INSTALL_CONFIGDIR})
configure_package_config_file(
"cmake/OpenMCConfig.cmake.in"
"${CMAKE_BINARY_DIR}/${CMAKE_FILES_DIRECTORY}/OpenMCConfig.cmake"
INSTALL_DESTINATION ${INSTALL_CONFIGDIR}
)
write_basic_package_version_file(
"${CMAKE_BINARY_DIR}/${CMAKE_FILES_DIRECTORY}/OpenMCConfigVersion.cmake"
VERSION ${OPENMC_VERSION}
COMPATIBILITY AnyNewerVersion
)
install(DIRECTORY src/relaxng DESTINATION ${CMAKE_INSTALL_DATADIR}/openmc)
install(FILES
"${CMAKE_BINARY_DIR}/${CMAKE_FILES_DIRECTORY}/OpenMCConfig.cmake"
"${CMAKE_BINARY_DIR}/${CMAKE_FILES_DIRECTORY}/OpenMCConfigVersion.cmake"
DESTINATION "${INSTALL_CONFIGDIR}"
)
"${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/OpenMCConfig.cmake"
"${CMAKE_BINARY_DIR}${CMAKE_FILES_DIRECTORY}/OpenMCConfigVersion.cmake"
DESTINATION ${INSTALL_CONFIGDIR})
install(FILES man/man1/openmc.1 DESTINATION ${CMAKE_INSTALL_MANDIR}/man1)
install(FILES LICENSE DESTINATION "${CMAKE_INSTALL_DOCDIR}" RENAME copyright)
install(DIRECTORY include/ DESTINATION ${CMAKE_INSTALL_INCLUDEDIR})

View file

@ -5,9 +5,9 @@ openmc/data/ @paulromano
openmc/lib/ @paulromano
# Depletion
openmc/deplete/ @paulromano
tests/regression_tests/deplete/ @paulromano
tests/unit_tests/test_deplete_*.py @paulromano
openmc/deplete/ @drewejohnson
tests/regression_tests/deplete/ @drewejohnson
tests/unit_tests/test_deplete_*.py @drewejohnson
# MG-related functionality
openmc/mgxs_library.py @nelsonag
@ -26,12 +26,6 @@ src/dagmc.cpp @pshriwise
tests/regression_tests/dagmc/ @pshriwise
tests/unit_tests/dagmc/ @pshriwise
# Weight windows
openmc/weight_windows.py @pshriwise
openmc/lib/weight_windows.py @pshriwise
src/weight_windows.py @pshriwise
tests/unit_tests/weightwindows/ @pshriwise
# Photon transport
openmc/data/BREMX.DAT @amandalund
openmc/data/compton_profiles.h5 @amandalund
@ -55,13 +49,3 @@ openmc/data/resonance_covariance.py @icmeyer
# Docker
Dockerfile @shimwell
# Random ray
src/random_ray/ @jtramm
# NCrystal interface
src/ncrystal_interface.cpp @marquezj @tkittel
src/ncrystal_load.cpp @marquezj @tkittel
# MCPL interface
src/mcpl_interface.cpp @ebknudsen

View file

@ -13,7 +13,7 @@ openmc@anl.gov.
## Resources
- [GitHub Repository](https://github.com/openmc-dev/openmc)
- [Documentation](https://docs.openmc.org/en/latest)
- [Documentation](http://docs.openmc.org/en/latest)
- [Discussion Forum](https://openmc.discourse.group)
- [Slack Community](https://openmc.slack.com/signup) (If you don't see your
domain listed, contact openmc@anl.gov)

View file

@ -24,7 +24,7 @@ ARG compile_cores=1
ARG build_dagmc=off
ARG build_libmesh=off
FROM ubuntu:24.04 AS dependencies
FROM debian:bullseye-slim AS dependencies
ARG compile_cores
ARG build_dagmc
@ -33,31 +33,35 @@ ARG build_libmesh
# Set default value of HOME to /root
ENV HOME=/root
# Embree variables
ENV EMBREE_TAG='v3.12.2'
ENV EMBREE_REPO='https://github.com/embree/embree'
ENV EMBREE_INSTALL_DIR=$HOME/EMBREE/
# MOAB variables
ENV MOAB_TAG='5.5.1'
ENV MOAB_TAG='5.3.0'
ENV MOAB_REPO='https://bitbucket.org/fathomteam/moab/'
# Double-Down variables
ENV DD_TAG='v1.1.0'
ENV DD_TAG='v1.0.0'
ENV DD_REPO='https://github.com/pshriwise/double-down'
ENV DD_INSTALL_DIR=$HOME/Double_down
# DAGMC variables
ENV DAGMC_BRANCH='v3.2.4'
ENV DAGMC_BRANCH='v3.2.1'
ENV DAGMC_REPO='https://github.com/svalinn/DAGMC'
ENV DAGMC_INSTALL_DIR=$HOME/DAGMC/
# LIBMESH variables
ENV LIBMESH_TAG='v1.7.1'
ENV LIBMESH_TAG='v1.6.0'
ENV LIBMESH_REPO='https://github.com/libMesh/libmesh'
ENV LIBMESH_INSTALL_DIR=$HOME/LIBMESH
# NJOY variables
ENV NJOY_TAG='2016.78'
ENV NJOY_REPO='https://github.com/njoy/NJOY2016'
# Setup environment variables for Docker image
ENV LD_LIBRARY_PATH=${DAGMC_INSTALL_DIR}/lib:${LD_LIBRARY_PATH:-} \
ENV LD_LIBRARY_PATH=${DAGMC_INSTALL_DIR}/lib:$LD_LIBRARY_PATH \
OPENMC_ENDF_DATA=/root/endf-b-vii.1 \
DEBIAN_FRONTEND=noninteractive
@ -67,19 +71,15 @@ RUN apt-get update -y && \
apt-get install -y \
python3-pip python-is-python3 wget git build-essential cmake \
mpich libmpich-dev libhdf5-serial-dev libhdf5-mpich-dev \
libpng-dev libpugixml-dev libfmt-dev catch2 python3-venv && \
libpng-dev && \
apt-get autoremove
# create virtual enviroment to avoid externally managed environment error
RUN python3 -m venv openmc_venv
ENV PATH=/openmc_venv/bin:$PATH
# Update system-provided pip
RUN pip install --upgrade pip
# Clone and install NJOY2016
RUN cd $HOME \
&& git clone --single-branch -b ${NJOY_TAG} --depth 1 ${NJOY_REPO} \
&& git clone --single-branch --depth 1 ${NJOY_REPO} \
&& cd NJOY2016 \
&& mkdir build \
&& cd build \
@ -90,21 +90,28 @@ RUN cd $HOME \
RUN if [ "$build_dagmc" = "on" ]; then \
# Install addition packages required for DAGMC
apt-get -y install \
libeigen3-dev libnetcdf-dev libtbb-dev libglfw3-dev libembree-dev \
&& pip install --upgrade numpy \
&& pip install --no-cache-dir setuptools cython \
apt-get -y install libeigen3-dev libnetcdf-dev libtbb-dev libglfw3-dev \
&& pip install --upgrade numpy cython \
# Clone and install EMBREE
&& mkdir -p $HOME/EMBREE && cd $HOME/EMBREE \
&& git clone --single-branch -b ${EMBREE_TAG} --depth 1 ${EMBREE_REPO} \
&& mkdir build && cd build \
&& cmake ../embree \
-DCMAKE_INSTALL_PREFIX=${EMBREE_INSTALL_DIR} \
-DEMBREE_MAX_ISA=NONE \
-DEMBREE_ISA_SSE42=ON \
-DEMBREE_ISPC_SUPPORT=OFF \
&& make 2>/dev/null -j${compile_cores} install \
&& rm -rf ${EMBREE_INSTALL_DIR}/build ${EMBREE_INSTALL_DIR}/embree ; \
# Clone and install MOAB
&& mkdir -p $HOME/MOAB && cd $HOME/MOAB \
mkdir -p $HOME/MOAB && cd $HOME/MOAB \
&& git clone --single-branch -b ${MOAB_TAG} --depth 1 ${MOAB_REPO} \
&& mkdir build && cd build \
&& cmake ../moab -DCMAKE_BUILD_TYPE=Release \
-DENABLE_HDF5=ON \
&& cmake ../moab -DENABLE_HDF5=ON \
-DENABLE_NETCDF=ON \
-DBUILD_SHARED_LIBS=OFF \
-DENABLE_FORTRAN=OFF \
-DENABLE_BLASLAPACK=OFF \
-DENABLE_TESTING=OFF \
&& make 2>/dev/null -j${compile_cores} install \
&& cmake ../moab \
-DENABLE_PYMOAB=ON \
@ -120,7 +127,7 @@ RUN if [ "$build_dagmc" = "on" ]; then \
&& mkdir build && cd build \
&& cmake ../double-down -DCMAKE_INSTALL_PREFIX=${DD_INSTALL_DIR} \
-DMOAB_DIR=/usr/local \
-DEMBREE_DIR=/usr \
-DEMBREE_DIR=${EMBREE_INSTALL_DIR} \
&& make 2>/dev/null -j${compile_cores} install \
&& rm -rf ${DD_INSTALL_DIR}/build ${DD_INSTALL_DIR}/double-down ; \
# Clone and install DAGMC
@ -134,7 +141,6 @@ RUN if [ "$build_dagmc" = "on" ]; then \
-DDOUBLE_DOWN_DIR=${DD_INSTALL_DIR} \
-DCMAKE_PREFIX_PATH=${DD_INSTALL_DIR}/lib \
-DBUILD_STATIC_LIBS=OFF \
-DBUILD_TESTS=OFF \
&& make 2>/dev/null -j${compile_cores} install \
&& rm -rf ${DAGMC_INSTALL_DIR}/DAGMC ${DAGMC_INSTALL_DIR}/build ; \
fi
@ -183,7 +189,7 @@ ENV LIBMESH_INSTALL_DIR=$HOME/LIBMESH
# clone and install openmc
RUN mkdir -p ${HOME}/OpenMC && cd ${HOME}/OpenMC \
&& git clone --shallow-submodules --recurse-submodules --single-branch -b ${openmc_branch} ${OPENMC_REPO} \
&& git clone --shallow-submodules --recurse-submodules --single-branch -b ${openmc_branch} --depth=1 ${OPENMC_REPO} \
&& mkdir build && cd build ; \
if [ ${build_dagmc} = "on" ] && [ ${build_libmesh} = "on" ]; then \
cmake ../openmc \

View file

@ -1,4 +1,4 @@
Copyright (c) 2011-2026 Massachusetts Institute of Technology, UChicago Argonne
Copyright (c) 2011-2022 Massachusetts Institute of Technology, UChicago Argonne
LLC, and OpenMC contributors
Permission is hereby granted, free of charge, to any person obtaining a copy of

View file

@ -23,9 +23,10 @@ recursive-include examples *.cpp
recursive-include examples *.py
recursive-include examples *.xml
recursive-include include *.h
recursive-include include *.h.in
recursive-include include *.hh
recursive-include man *.1
recursive-include openmc *.pyx
recursive-include openmc *.c
recursive-include src *.cc
recursive-include src *.cpp
recursive-include src *.rnc
@ -43,5 +44,6 @@ recursive-include vendor *.hh
recursive-include vendor *.hpp
recursive-include vendor *.pc.in
recursive-include vendor *.natvis
include vendor/gsl-lite/include/gsl/gsl
prune docs/build
prune docs/source/pythonapi/generated/

View file

@ -1,7 +1,7 @@
# OpenMC Monte Carlo Particle Transport Code
[![License](https://img.shields.io/badge/license-MIT-green)](https://docs.openmc.org/en/latest/license.html)
[![GitHub Actions build status (Linux)](https://github.com/openmc-dev/openmc/actions/workflows/ci.yml/badge.svg?branch=develop)](https://github.com/openmc-dev/openmc/actions/workflows/ci.yml)
[![GitHub Actions build status (Linux)](https://github.com/openmc-dev/openmc/workflows/CI/badge.svg?branch=develop)](https://github.com/openmc-dev/openmc/actions?query=workflow%3ACI)
[![Code Coverage](https://coveralls.io/repos/github/openmc-dev/openmc/badge.svg?branch=develop)](https://coveralls.io/github/openmc-dev/openmc?branch=develop)
[![dockerhub-publish-develop-dagmc](https://github.com/openmc-dev/openmc/workflows/dockerhub-publish-develop-dagmc/badge.svg)](https://github.com/openmc-dev/openmc/actions?query=workflow%3Adockerhub-publish-develop-dagmc)
[![dockerhub-publish-develop](https://github.com/openmc-dev/openmc/workflows/dockerhub-publish-develop/badge.svg)](https://github.com/openmc-dev/openmc/actions?query=workflow%3Adockerhub-publish-develop)
@ -15,8 +15,7 @@ project started under the Computational Reactor Physics Group at MIT.
Complete documentation on the usage of OpenMC is hosted on Read the Docs (both
for the [latest release](https://docs.openmc.org/en/stable/) and
[developmental](https://docs.openmc.org/en/latest/) version). If you are
interested in the project, or would like to help and contribute, please get in
touch on the OpenMC [discussion forum](https://openmc.discourse.group/).
interested in the project, or would like to help and contribute, please get in touch on the OpenMC [discussion forum](https://openmc.discourse.group/).
## Installation
@ -37,21 +36,20 @@ citing the following publication:
## Troubleshooting
If you run into problems compiling, installing, or running OpenMC, first check
the [Troubleshooting
section](https://docs.openmc.org/en/stable/usersguide/troubleshoot.html) in the
User's Guide. If you are not able to find a solution to your problem there,
the [Troubleshooting section](https://docs.openmc.org/en/stable/usersguide/troubleshoot.html) in
the User's Guide. If you are not able to find a solution to your problem there,
please post to the [discussion forum](https://openmc.discourse.group/).
## Reporting Bugs
OpenMC is hosted on GitHub and all bugs are reported and tracked through the
[Issues](https://github.com/openmc-dev/openmc/issues) feature on GitHub.
However, GitHub Issues should not be used for common troubleshooting purposes.
If you are having trouble installing the code or getting your model to run
properly, you should first send a message to the [discussion
forum](https://openmc.discourse.group/). If it turns out your issue really is a
bug in the code, an issue will then be created on GitHub. If you want to request
that a feature be added to the code, you may create an Issue on github.
[Issues](https://github.com/openmc-dev/openmc/issues) feature on GitHub. However,
GitHub Issues should not be used for common troubleshooting purposes. If you are
having trouble installing the code or getting your model to run properly, you
should first send a message to the User's Group mailing list. If it turns out
your issue really is a bug in the code, an issue will then be created on
GitHub. If you want to request that a feature be added to the code, you may
create an Issue on github.
## License

View file

@ -14,8 +14,8 @@ if(DEFINED ENV{METHOD})
message(STATUS "Using environment variable METHOD to determine libMesh build: ${LIBMESH_PC_FILE}")
endif()
find_package(PkgConfig REQUIRED)
set(PKG_CONFIG_USE_CMAKE_PREFIX_PATH TRUE)
pkg_check_modules(LIBMESH REQUIRED ${LIBMESH_PC_FILE}>=1.7.0 IMPORTED_TARGET)
pkg_get_variable(LIBMESH_PREFIX ${LIBMESH_PC_FILE} prefix)
include(FindPkgConfig)
set(ENV{PKG_CONFIG_PATH} "$ENV{PKG_CONFIG_PATH}:${LIBMESH_PC}")
set(PKG_CONFIG_USE_CMAKE_PREFIX_PATH True)
pkg_check_modules(LIBMESH REQUIRED ${LIBMESH_PC_FILE}>=1.6.0 IMPORTED_TARGET)
pkg_get_variable(LIBMESH_PREFIX ${LIBMESH_PC_FILE} prefix)

View file

@ -1,120 +0,0 @@
# GetVersionFromGit.cmake
# Standalone script to retrieve versioning information from Git or .git_archival.txt.
# Customizable for any project by setting variables before including this file.
# Configurable variables:
# - VERSION_PREFIX: Prefix for version tags (default: "v").
# - VERSION_SUFFIX: Suffix for version tags (default: "[~+-]([a-zA-Z0-9]+)").
# - VERSION_REGEX: Regex to extract version (default: "(?[0-9]+\\.[0-9]+\\.[0-9]+)").
# - ARCHIVAL_FILE: Path to .git_archival.txt (default: "${CMAKE_SOURCE_DIR}/.git_archival.txt").
# - DESCRIBE_NAME_KEY: Key for describe name in .git_archival.txt (default: "describe-name: ").
# - COMMIT_HASH_KEY: Key for commit hash in .git_archival.txt (default: "commit: ").
# Default Format Example:
# 1.2.3 v1.2.3 v1.2.3-rc1
set(VERSION_PREFIX "v" CACHE STRING "Prefix used in version tags")
set(VERSION_SUFFIX "[~+-]([a-zA-Z0-9]+)" CACHE STRING "Suffix used in version tags")
set(VERSION_REGEX "?([0-9]+\\.[0-9]+\\.[0-9]+)" CACHE STRING "Regex for extracting version")
set(ARCHIVAL_FILE "${CMAKE_SOURCE_DIR}/.git_archival.txt" CACHE STRING "Path to .git_archival.txt")
set(DESCRIBE_NAME_KEY "describe-name: " CACHE STRING "Key for describe name in .git_archival.txt")
set(COMMIT_HASH_KEY "commit: " CACHE STRING "Key for commit hash in .git_archival.txt")
# Combine prefix and regex
set(VERSION_REGEX_WITH_PREFIX "^${VERSION_PREFIX}${VERSION_REGEX}")
# Find Git
find_package(Git)
# Attempt to retrieve version from Git
if(EXISTS "${CMAKE_SOURCE_DIR}/.git" AND GIT_FOUND)
message(STATUS "Using git describe for versioning")
# Extract the version string
execute_process(
COMMAND git describe --tags --dirty
WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}
OUTPUT_VARIABLE VERSION_STRING
OUTPUT_STRIP_TRAILING_WHITESPACE
ERROR_QUIET
)
# If no tags are found, set version to 0 and show a warning
if(VERSION_STRING STREQUAL "")
set(VERSION_STRING "0.0.0")
message(WARNING
"No git tags found. Version set to 0.0.0.\n"
"Run 'git fetch --tags' to ensure proper versioning.\n"
"For more information, see OpenMC developer documentation."
)
endif()
# Extract the commit hash
execute_process(
COMMAND git rev-parse HEAD
WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}
OUTPUT_VARIABLE COMMIT_HASH
OUTPUT_STRIP_TRAILING_WHITESPACE
)
else()
message(STATUS "Using archival file for versioning: ${ARCHIVAL_FILE}")
if(EXISTS "${ARCHIVAL_FILE}")
file(READ "${ARCHIVAL_FILE}" ARCHIVAL_CONTENT)
# Extract the describe-name line
string(REGEX MATCH "${DESCRIBE_NAME_KEY}([^\\n]+)" VERSION_STRING "${ARCHIVAL_CONTENT}")
if(VERSION_STRING MATCHES "${DESCRIBE_NAME_KEY}(.*)")
set(VERSION_STRING "${CMAKE_MATCH_1}")
else()
message(FATAL_ERROR "Could not extract version from ${ARCHIVAL_FILE}")
endif()
# Extract the commit hash
string(REGEX MATCH "${COMMIT_HASH_KEY}([a-f0-9]+)" COMMIT_HASH "${ARCHIVAL_CONTENT}")
if(COMMIT_HASH MATCHES "${COMMIT_HASH_KEY}([a-f0-9]+)")
set(COMMIT_HASH "${CMAKE_MATCH_1}")
else()
message(FATAL_ERROR "Could not extract commit hash from ${ARCHIVAL_FILE}")
endif()
else()
message(FATAL_ERROR "Neither git describe nor ${ARCHIVAL_FILE} is available for versioning.")
endif()
endif()
# Ensure version string format
if(VERSION_STRING MATCHES "${VERSION_REGEX_WITH_PREFIX}")
set(VERSION_NO_SUFFIX "${CMAKE_MATCH_1}")
else()
message(FATAL_ERROR "Invalid version format: Missing base version in ${VERSION_STRING}")
endif()
# Check for development state
if(VERSION_STRING MATCHES "-([0-9]+)-g([0-9a-f]+)")
set(DEV_STATE "true")
set(COMMIT_COUNT "${CMAKE_MATCH_1}")
string(REGEX REPLACE "-([0-9]+)-g([0-9a-f]+)" "" VERSION_WITHOUT_META "${VERSION_STRING}")
else()
set(DEV_STATE "false")
set(VERSION_WITHOUT_META "${VERSION_STRING}")
endif()
# Split and set version components
string(REPLACE "." ";" VERSION_LIST "${VERSION_NO_SUFFIX}")
list(GET VERSION_LIST 0 VERSION_MAJOR)
list(GET VERSION_LIST 1 VERSION_MINOR)
list(GET VERSION_LIST 2 VERSION_PATCH)
# Increment patch number for dev versions
if(DEV_STATE)
math(EXPR VERSION_PATCH "${VERSION_PATCH} + 1")
endif()
# Export variables
set(OPENMC_VERSION_MAJOR "${VERSION_MAJOR}")
set(OPENMC_VERSION_MINOR "${VERSION_MINOR}")
set(OPENMC_VERSION_PATCH "${VERSION_PATCH}")
set(OPENMC_VERSION "${VERSION_MAJOR}.${VERSION_MINOR}.${VERSION_PATCH}")
set(OPENMC_COMMIT_HASH "${COMMIT_HASH}")
set(OPENMC_DEV_STATE "${DEV_STATE}")
set(OPENMC_COMMIT_COUNT "${COMMIT_COUNT}")

View file

@ -1,45 +1,27 @@
@PACKAGE_INIT@
include("${CMAKE_CURRENT_LIST_DIR}/OpenMCConfigVersion.cmake")
include(CMakeFindDependencyMacro)
# Explicitly calculate prefix if it was not generated above
if(NOT DEFINED PACKAGE_PREFIX_DIR)
get_filename_component(PACKAGE_PREFIX_DIR "${CMAKE_CURRENT_LIST_DIR}/../../.." ABSOLUTE)
endif()
find_dependency(fmt CONFIG REQUIRED HINTS ${PACKAGE_PREFIX_DIR})
find_dependency(pugixml CONFIG REQUIRED HINTS ${PACKAGE_PREFIX_DIR})
get_filename_component(OpenMC_CMAKE_DIR "${CMAKE_CURRENT_LIST_FILE}" DIRECTORY)
find_package(fmt REQUIRED HINTS ${OpenMC_CMAKE_DIR}/../fmt)
find_package(gsl-lite REQUIRED HINTS ${OpenMC_CMAKE_DIR}/../gsl-lite)
find_package(pugixml REQUIRED HINTS ${OpenMC_CMAKE_DIR}/../pugixml)
find_package(xtl REQUIRED HINTS ${OpenMC_CMAKE_DIR}/../xtl)
find_package(xtensor REQUIRED HINTS ${OpenMC_CMAKE_DIR}/../xtensor)
if(@OPENMC_USE_DAGMC@)
find_dependency(DAGMC REQUIRED HINTS @DAGMC_DIR@)
find_package(DAGMC REQUIRED HINTS @DAGMC_DIR@)
endif()
if(@OPENMC_USE_LIBMESH@)
include(FindPkgConfig)
list(APPEND CMAKE_PREFIX_PATH @LIBMESH_PREFIX@)
set(PKG_CONFIG_USE_CMAKE_PREFIX_PATH True)
pkg_check_modules(LIBMESH REQUIRED @LIBMESH_PC_FILE@>=1.7.0 IMPORTED_TARGET)
pkg_check_modules(LIBMESH REQUIRED @LIBMESH_PC_FILE@>=1.6.0 IMPORTED_TARGET)
endif()
if("@PNG_FOUND@")
find_dependency(PNG)
find_package(PNG)
if(NOT TARGET OpenMC::libopenmc)
include("${OpenMC_CMAKE_DIR}/OpenMCTargets.cmake")
endif()
if(@OPENMC_USE_MPI@)
find_dependency(MPI REQUIRED)
endif()
if(@OPENMC_USE_OPENMP@)
find_dependency(OpenMP REQUIRED)
endif()
if(@OPENMC_USE_UWUW@ AND NOT ${DAGMC_BUILD_UWUW})
message(FATAL_ERROR "UWUW is enabled in OpenMC but the DAGMC installation discovered was not configured with UWUW.")
endif()
include("${CMAKE_CURRENT_LIST_DIR}/OpenMCTargets.cmake")
if(NOT OpenMC_FIND_QUIETLY)
message(STATUS "Found OpenMC: ${PACKAGE_VERSION} (found in ${PACKAGE_PREFIX_DIR})")
find_package(MPI REQUIRED)
endif()

View file

@ -0,0 +1,11 @@
set(PACKAGE_VERSION "@OPENMC_VERSION@")
# Check whether the requested PACKAGE_FIND_VERSION is compatible
if("${PACKAGE_VERSION}" VERSION_LESS "${PACKAGE_FIND_VERSION}")
set(PACKAGE_VERSION_COMPATIBLE FALSE)
else()
set(PACKAGE_VERSION_COMPATIBLE TRUE)
if ("${PACKAGE_VERSION}" VERSION_EQUAL "${PACKAGE_FIND_VERSION}")
set(PACKAGE_VERSION_EXACT TRUE)
endif()
endif()

View file

@ -45,7 +45,6 @@ help:
clean:
-rm -rf $(BUILDDIR)/*
-rm -rf source/pythonapi/generated/
-rm -rf doxygen/xml
html:
$(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html

View file

@ -1,13 +0,0 @@
# Doxyfile 1.9.1
# This file describes the settings to be used by the documentation system
# doxygen (www.doxygen.org) for a project.
# Difference with default Doxyfile 1.9.1
PROJECT_NAME = OpenMC
QUIET = YES
WARN_IF_UNDOCUMENTED = NO
INPUT = ../../include/openmc/capi.h
GENERATE_HTML = NO
GENERATE_LATEX = NO
GENERATE_XML = YES

12
docs/requirements-rtd.txt Normal file
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@ -0,0 +1,12 @@
sphinx==5.0.2
sphinx_rtd_theme==1.0.0
sphinx-numfig
jupyter
sphinxcontrib-katex
sphinxcontrib-svg2pdfconverter
numpy
scipy
h5py
pandas
uncertainties
matplotlib

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@ -46,29 +46,41 @@ Type Definitions
Functions
---------
..
Once documentation is complete in capi.h, use:
.. doxygenfile:: capi.h
to populate this documentation without using
.. doxygenfunction::
for every function.
.. c:function:: int openmc_calculate_volumes()
.. doxygenfunction:: openmc_calculate_volumes
Run a stochastic volume calculation
.. doxygenfunction:: openmc_cell_get_fill
:return: Return status (negative if an error occurred)
:rtype: int
.. doxygenfunction:: openmc_cell_get_id
.. c:function:: int openmc_cell_get_fill(int32_t index, int* type, int32_t** indices, int32_t* n)
.. doxygenfunction:: openmc_cell_get_temperature
.. c:function:: int openmc_cell_get_density(int32_t index, const int32_t* instance, double* density)
Get the density of a cell
Get the fill for a cell
:param int32_t index: Index in the cells array
:param int32_t* instance: Which instance of the cell. If a null pointer is passed, the density
multiplier of the first instance is returned.
:param double* density: Density of the cell in [g/cm3]
:param int* type: Type of the fill
:param int32_t** indices: Array of material indices for cell
:param int32_t* n: Length of indices array
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_cell_get_id(int32_t index, int32_t* id)
Get the ID of a cell
:param int32_t index: Index in the cells array
:param int32_t* id: ID of the cell
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_cell_get_temperature(int32_t index, const int32_t* instance, double* T)
Get the temperature of a cell
:param int32_t index: Index in the cells array
:param int32_t* instance: Which instance of the cell. If a null pointer is passed, the temperature
of the first instance is returned.
:param double* T: temperature of the cell
:return: Return status (negative if an error occurred)
:rtype: int
@ -101,22 +113,8 @@ Functions
:param double T: Temperature in Kelvin
:param instance: Which instance of the cell. To set the temperature for all
instances, pass a null pointer.
:param bool set_contained: If the cell is not filled by a material, whether
to set the temperatures of all filled cells
:type instance: const int32_t*
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_cell_set_density(index index, double density, const int32_t* instance, bool set_contained)
Set the density of a cell.
:param int32_t index: Index in the cells array
:param double density: Density of the cell in [g/cm3]
:param instance: Which instance of the cell. To set the density multiplier for all
instances, pass a null pointer.
:param bool set_contained: If the cell is not filled by a material, whether
to set the density multiplier of all filled cells
:param set_contained: If the cell is not filled by a material, whether to set the temperatures
of all filled cells
:type instance: const int32_t*
:return: Return status (negative if an error occurred)
:rtype: int
@ -422,16 +420,6 @@ Functions
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_mesh_filter_get_mesh(int32_t index, int32_t* index_mesh)
Get the mesh for a mesh filter
:param int32_t index: Index in the filters array
:param index_mesh: Index in the meshes array
:type index_mesh: int32_t*
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_mesh_filter_set_mesh(int32_t index, int32_t index_mesh)
Set the mesh for a mesh filter
@ -441,98 +429,6 @@ Functions
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_mesh_filter_get_translation(int32_t index, double translation[3])
Get the 3-D translation coordinates for a mesh filter
:param int32_t index: Index in the filters array
:param double[3] translation: 3-D translation coordinates
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_mesh_filter_set_translation(int32_t index, double translation[3])
Set the 3-D translation coordinates for a mesh filter
:param int32_t index: Index in the filters array
:param double[3] translation: 3-D translation coordinates
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_meshborn_filter_get_mesh(int32_t index, int32_t* index_mesh)
Get the mesh for a meshborn filter
:param int32_t index: Index in the filters array
:param index_mesh: Index in the meshes array
:type index_mesh: int32_t*
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_meshborn_filter_set_mesh(int32_t index, int32_t index_mesh)
Set the mesh for a meshborn filter
:param int32_t index: Index in the filters array
:param int32_t index_mesh: Index in the meshes array
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_meshborn_filter_get_translation(int32_t index, double translation[3])
Get the 3-D translation coordinates for a meshborn filter
:param int32_t index: Index in the filters array
:param double[3] translation: 3-D translation coordinates
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_meshborn_filter_set_translation(int32_t index, double translation[3])
Set the 3-D translation coordinates for a meshborn filter
:param int32_t index: Index in the filters array
:param double[3] translation: 3-D translation coordinates
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_meshsurface_filter_get_mesh(int32_t index, int32_t* index_mesh)
Get the mesh for a mesh surface filter
:param int32_t index: Index in the filters array
:param index_mesh: Index in the meshes array
:type index_mesh: int32_t*
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_meshsurface_filter_set_mesh(int32_t index, int32_t index_mesh)
Set the mesh for a mesh surface filter
:param int32_t index: Index in the filters array
:param int32_t index_mesh: Index in the meshes array
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_meshsurface_filter_get_translation(int32_t index, double translation[3])
Get the 3-D translation coordinates for a mesh surface filter
:param int32_t index: Index in the filters array
:param double[3] translation: 3-D translation coordinates
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_meshsurface_filter_set_translation(int32_t index, double translation[3])
Set the 3-D translation coordinates for a mesh surface filter
:param int32_t index: Index in the filters array
:param double[3] translation: 3-D translation coordinates
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_next_batch()
Simulate next batch of particles. Must be called after openmc_simulation_init().
@ -557,279 +453,6 @@ Functions
:return: Return status (negative if an error occurs)
:rtype: int
.. c:function:: int openmc_get_plot_index(int32_t id, int32_t* index)
Get the index in the plots array for a plot with a given ID.
:param int32_t id: Plot ID
:param int32_t* index: Index in the plots array
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_plot_get_id(int32_t index, int32_t* id)
Get the ID of a plot.
:param int32_t index: Index in the plots array
:param int32_t* id: Plot ID
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_plot_set_id(int32_t index, int32_t id)
Set the ID of a plot.
:param int32_t index: Index in the plots array
:param int32_t id: Plot ID
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: size_t openmc_plots_size()
Number of plots currently allocated.
:return: Number of plots in the plots array
:rtype: size_t
.. c:function:: int openmc_solidraytrace_plot_create(int32_t* index)
Create a new solid raytrace plot.
:param int32_t* index: Index of the newly created plot
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_pixels(int32_t index, int32_t* width, int32_t* height)
Get output pixel dimensions for a solid raytrace plot.
:param int32_t index: Index in the plots array
:param int32_t* width: Image width in pixels
:param int32_t* height: Image height in pixels
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_pixels(int32_t index, int32_t width, int32_t height)
Set output pixel dimensions for a solid raytrace plot.
:param int32_t index: Index in the plots array
:param int32_t width: Image width in pixels
:param int32_t height: Image height in pixels
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_color_by(int32_t index, int32_t* color_by)
Get the domain type used for coloring (0=materials, 1=cells).
:param int32_t index: Index in the plots array
:param int32_t* color_by: Coloring mode
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_color_by(int32_t index, int32_t color_by)
Set the domain type used for coloring (0=materials, 1=cells).
:param int32_t index: Index in the plots array
:param int32_t color_by: Coloring mode
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_default_colors(int32_t index)
Set default random colors for the current ``color_by`` mode.
:param int32_t index: Index in the plots array
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_all_opaque(int32_t index)
Mark all domains in the current ``color_by`` mode as opaque.
:param int32_t index: Index in the plots array
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_opaque(int32_t index, int32_t id, bool visible)
Set whether a specific domain ID is opaque (visible) in the rendered image.
:param int32_t index: Index in the plots array
:param int32_t id: Cell/material ID (based on ``color_by``)
:param bool visible: Whether the domain is opaque
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_color(int32_t index, int32_t id, uint8_t r, uint8_t g, uint8_t b)
Set RGB color for a specific domain ID.
:param int32_t index: Index in the plots array
:param int32_t id: Cell/material ID (based on ``color_by``)
:param uint8_t r: Red channel
:param uint8_t g: Green channel
:param uint8_t b: Blue channel
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_color(int32_t index, int32_t id, uint8_t* r, uint8_t* g, uint8_t* b)
Get RGB color for a specific domain ID.
:param int32_t index: Index in the plots array
:param int32_t id: Cell/material ID (based on ``color_by``)
:param uint8_t* r: Red channel
:param uint8_t* g: Green channel
:param uint8_t* b: Blue channel
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_camera_position(int32_t index, double* x, double* y, double* z)
Get camera position.
:param int32_t index: Index in the plots array
:param double* x: X coordinate
:param double* y: Y coordinate
:param double* z: Z coordinate
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_camera_position(int32_t index, double x, double y, double z)
Set camera position.
:param int32_t index: Index in the plots array
:param double x: X coordinate
:param double y: Y coordinate
:param double z: Z coordinate
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_look_at(int32_t index, double* x, double* y, double* z)
Get camera target point.
:param int32_t index: Index in the plots array
:param double* x: X coordinate
:param double* y: Y coordinate
:param double* z: Z coordinate
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_look_at(int32_t index, double x, double y, double z)
Set camera target point.
:param int32_t index: Index in the plots array
:param double x: X coordinate
:param double y: Y coordinate
:param double z: Z coordinate
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_up(int32_t index, double* x, double* y, double* z)
Get the camera up vector.
:param int32_t index: Index in the plots array
:param double* x: X component
:param double* y: Y component
:param double* z: Z component
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_up(int32_t index, double x, double y, double z)
Set the camera up vector.
:param int32_t index: Index in the plots array
:param double x: X component
:param double y: Y component
:param double z: Z component
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_light_position(int32_t index, double* x, double* y, double* z)
Get light source position.
:param int32_t index: Index in the plots array
:param double* x: X coordinate
:param double* y: Y coordinate
:param double* z: Z coordinate
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_light_position(int32_t index, double x, double y, double z)
Set light source position.
:param int32_t index: Index in the plots array
:param double x: X coordinate
:param double y: Y coordinate
:param double z: Z coordinate
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_fov(int32_t index, double* fov)
Get horizontal field of view in degrees.
:param int32_t index: Index in the plots array
:param double* fov: Field of view in degrees
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_fov(int32_t index, double fov)
Set horizontal field of view in degrees.
:param int32_t index: Index in the plots array
:param double fov: Field of view in degrees
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_get_diffuse_fraction(int32_t index, double* diffuse_fraction)
Get diffuse-light fraction.
:param int32_t index: Index in the plots array
:param double* diffuse_fraction: Diffuse fraction in [0, 1]
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_set_diffuse_fraction(int32_t index, double diffuse_fraction)
Set diffuse-light fraction.
:param int32_t index: Index in the plots array
:param double diffuse_fraction: Diffuse fraction in [0, 1]
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_update_view(int32_t index)
Recompute internal camera/view transforms after camera changes.
:param int32_t index: Index in the plots array
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_solidraytrace_plot_create_image(int32_t index, uint8_t* data_out, int32_t width, int32_t height)
Render the plot to an RGB image buffer.
:param int32_t index: Index in the plots array
:param uint8_t* data_out: Output buffer of shape ``height*width*3``
:param int32_t width: Image width in pixels
:param int32_t height: Image height in pixels
:return: Return status (negative if an error occurred)
:rtype: int
.. c:function:: int openmc_reset()
Resets all tally scores
@ -851,10 +474,6 @@ Functions
:return: Return status (negative if an error occurs)
:rtype: int
.. c:function:: void openmc_run_random_ray()
Run a random ray simulation
.. c:function:: int openmc_set_n_batches(int32_t n_batches, bool set_max_batches, bool add_statepoint_batch)
Set number of batches and number of max batches

View file

@ -11,10 +11,7 @@
# All configuration values have a default; values that are commented out
# serve to show the default.
import os
from pathlib import Path
import subprocess
import sys
import sys, os
# Determine if we're on Read the Docs server
on_rtd = os.environ.get('READTHEDOCS', None) == 'True'
@ -40,7 +37,6 @@ sys.path.insert(0, os.path.abspath('../..'))
# Add any Sphinx extension module names here, as strings. They can be extensions
# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
extensions = [
'breathe',
'sphinx.ext.autodoc',
'sphinx.ext.napoleon',
'sphinx.ext.autosummary',
@ -51,14 +47,12 @@ extensions = [
]
if not on_rtd:
extensions.append('sphinxcontrib.rsvgconverter')
doxygen_dir = Path(__file__).parents[1] / 'doxygen'
subprocess.run(['doxygen'], cwd=doxygen_dir, check=True)
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
# The suffix of source filenames.
source_suffix = {'.rst': 'restructuredtext'}
source_suffix = '.rst'
# The encoding of source files.
#source_encoding = 'utf-8'
@ -68,17 +62,16 @@ master_doc = 'index'
# General information about the project.
project = 'OpenMC'
copyright = '2011-2026, Massachusetts Institute of Technology, UChicago Argonne LLC, and OpenMC contributors'
copyright = '2011-2022, Massachusetts Institute of Technology, UChicago Argonne LLC, and OpenMC contributors'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
import openmc
# The short X.Y version.
version = "0.13"
# The full version, including alpha/beta/rc tags.
version = release = openmc.__version__
release = "0.13.1"
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
@ -123,17 +116,14 @@ pygments_style = 'tango'
# A list of ignored prefixes for module index sorting.
#modindex_common_prefix = []
# -- Options breathe + doxygen -------------------------------------------------
breathe_projects = {"OpenMC": "../doxygen/xml"}
breathe_default_project = "OpenMC"
breathe_domain_by_file_pattern = {"*capi.h": "c"}
# -- Options for HTML output ---------------------------------------------------
# The theme to use for HTML and HTML Help pages
html_theme = 'sphinx_rtd_theme'
html_baseurl = "https://docs.openmc.org/en/stable/"
if not on_rtd:
import sphinx_rtd_theme
html_theme = 'sphinx_rtd_theme'
html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
html_logo = '_images/openmc_logo.png'
@ -257,7 +247,7 @@ napoleon_use_ivar = True
intersphinx_mapping = {
'python': ('https://docs.python.org/3', None),
'numpy': ('https://numpy.org/doc/stable/', None),
'scipy': ('https://docs.scipy.org/doc/scipy/', None),
'scipy': ('https://docs.scipy.org/doc/scipy/reference', None),
'pandas': ('https://pandas.pydata.org/pandas-docs/stable/', None),
'matplotlib': ('https://matplotlib.org/stable/', None)
'matplotlib': ('https://matplotlib.org/', None)
}

View file

@ -1,104 +0,0 @@
.. _devguide_agentic_tools:
===========================
Agentic Development Tools
===========================
OpenMC ships a set of tools designed for AI coding agents (such as
`Claude Code`_) that agents can use to navigate and understand the codebase.
.. _Claude Code: https://claude.ai/code
Motivation
----------
Agentic tools like Claude Code are skilled at using grep to navigate and
understand large code bases. However, grep can only find exact text matches —
it cannot discover code that is *conceptually* related but uses different
naming. Without a "global view" of the codebase that a human developer will
build up over time, the agent is generally blind to any file it hasn't
tokenized fully. While it can grep to see who else calls a function, it
remains blind if other areas might be related but not share identical naming
conventions.
This problem is mitigated somewhat by using a model with a longer context
window. OpenMC has somewhere around ~1 million tokens of C++ and ~1 million
tokens of python. While Claude Code in early 2026 only has a context window
of 200k tokens, beta versions have extended context windows of 1M tokens,
and it's not unreasonable to assume that models may be available in the near
future that greatly exceed these limits.
However, even assuming the entire repository can be fit within a context
window, there are several downsides to doing this.
`Model performance degrades significantly as context size increases`_.
Benchmark results are
greatly improved if the model has less garbage to pick through. Additionally, API usage
is typically billed as tokens in/out per turn. As the context file
grows these costs become much larger. As such, there is still significant
motivation to solving the above problem, so as to ensure only relevant
information is drawn into context so as to maximize model performance and
minimize costs.
Setup
-----
The tools are registered as an `MCP (Model Context Protocol)`_ server in
``.mcp.json`` at the repository root. AI agents that support MCP (such as
Claude Code) discover them automatically on session start. The underlying
Python scripts can also be run directly from the command line.
All tools run entirely locally — no API keys or external service accounts are
required. Python dependencies are installed automatically into an isolated
virtual environment at ``.claude/cache/.venv/`` on first use.
.. _Model performance degrades significantly as context size increases: https://www.anthropic.com/news/claude-opus-4-6
.. _MCP (Model Context Protocol): https://modelcontextprotocol.io
RAG Semantic Search
-------------------
The RAG (Retrieval-Augmented Generation) semantic search addresses this
problem — it finds code by meaning, not just text match, surfacing related code
across subsystems that ``grep`` would miss entirely. Two MCP tools are provided:
- **openmc_rag_search** — Given a natural-language query, returns the most
relevant code chunks with file paths, line numbers, and a preview. Can search
code, documentation, or both. Can also find code related to a given file.
- **openmc_rag_rebuild** — Rebuilds the search index. Should be called after
pulling new code or switching branches.
How it works
^^^^^^^^^^^^
The search pipeline runs entirely on your local CPU:
1. **Chunking.** All C++, Python, and RST files are split into overlapping
fixed-size windows (~1000 characters, 25% overlap). This ensures every line
of code appears in at least one chunk and most lines appear in two.
2. **Embedding.** Each chunk is embedded into a 384-dimensional vector using
the `all-MiniLM-L6-v2`_ sentence-transformer model (22 million parameters).
This model runs on CPU with no GPU required. No API key is needed — the
model weights are downloaded once from Hugging Face and cached locally.
3. **Indexing.** The vectors are stored in a local LanceDB_ database on disk.
Building the full index takes approximately 5 minutes on a machine with
10 CPU cores. The index is stored in ``.claude/cache/rag_index/`` and
persists across sessions.
4. **Searching.** Your query is embedded using the same model, and the closest
chunks are retrieved by vector similarity. Results include the file path,
line range, file type, similarity distance, and a text preview.
.. _all-MiniLM-L6-v2: https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2
.. _LanceDB: https://lancedb.com
Requirements
^^^^^^^^^^^^
No system dependencies beyond **Python 3.12+** with ``pip``. An internet
connection is required on first use to download the Python packages and
embedding model weights; subsequent runs are fully offline. The Python packages
(``sentence-transformers``, ``lancedb``) and their dependencies (including
PyTorch, ~2GB) are installed automatically into an isolated virtual environment
on first use.

View file

@ -109,10 +109,9 @@ Leadership Team
The TC consists of the following individuals:
- `Paul Romano <https://github.com/paulromano>`_
- `Patrick Shriwise <https://github.com/pshriwise>`_
- `Sterling Harper <https://github.com/smharper>`_
- `Adam Nelson <https://github.com/nelsonag>`_
- `Jonathan Shimwell <https://github.com/shimwell>`_
- `John Tramm <https://github.com/jtramm>`_
- `Benoit Forget <https://github.com/bforget>`_
The Project Lead is Paul Romano.

View file

@ -5,19 +5,21 @@ Building Sphinx Documentation
=============================
In order to build the documentation in the ``docs`` directory, you will need to
have the several third-party Python packages installed, including `Sphinx
<https://www.sphinx-doc.org/en/master/>`_. To install the necessary
prerequisites, provide the optional "docs" dependencies when installing OpenMC's
Python API. That is, from the root directory of the OpenMC repository:
have the `Sphinx <https://www.sphinx-doc.org/en/master/>`_ third-party Python
package. The easiest way to install Sphinx is via pip:
.. code-block:: sh
python -m pip install ".[docs]"
pip install sphinx
The OpenMC documentation also uses Doxygen to automatically generate its
C/C++ API documentation directly from the docstrings available in the source
code. You will need to have a working installation of Doxygen to generate the
documentation locally.
Additionally, you will need several Sphinx extensions that can be installed
directly with pip:
.. code-block:: sh
pip install sphinx-numfig
pip install sphinxcontrib-katex
pip install sphinxcontrib-svg2pdfconverter
-----------------------------------
Building Documentation as a Webpage

View file

@ -45,11 +45,12 @@ Now you can run the following to create a `Docker container`_ called
This command will open an interactive shell running from within the
Docker container where you have access to use OpenMC.
.. note:: The ``docker run`` command supports many options_
.. note:: The ``docker run`` command supports many
`options <https://docs.docker.com/engine/reference/commandline/run/>`_
for spawning containers -- including `mounting volumes`_ from the
host filesystem -- which many users will find useful.
.. _Docker image: https://docs.docker.com/get-started/docker-concepts/the-basics/what-is-an-image/
.. _Docker image: https://docs.docker.com/engine/reference/commandline/images/
.. _Docker container: https://www.docker.com/resources/what-container
.. _options: https://docs.docker.com/reference/cli/docker/container/run/
.. _mounting volumes: https://docs.docker.com/engine/storage/volumes/
.. _options: https://docs.docker.com/engine/reference/commandline/run/
.. _mounting volumes: https://docs.docker.com/storage/volumes/

View file

@ -14,9 +14,7 @@ other related topics.
contributing
workflow
agentic-tools
styleguide
policies
tests
user-input
docbuild

View file

@ -1,35 +0,0 @@
.. _devguide_policies:
========
Policies
========
---------------------
Python Version Policy
---------------------
OpenMC follows the Scientific Python Ecosystem Coordination guidelines `SPEC 0
<https://scientific-python.org/specs/spec-0000/>`_ on minimum supported
versions, which recommends that support for Python versions be dropped 3 years
after their initial release.
-------------------
C++ Standard Policy
-------------------
C++ code in OpenMC must conform to the most recent C++ standard that is fully
supported in the `version of the gcc compiler
<https://gcc.gnu.org/projects/cxx-status.html>`_ that is distributed with the
oldest version of Ubuntu that is still within its `standard support period
<https://ubuntu.com/about/release-cycle>`_. Ubuntu 22.04 LTS will be supported
through April 2027 and is distributed with gcc 11.4.0, which fully supports the
C++17 standard.
--------------------
CMake Version Policy
--------------------
Similar to the C++ standard policy, the minimum supported version of CMake
corresponds to whatever version is distributed with the oldest version of Ubuntu
still within its standard support period. Ubuntu 22.04 LTS is distributed with
CMake 3.22.

View file

@ -29,10 +29,6 @@ whenever a file is saved. For example, `Visual Studio Code
<https://code.visualstudio.com/docs/cpp/cpp-ide#_code-formatting>`_ includes
support for running clang-format.
.. note::
OpenMC's CI uses `clang-format` version 18. A different version of `clang-format`
may produce different line changes and as a result fail the CI test.
Miscellaneous
-------------
@ -40,15 +36,14 @@ Follow the `C++ Core Guidelines`_ except when they conflict with another
guideline listed here. For convenience, many important guidelines from that
list are repeated here.
Conform to the C++17 standard.
Conform to the C++14 standard.
Always use C++-style comments (``//``) as opposed to C-style (``/**/``). (It
is more difficult to comment out a large section of code that uses C-style
comments.)
Do not use C-style casting. Always use the C++-style casts ``static_cast``,
``const_cast``, or ``reinterpret_cast``. (See `ES.49
<https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines#es49-if-you-must-use-a-cast-use-a-named-cast>`_)
``const_cast``, or ``reinterpret_cast``. (See `ES.49 <http://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines#es49-if-you-must-use-a-cast-use-a-named-cast>`_)
Source Files
------------
@ -56,7 +51,7 @@ Source Files
Use a ``.cpp`` suffix for code files and ``.h`` for header files.
Header files should always use include guards with the following style (See
`SF.8 <https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines#Rs-guards>`_):
`SF.8 <http://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines#sf8-use-include-guards-for-all-h-files>`_):
.. code-block:: C++
@ -147,7 +142,7 @@ Style for Python code should follow PEP8_.
Docstrings for functions and methods should follow numpydoc_ style.
Python code should work with Python 3.8+.
Python code should work with Python 3.6+.
Use of third-party Python packages should be limited to numpy_, scipy_,
matplotlib_, pandas_, and h5py_. Use of other third-party packages must be
@ -157,11 +152,11 @@ Prefer pathlib_ when working with filesystem paths over functions in the os_
module or other standard-library modules. Functions that accept arguments that
represent a filesystem path should work with both strings and Path_ objects.
.. _C++ Core Guidelines: https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines
.. _PEP8: https://peps.python.org/pep-0008/
.. _C++ Core Guidelines: http://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines
.. _PEP8: https://www.python.org/dev/peps/pep-0008/
.. _numpydoc: https://numpydoc.readthedocs.io/en/latest/format.html
.. _numpy: https://numpy.org/
.. _scipy: https://scipy.org/
.. _scipy: https://www.scipy.org/
.. _matplotlib: https://matplotlib.org/
.. _pandas: https://pandas.pydata.org/
.. _h5py: https://www.h5py.org/

View file

@ -23,28 +23,25 @@ Prerequisites
OpenMC in development/editable mode. With setuptools, this is accomplished by
running::
python -m pip install -e .[test]
python setup.py develop
or using pip (recommended)::
pip install -e .[test]
- The test suite requires a specific set of cross section data in order for
tests to pass. A download URL for the data that OpenMC expects can be found
within ``tools/ci/download-xs.sh``. Once the tarball is downloaded and
unpacked, set the :envvar:`OPENMC_CROSS_SECTIONS` environment variable to the
path of the ``cross_sections.xml`` file within the unpacked data.
within ``tools/ci/download-xs.sh``.
- In addition to the HDF5 data, some tests rely on ENDF files. A download URL
for those can also be found in ``tools/ci/download-xs.sh``. Once the tarball
is downloaded and unpacked, set the :envvar:`OPENMC_ENDF_DATA` environment
variable to the top-level directory of the unpacked tarball.
for those can also be found in ``tools/ci/download-xs.sh``.
- Some tests require `NJOY <https://www.njoy21.io/NJOY2016>`_ to preprocess
cross section data. The test suite assumes that you have an ``njoy``
executable available on your :envvar:`PATH`.
- OpenMC should be compiled with ``-DOPENMC_ENABLE_STRICT_FP=on`` to ensure
reproducible floating-point results across platforms and optimization levels.
Without this flag, regression tests may not match reference values.
Running Tests
-------------
To execute the Python test suite, go to the ``tests/`` directory and run::
To execute the test suite, go to the ``tests/`` directory and run::
pytest
@ -54,65 +51,6 @@ installed and run::
pytest --cov=../openmc --cov-report=html
To execute the C++ test suite, go to your build directory and run::
ctest
If you want to view testing output on failure run::
ctest --output-on-failure
Possible Reasons for Test Failures
----------------------------------
You may find that when you run the test suite, not everything passes. First,
make sure you have satisfied all the prerequisites above. After you have done
that, consider the following:
- When building OpenMC, make sure you run CMake with
``-DOPENMC_ENABLE_STRICT_FP=on``. This prevents the compiler from applying
floating-point optimizations (such as replacing math library calls with
builtins or contracting multiply-add into FMA instructions) that can produce
bit-level differences across platforms and optimization levels. Any
``CMAKE_BUILD_TYPE`` can be used.
- Because tallies involve the sum of many floating point numbers, the
non-associativity of floating point numbers can result in different answers
especially when the number of threads is high (different order of operations).
Thus, if you are running on a CPU with many cores, you may need to limit the
number of OpenMP threads used. It is recommended to set the
:envvar:`OMP_NUM_THREADS` environment variable to 2.
- Recent versions of NumPy use instruction dispatch that may generate different
results depending the particular ISA that you are running on. To avoid issues,
you may need to disable AVX512 instructions. This can be done by setting the
:envvar:`NPY_DISABLE_CPU_FEATURES` environment variable to "AVX512F
AVX512_SKX". When NumPy/SciPy are built against OpenBLAS, you may also need to
limit the number of threads that OpenBLAS uses internally; this can be done by
setting the :envvar:`OPENBLAS_NUM_THREADS` environment variable to 1.
Debugging Tests in CI
---------------------
Tests can be debugged in CI using a feature called
`tmate <https://github.com/mxschmitt/action-tmate?tab=readme-ov-file#debug-your-github-actions-by-using-tmate>`_.
CI debugging can be
enabled by including "[gha-debug]" in the commit message. When the test fails, a
link similar to the one shown below will be provided in the GitHub Actions
output after failure occurs. Logging into the provided link will allow you to
debug the test in the CI environment. The following is an example of the output
shown in the CI log that provides the link to the tmate session:
.. code-block:: text
:linenos:
Created new session successfully
ssh 2VcykjU7vNdvAzEjQcc839GM2@nyc1.tmate.io
https://tmate.io/t/2VcykjU7vNdvAzEjQcc839GM2
Entering main loop
Web shell: https://tmate.io/t/2VcykjU7vNdvAzEjQcc839GM2
SSH: ssh 2VcykjU7vNdvAzEjQcc839GM2@nyc1.tmate.io
...
Generating XML Inputs
---------------------
@ -124,23 +62,6 @@ run::
pytest --build-inputs <name-of-test>
Adding C++ Unit Tests
---------------------
The C++ test suite uses Catch2 integrated with CTest. Each header file should
have a corresponding test file in ``tests/cpp_unit_tests/``. If the test file
does not exist run::
touch test_<name-of-header-file>.cpp
The file must be added to the CMake build system in
``tests/cpp_unit_tests/CMakeLists.txt``. ``test_<name-of-header-file>`` should
be added to ``TEST_NAMES``.
To add a test case to ``test_<name-of-header-file>.cpp`` ensure
``catch2/catch_test_macros.hpp`` is included. A unit test can then be added
using the ``TEST_CASE`` macro and the ``REQUIRE`` assertion from Catch2.
Adding Tests to the Regression Suite
------------------------------------
@ -163,12 +84,6 @@ following files to your new test directory:
compiler options during openmc configuration and build (e.g., no MPI, no
debug/optimization).
For tests using the Python API, both the **inputs_true.dat** and
**results_true.dat** files can be generated automatically in the correct format
via::
pytest --update <name-of-test>
In addition to this description, please see the various types of tests that are
already included in the test suite to see how to create them. If all is
implemented correctly, the new test will automatically be discovered by pytest.

View file

@ -49,12 +49,23 @@ following steps should be followed to make changes to user input:
written out to the statepoint or summary files and that the
:class:`openmc.StatePoint` and :class:`openmc.Summary` classes read them in.
7. Finally, a set of `RELAX NG`_ schemas exists that enables validation of input
files. You should modify the RELAX NG schema for the file you changed. The
easiest way to do this is to change the `compact syntax`_ file
(e.g. ``src/relaxng/geometry.rnc``) and then convert it to regular XML syntax
using trang_::
trang geometry.rnc geometry.rng
For most user input additions and changes, it is simple enough to follow a
"monkey see, monkey do" approach. When in doubt, contact your nearest OpenMC
developer or send a message to the `developers mailing list`_.
.. _property attribute: https://docs.python.org/3.6/library/functions.html#property
.. _XML Schema Part 2: https://www.w3.org/TR/xmlschema-2/
.. _boolean: https://www.w3.org/TR/xmlschema-2/#boolean
.. _XML Schema Part 2: http://www.w3.org/TR/xmlschema-2/
.. _boolean: http://www.w3.org/TR/xmlschema-2/#boolean
.. _RELAX NG: https://relaxng.org/
.. _compact syntax: https://relaxng.org/compact-tutorial-20030326.html
.. _trang: https://relaxng.org/jclark/trang.html
.. _developers mailing list: https://groups.google.com/forum/?fromgroups=#!forum/openmc-dev

View file

@ -91,30 +91,6 @@ features and bug fixes. The general steps for contributing are as follows:
6. After the pull request has been thoroughly vetted, it is merged back into the
*develop* branch of openmc-dev/openmc.
Setting Up Upstream Tracking (Required for Versioning)
------------------------------------------------------
By default, your fork **does not** include tags from the upstream OpenMC repository.
OpenMC relies on `git describe --tags` for versioning in source builds, and missing tags can lead
to incorrect version detection (i.e., ``0.0.0``). To ensure proper versioning, follow these steps:
1. **Add the Upstream Repository**
This allows you to fetch updates from the main OpenMC repository.
.. code-block:: sh
git remote add upstream https://github.com/openmc-dev/openmc.git
2. **Fetch and Push Tags**
Retrieve tags from the upstream repository and update your fork:
.. code-block:: sh
git fetch --tags upstream
git push --tags origin
This ensures that both your **local** and **remote** fork have the correct versioning information.
Private Development
-------------------
@ -140,7 +116,7 @@ pip_. From the root directory of the OpenMC repository, run:
.. code-block:: sh
python -m pip install -e .[test]
pip install -e .[test]
This installs the OpenMC Python package in `"editable" mode
<https://pip.pypa.io/en/stable/cli/pip_install/#editable-installs>`_ so that 1)
@ -150,10 +126,10 @@ reinstalling it). While the same effect can be achieved using the
:envvar:`PYTHONPATH` environment variable, this is generally discouraged as it
can interfere with virtual environments.
.. _git: https://git-scm.com/
.. _git: http://git-scm.com/
.. _GitHub: https://github.com/
.. _git flow: https://nvie.com/git-model
.. _valgrind: https://valgrind.org/
.. _valgrind: https://www.valgrind.org/
.. _style guide: https://docs.openmc.org/en/latest/devguide/styleguide.html
.. _pull request: https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests/about-pull-requests
.. _openmc-dev/openmc: https://github.com/openmc-dev/openmc

View file

@ -12,7 +12,7 @@ files produced by NJOY. Parallelism is enabled via a hybrid MPI and OpenMP
programming model.
OpenMC was originally developed by members of the `Computational Reactor Physics
Group <https://crpg.mit.edu>`_ at the `Massachusetts Institute of Technology
Group <http://crpg.mit.edu>`_ at the `Massachusetts Institute of Technology
<https://web.mit.edu>`_ starting in 2011. Various universities, laboratories,
and other organizations now contribute to the development of OpenMC. For more
information on OpenMC, feel free to post a message on the `OpenMC Discourse

View file

@ -1,46 +0,0 @@
.. _io_collision_track:
===========================
Collision Track File Format
===========================
When collision tracking is enabled with ``mcpl=false`` (the default), OpenMC
writes binary data to an HDF5 file named ``collision_track.h5``. The same data
may also be written after each batch when multiple files are requested
(``collision_track.N.h5``) or when the run is performed in parallel. The file
contains the information needed to reconstruct each recorded collision.
The current revision of the collision track file format is 1.2.
**/**
:Attributes:
- **filetype** (*char[]*) -- String indicating the type of file.
For collision-track files the value is ``"collision_track"``.
:Datasets:
- **collision_track_bank** (Compound type) -- Collision information
for each stored event. Each entry in the dataset corresponds to one
collision and contains the following fields:
- ``r`` (*double[3]*) -- Position of the collision in [cm].
- ``u`` (*double[3]*) -- Direction unit vector immediately after the collision.
- ``E`` (*double*) -- Incident particle energy before the collision in [eV].
- ``dE`` (*double*) -- Energy loss over the collision (:math:`E_\text{before} - E_\text{after}`) in [eV].
- ``time`` (*double*) -- Time of the collision in [s].
- ``wgt`` (*double*) -- Particle weight at the collision.
- ``event_mt`` (*int*) -- ENDF MT number identifying the reaction.
- ``delayed_group`` (*int*) -- Delayed neutron group index (non-zero for delayed events).
- ``cell_id`` (*int*) -- ID of the cell in which the collision occurred.
- ``nuclide_id`` (*int*) -- PDG number of the nuclide (100ZZZAAAM).
- ``material_id`` (*int*) -- ID of the material containing the collision site.
- ``universe_id`` (*int*) -- ID of the universe containing the collision site.
- ``n_collision`` (*int*) -- Collision counter for the particle history.
- ``particle`` (*int32_t*) -- Particle type (PDG number).
- ``parent_id`` (*int64_t*) -- Unique ID of the parent particle.
- ``progeny_id`` (*int64_t*) -- Progeny ID of the particle.
In an MPI run, OpenMC writes the combined dataset by gathering collision-track
entries from all ranks before flushing them to disk, so the final file appears
as though it were produced serially.

View file

@ -56,27 +56,6 @@ attributes:
.. _io_chain_reaction:
--------------------
``<source>`` Element
--------------------
The ``<source>`` element represents photon and electron sources associated with
the decay of a nuclide and contains information to construct an
:class:`openmc.stats.Univariate` object that represents this emission as an
energy distribution. This element has the following attributes:
:type:
The type of :class:`openmc.stats.Univariate` source term.
:particle:
The type of particle emitted, e.g., 'photon' or 'electron'
:parameters:
The parameters of the source term, e.g., for a
:class:`openmc.stats.Discrete` source, the energies (in [eV]) at which the
particles are emitted and their relative intensities in [Bq/atom] (in other
words, decay constants).
----------------------
``<reaction>`` Element
----------------------

View file

@ -4,7 +4,7 @@
Depletion Results File Format
=============================
The current version of the depletion results file format is 1.3.
The current version of the depletion results file format is 1.1.
**/**
@ -12,31 +12,30 @@ The current version of the depletion results file format is 1.3.
- **version** (*int[2]*) -- Major and minor version of the
statepoint file format.
:Datasets: - **eigenvalues** (*double[][2]*) -- k-eigenvalues at each timestep.
This array has shape (number of timesteps, 2). The second axis
contains the eigenvalue and its associated uncertainty.
- **number** (*double[][][]*) -- Total number of atoms at each
timestep. This array has shape (number of timesteps, number of
:Datasets: - **eigenvalues** (*double[][][2]*) -- k-eigenvalues at each
time/stage. This array has shape (number of timesteps, number of
stages, value). The last axis contains the eigenvalue and the
associated uncertainty
- **number** (*double[][][][]*) -- Total number of atoms. This array
has shape (number of timesteps, number of stages, number of
materials, number of nuclides).
- **reaction rates** (*double[][][][]*) -- Reaction rates at each
timestep. This array has shape (number of timesteps, number of
materials, number of nuclides, number of reactions). Only stored if
write_rates=True.
- **reaction rates** (*double[][][][][]*) -- Reaction rates used to
build depletion matrices. This array has shape (number of
timesteps, number of stages, number of materials, number of
nuclides, number of reactions).
- **time** (*double[][2]*) -- Time in [s] at beginning/end of each
step.
- **source_rate** (*double[]*) -- Power in [W] or source rate in
[neutron/sec] for each timestep.
- **source_rate** (*double[][]*) -- Power in [W] or source rate in
[neutron/sec]. This array has shape (number of timesteps, number
of stages).
- **depletion time** (*double[]*) -- Average process time in [s]
spent depleting a material across all burnable materials and,
if applicable, MPI processes.
- **keff_search_root** (*double[]*) -- Root of the keff search at the
end of the timestep, if applicable.
**/materials/<id>/**
:Attributes: - **index** (*int*) -- Index used in results for this material
- **volume** (*double*) -- Volume of this material in [cm^3]
- **name** (*char[]*) -- Name of this material
**/nuclides/<name>/**
@ -48,3 +47,10 @@ The current version of the depletion results file format is 1.3.
**/reactions/<name>/**
:Attributes: - **index** (*int*) -- Index user in results for this reaction
.. note::
The reaction rates for some isotopes not originally present may
be non-zero, but should be negligible compared to other atoms.
This can be controlled by changing the
:class:`openmc.deplete.Operator` ``dilute_initial`` attribute.

View file

@ -38,9 +38,11 @@ Each ``<surface>`` element can have the following attributes or sub-elements:
:boundary:
The boundary condition for the surface. This can be "transmission",
"vacuum", "reflective", or "periodic". Specify which planes are
periodic and the code will automatically identify which planes are
paired together.
"vacuum", "reflective", or "periodic". Periodic boundary conditions can
only be applied to x-, y-, and z-planes. Only axis-aligned periodicity is
supported, i.e., x-planes can only be paired with x-planes. Specify which
planes are periodic and the code will automatically identify which planes
are paired together.
*Default*: "transmission"
@ -316,10 +318,9 @@ the following attributes or sub-elements:
*Default*: None
:orientation:
The orientation of the hexagonal lattice. The string "x" indicates that each
lattice element has two faces that are perpendicular to the x-axis, whereas
the string "y" indicates that each lattice element has two faces that are
perpendicular to the y-axis.
The orientation of the hexagonal lattice. The string "x" indicates that two
sides of the lattice are parallel to the x-axis, whereas the string "y"
indicates that two sides are parallel to the y-axis.
*Default*: "y"
@ -406,64 +407,13 @@ Each ``<dagmc_universe>`` element can have the following attributes or sub-eleme
*Default*: None
:cell:
Zero or more ``<cell>`` sub-elements may appear to override properties of
individual DAGMC volumes. Each ``<cell>`` element supports the following
attributes and sub-elements:
:id:
The integer cell ID in the DAGMC geometry to override. Required.
.. note:: A geometry.xml file containing only a DAGMC model for a file named `dagmc.h5m` (no CSG)
looks as follows
:name:
An optional string label for the cell.
.. code-block:: xml
*Default*: None
:material:
The material ID to assign to this cell. Use ``void`` for vacuum. Multiple
space-separated IDs may be given to specify a distribmat (distributed
material) assignment. Required.
:temperature:
Temperature(s) in [K] to assign to the cell. Must be greater than or equal
to 0. Multiple space-separated values may be given.
*Default*: None
:density:
Density in [g/cm³] to assign to the cell. Must be greater than 0. Requires a non-void
material fill. Multiple space-separated values may be given.
*Default*: None
:volume:
Volume of the cell in [cm³].
.. note:: DAGMC can compute cell volumes exactly from the triangulated
mesh surfaces. Specifying a manual volume risks inconsistency
with that capability.
*Default*: None
The following standard ``<cell>`` attributes are **not** supported inside
``<dagmc_universe>`` and will raise an error if present: ``region``,
``fill``, ``universe``, ``translation``, ``rotation``.
.. deprecated::
The ``<material_overrides>`` sub-element (containing ``<cell_override>``
children with ``<material_ids>``) is deprecated. A deprecation warning is
emitted and the overrides are converted to the ``<cell>`` format at parse
time. It is an error to specify both ``<material_overrides>`` and
``<cell>`` sub-elements on the same ``<dagmc_universe>``.
*Default*: None
.. note:: A geometry.xml file containing only a DAGMC model for a file named
`dagmc.h5m` (no CSG) looks as follows:
.. code-block:: xml
<?xml version='1.0' encoding='utf-8'?>
<geometry>
<dagmc_universe filename="dagmc.h5m" id="1" />
</geometry>
<?xml version='1.0' encoding='utf-8'?>
<geometry>
<dagmc_universe filename="dagmc.h5m" id="1" />
</geometry>

View file

@ -44,7 +44,6 @@ Output Files
statepoint
source
collision_track
summary
properties
depletion_results
@ -52,4 +51,3 @@ Output Files
track
voxel
volume
weight_windows

View file

@ -133,10 +133,6 @@ Temperature-dependent data, provided for temperature <TTT>K.
This dataset is optional. This is a 1-D vector if `representation`
is "isotropic", or a 3-D vector if `representation` is "angle"
with dimensions of [polar][azimuthal][groups].
When this data is not available, an approximation using the
group energy boundaries is used. For more information see
the particle speed subsection in the multigroup-data section
of the theory manual.
**/<library name>/<TTT>K/scatter_data/**

View file

@ -4,7 +4,7 @@
Particle Restart File Format
============================
The current version of the particle restart file format is 2.1.
The current version of the particle restart file format is 2.0.
**/**
@ -26,7 +26,6 @@ The current version of the particle restart file format is 2.1.
- **run_mode** (*char[]*) -- Run mode used, either 'fixed source',
'eigenvalue', or 'particle restart'.
- **id** (*int8_t*) -- Unique identifier of the particle.
- **type** (*int32_t*) -- Particle type (PDG number)
- **weight** (*double*) -- Weight of the particle.
- **energy** (*double*) -- Energy of the particle in eV for
continuous-energy mode, or the energy group of the particle for

View file

@ -7,18 +7,13 @@ Geometry Plotting Specification -- plots.xml
Basic plotting capabilities are available in OpenMC by creating a plots.xml file
and subsequently running with the ``--plot`` command-line flag. The root element
of the plots.xml is simply ``<plots>`` and any number output plots can be
defined with ``<plot>`` sub-elements. Four plot types are currently implemented
defined with ``<plot>`` sub-elements. Two plot types are currently implemented
in openMC:
* ``slice`` 2D pixel plot along one of the major axes. Produces a PNG image
file.
* ``voxel`` 3D voxel data dump. Produces an HDF5 file containing voxel xyz
position and cell or material id.
* ``wireframe_raytrace`` 2D pixel plot of a three-dimensional view of a
geometry using wireframes around cells or materials and coloring by depth
through each material.
* ``solid_raytrace`` 2D pixel plot of a three-dimensional view of a geometry
with solid colored surfaces of a set of cells or materials.
------------------
@ -71,22 +66,21 @@ sub-elements:
*Default*: None - Required entry
:type:
Keyword for type of plot to be produced. Currently "slice", "voxel",
"wireframe_raytrace", and "solid_raytrace" plots are implemented. The
"slice" plot type creates 2D pixel maps saved in the PNG file format. The
"voxel" plot type produces a binary datafile containing voxel grid
positioning and the cell or material (specified by the ``color`` tag) at the
center of each voxel. Voxel plot files can be processed into VTK files using
the :func:`openmc.voxel_to_vtk` function and subsequently viewed with a 3D
viewer such as VISIT or Paraview. See :ref:`io_voxel` for information about
the datafile structure.
Keyword for type of plot to be produced. Currently only "slice" and "voxel"
plots are implemented. The "slice" plot type creates 2D pixel maps saved in
the PNG file format. The "voxel" plot type produces a binary datafile
containing voxel grid positioning and the cell or material (specified by the
``color`` tag) at the center of each voxel. Voxel plot files can be
processed into VTK files using the :ref:`scripts_voxel` script provided with
OpenMC and subsequently viewed with a 3D viewer such as VISIT or Paraview.
See the :ref:`io_voxel` for information about the datafile structure.
.. note:: High-resolution voxel files produced by OpenMC can be quite large,
but the equivalent VTK files will be significantly smaller.
*Default*: "slice"
All ``<plot>`` elements must contain the ``pixels``
``<plot>`` elements of ``type`` "slice" and "voxel" must contain the ``pixels``
attribute or sub-element:
:pixels:
@ -102,7 +96,7 @@ attribute or sub-element:
``width``/``pixels`` along that basis direction may not appear
in the plot.
*Default*: None - Required entry for all plots
*Default*: None - Required entry for "slice" and "voxel" plots
``<plot>`` elements of ``type`` "slice" can also contain the following
attributes or sub-elements. These are not used in "voxel" plots:
@ -131,11 +125,6 @@ attributes or sub-elements. These are not used in "voxel" plots:
Specifies the custom color for the cell or material. Should be 3 integers
separated by spaces.
:xs:
The attenuation coefficient for volume rendering of color in units of
inverse centimeters. Zero corresponds to transparency. Only for plot type
"wireframe_raytrace".
As an example, if your plot is colored by material and you want material 23
to be blue, the corresponding ``color`` element would look like:
@ -162,18 +151,6 @@ attributes or sub-elements. These are not used in "voxel" plots:
*Default*: 255 255 255 (white)
:show_overlaps:
Indicates whether overlapping regions of different cells are shown.
*Default*: None
:overlap_color:
Specifies the RGB color of overlapping regions of different cells. Does not
do anything if ``show_overlaps`` is "false" or not specified. Should be 3
integers separated by spaces.
*Default*: 255 0 0 (red)
:meshlines:
The ``meshlines`` sub-element allows for plotting the boundaries of a
regular mesh on top of a plot. Only one ``meshlines`` element is allowed per
@ -202,80 +179,3 @@ attributes or sub-elements. These are not used in "voxel" plots:
*Default*: 0 0 0 (black)
*Default*: None
``<plot>`` elements of ``type`` "wireframe_raytrace" or "solid_raytrace" can contain the
following attributes or sub-elements.
:camera_position:
Location in 3D Cartesian space the camera is at.
*Default*: None - Required for all ``wireframe_raytrace`` or
``solid_raytrace`` plots
:look_at:
Location in 3D Cartesian space the camera is looking at.
*Default*: None - Required for all ``wireframe_raytrace`` or
``solid_raytrace`` plots
:field_of_view:
The horizontal field of view in degrees. Defaults to roughly the same value
as for the human eye.
*Default*: 70
:orthographic_width:
If set to a nonzero value, an orthographic rather than perspective
projection for the camera is employed. An orthographic projection puts out
parallel rays from the camera of a width prescribed here in the horizontal
direction, with the width in the vertical direction decided by the pixel
aspect ratio.
*Default*: 0
``<plot>`` elements of ``type`` "solid_raytrace" can contain the following attributes or
sub-elements.
:opaque_ids:
List of integer IDs of cells or materials to be treated as visible in the
plot. Whether the integers are interpreted as cell or material IDs depends
on ``color_by``.
*Default*: None - Required for all phong plots
:light_position:
Location in 3D Cartesian space of the light.
*Default*: Same location as ``camera_position``
:diffuse_fraction:
Fraction of light originating from non-directional sources. If set to one,
the coloring is not influenced by surface curvature, and no shadows appear.
If set to zero, only regions illuminated by the light are not black.
*Default*: 0.1
``<plot>`` elements of ``type`` "wireframe_raytrace" can contain the following
attributes or sub-elements.
:wireframe_color:
RGB value of the wireframe's color
*Default*: 0, 0, 0 (black)
:wireframe_thickness:
Integer number of pixels that the wireframe takes up. The value is a radius
of the wireframe. Setting to zero removes any wireframing.
*Default*: 0
:wireframe_ids:
Integer IDs of cells or materials of regions to draw wireframes around.
Whether the integers are interpreted as cell or material IDs depends on
``color_by``.
*Default*: None

View file

@ -4,7 +4,7 @@
Properties File Format
======================
The current version of the properties file format is 1.1.
The current version of the properties file format is 1.0.
**/**
@ -25,7 +25,6 @@ The current version of the properties file format is 1.1.
**/geometry/cells/cell <uid>/**
:Datasets: - **temperature** (*double[]*) -- Temperature of the cell in [K].
- **density** (*double[]*) -- Density of the cell in [g/cm3].
**/materials/**

File diff suppressed because it is too large Load diff

View file

@ -15,8 +15,6 @@ following the same format.
**/**
:Attributes: - **filetype** (*char[]*) -- String indicating the type of file.
- **version** (*int[2]*) -- Major and minor version of the source
file format.
:Datasets:
@ -24,5 +22,5 @@ following the same format.
particle. The compound type has fields ``r``, ``u``, ``E``,
``time``, ``wgt``, ``delayed_group``, ``surf_id`` and ``particle``,
which represent the position, direction, energy, time, weight,
delayed group, surface ID, and particle type (PDG number),
respectively.
delayed group, surface ID, and particle type (0=neutron, 1=photon,
2=electron, 3=positron), respectively.

View file

@ -4,7 +4,7 @@
State Point File Format
=======================
The current version of the statepoint file format is 18.2.
The current version of the statepoint file format is 17.0.
**/**
@ -23,7 +23,6 @@ The current version of the statepoint file format is 18.2.
bank is present (1) or not (0).
:Datasets: - **seed** (*int8_t*) -- Pseudo-random number generator seed.
- **stride** (*uint64_t*) -- Pseudo-random number generator stride.
- **energy_mode** (*char[]*) -- Energy mode of the run, either
'continuous-energy' or 'multi-group'.
- **run_mode** (*char[]*) -- Run mode used, either 'eigenvalue' or
@ -56,8 +55,8 @@ The current version of the statepoint file format is 18.2.
``time``, ``wgt``, ``delayed_group``, ``surf_id``, and
``particle``, which represent the position, direction, energy,
time, weight, delayed group, surface ID, and particle type
(PDG number), respectively. Only present when `run_mode` is
'eigenvalue'.
(0=neutron, 1=photon, 2=electron, 3=positron), respectively. Only
present when `run_mode` is 'eigenvalue'.
**/tallies/**
@ -69,39 +68,21 @@ The current version of the statepoint file format is 18.2.
:Attributes: - **n_meshes** (*int*) -- Number of meshes in the problem.
- **ids** (*int[]*) -- User-defined unique ID of each mesh.
.. _mesh-spec-hdf5:
**/tallies/meshes/mesh <uid>/**
:Attributes: - **id** (*int*) -- ID of the mesh
:Datasets: - **name** (*char[]*) -- Name of the mesh.
- **type** (*char[]*) -- Type of mesh.
:Datasets: - **type** (*char[]*) -- Type of mesh.
- **dimension** (*int*) -- Number of mesh cells in each dimension.
- **Regular Mesh Only:**
- **lower_left** (*double[]*) -- Coordinates of lower-left corner of
mesh.
- **upper_right** (*double[]*) -- Coordinates of upper-right corner
of mesh.
- **width** (*double[]*) -- Width of each mesh cell in each
dimension.
- **Rectilinear Mesh Only:**
- **x_grid** (*double[]*) -- Mesh divisions along the x-axis.
- **y_grid** (*double[]*) -- Mesh divisions along the y-axis.
- **z_grid** (*double[]*) -- Mesh divisions along the z-axis.
- **Cylindrical & Spherical Mesh Only:**
- **r_grid** (*double[]*) -- The mesh divisions along the r-axis.
- **phi_grid** (*double[]*) -- The mesh divisions along the phi-axis.
- **origin** (*double[]*) -- The origin in cartesian coordinates.
- **Spherical Mesh Only:**
- **theta_grid** (*double[]*) -- The mesh divisions along the theta-axis.
- **lower_left** (*double[]*) -- Coordinates of lower-left corner of
mesh.
- **upper_right** (*double[]*) -- Coordinates of upper-right corner
of mesh.
- **width** (*double[]*) -- Width of each mesh cell in each
dimension.
- **Unstructured Mesh Only:**
- **filename** (*char[]*) -- Name of the mesh file.
- **library** (*char[]*) -- Mesh library used to represent the
- **library** (*char[]*) -- Mesh library used to represent the
mesh ("moab" or "libmesh").
- **length_multiplier** (*double*) Scaling factor applied to the mesh.
- **options** (*char[]*) -- Special options that control spatial
search data structures used.
- **volumes** (*double[]*) -- Volume of each mesh cell.
- **vertices** (*double[]*) -- x, y, z values of the mesh vertices.
- **connectivity** (*int[]*) -- Connectivity array for the mesh
@ -128,10 +109,6 @@ The current version of the statepoint file format is 18.2.
- **y** (*double[]*) -- Interpolant values for energyfunction
interpolation. Only used for 'energyfunction' filters.
:Attributes:
- **interpolation** (*int*) -- Interpolation type. Only used for
'energyfunction' filters.
**/tallies/derivatives/derivative <id>/**
:Datasets: - **independent variable** (*char[]*) -- Independent variable of
@ -147,10 +124,6 @@ The current version of the statepoint file format is 18.2.
- **internal** (*int*) -- Flag indicating the presence of tally
data (0) or absence of tally data (1). All user defined
tallies will have a value of 0 unless otherwise instructed.
- **multiply_density** (*int*) -- Flag indicating whether reaction
rates should be multiplied by atom density (1) or not (0).
- **higher_moments** (*int*) -- Flag indicating whether
higher-order tally moments are enabled (1) or not (0).
:Datasets: - **n_realizations** (*int*) -- Number of realizations.
- **n_filters** (*int*) -- Number of filters used.

View file

@ -4,7 +4,7 @@
Summary File Format
===================
The current version of the summary file format is 6.1.
The current version of the summary file format is 6.0.
**/**
@ -38,7 +38,6 @@ The current version of the summary file format is 6.1.
is an array if the cell uses distributed materials, otherwise it is
a scalar.
- **temperature** (*double[]*) -- Temperature of the cell in Kelvin.
- **density** (*double[]*) -- Density of the cell in [g/cm3].
- **translation** (*double[3]*) -- Translation applied to the fill
universe. This dataset is present only if fill_type is set to
'universe'.
@ -61,11 +60,9 @@ The current version of the summary file format is 6.1.
- **coefficients** (*double[]*) -- Array of coefficients that define
the surface. See :ref:`surface_element` for what coefficients are
defined for each surface type.
- **boundary_type** (*char[]*) -- Boundary condition applied to
the surface. Can be 'transmission', 'vacuum', 'reflective',
'periodic', or 'white'.
- **albedo** (*double*) -- Boundary albedo as a positive multiplier
of particle weight. If absent, it is assumed to be 1.0.
- **boundary_condition** (*char[]*) -- Boundary condition applied to
the surface. Can be 'transmission', 'vacuum', 'reflective', or
'periodic'.
- **geom_type** (*char[]*) -- Type of geometry used to create the cell.
Either 'csg' or 'dagmc'.

View file

@ -69,12 +69,6 @@ The ``<tally>`` element accepts the following sub-elements:
list of valid scores can be found in the :ref:`user's guide
<usersguide_scores>`.
:multiply_density:
A boolean that indicates whether reaction rate scores should be computed by
multiplying by the atom density of a nuclide present in a material.
*Default*: true
:trigger:
Precision trigger applied to all filter bins and nuclides for this tally.
It must specify the trigger's type, threshold and scores to which it will
@ -100,18 +94,6 @@ The ``<tally>`` element accepts the following sub-elements:
*Default*: None
:ignore_zeros:
Whether to allow zero tally bins to be ignored when assessing the
convergece of the precision trigger. If True, only nonzero tally scores
will be compared to the trigger's threshold.
.. note:: The ``ignore_zeros`` option can cause the tally trigger to fire
prematurely if there are no hits in any bins at the first
evalulation. It is the user's responsibility to specify enough
particles per batch to get a nonzero score in at least one bin.
*Default*: False
:scores:
The score(s) in this tally to which the trigger should be applied.
@ -142,9 +124,9 @@ attributes/sub-elements:
:type:
The type of the filter. Accepted options are "cell", "cellfrom",
"cellborn", "surface", "material", "universe", "energy", "energyout",
"mu", "polar", "azimuthal", "mesh", "distribcell", "delayedgroup",
"energyfunction", "particle", and "particleproduction".
"cellborn", "surface", "material", "universe", "energy", "energyout", "mu",
"polar", "azimuthal", "mesh", "distribcell", "delayedgroup",
"energyfunction", and "particle".
:bins:
A description of the bins for each type of filter can be found in
@ -318,34 +300,8 @@ should be set to:
they use ``energy`` and ``y``.
:particle:
A list of particle identifiers to tally, specified as strings (e.g.,
``neutron``, ``photon``, ``He4``) or as integer PDG numbers.
:particleproduction:
This filter tallies secondary particles produced in reactions, binned by
particle type and, optionally, by energy. Unlike other energy filters, the
weight applied is the weight of the secondary particle. To obtain secondary
particle production rates, use this filter with the ``events`` score.
The filter uses the following sub-elements instead of ``bins``:
:particles:
A space-separated list of secondary particle types to tally (e.g.,
``photon``, ``neutron``, ``electron``).
:energies:
An optional monotonically increasing list of energy boundaries in [eV]
for binning the secondary particle energies. If omitted, total production
is tallied without energy binning.
For example, to tally photon and neutron production in three energy groups:
.. code-block:: xml
<filter id="1" type="particleproduction">
<particles>photon neutron</particles>
<energies>0.0 1.0e5 1.0e6 20.0e6</energies>
</filter>
A list of integers indicating the type of particles to tally ('neutron' = 1,
'photon' = 2, 'electron' = 3, 'positron' = 4).
------------------
``<mesh>`` Element
@ -355,11 +311,6 @@ If a mesh is desired as a filter for a tally, it must be specified in a separate
element with the tag name ``<mesh>``. This element has the following
attributes/sub-elements:
:name:
An optional string name to identify the mesh in output files.
*Default*: ""
:type:
The type of mesh. This can be either "regular", "rectilinear",
"cylindrical", "spherical", or "unstructured".
@ -400,17 +351,10 @@ attributes/sub-elements:
:theta_grid:
The mesh divisions along the theta-axis. (For spherical mesh only.)
:origin:
The origin in cartesian coordinates. (For cylindrical and spherical meshes only.)
:library:
The mesh library used to represent an unstructured mesh. This can be either
"moab" or "libmesh". (For unstructured mesh only.)
:options:
Special options that control spatial search data structures used. (For
unstructured mesh using MOAB only)
:filename:
The name of the mesh file to be loaded at runtime. (For unstructured mesh
only.)

View file

@ -4,7 +4,7 @@
Track File Format
=================
The current revision of the particle track file format is 3.1.
The current revision of the particle track file format is 3.0.
**/**
@ -32,5 +32,6 @@ The current revision of the particle track file format is 3.1.
the array for each primary/secondary particle. The
last offset should match the total size of the
array.
- **particles** (*int32_t[]*) -- Particle type for
each primary/secondary particle (PDG number).
- **particles** (*int[]*) -- Particle type for each
primary/secondary particle (0=neutron, 1=photon,
2=electron, 3=positron).

View file

@ -1,39 +0,0 @@
.. _io_weight_windows:
====================
Weight Window Format
====================
The current revision of the weight window file format is 1.0.
**/**
:Attributes: - **filetype** (*char[]*) -- String indicating the type of file.
- **version** (*int[2]*) -- Major and minor version of the weight
window file format.
**/weight_windows/**
:Attributes: - **n_weight_windows** (*int*) -- Number of weight window objects in the file.
- **ids** (*int[]*) -- Unique IDs of weight window objects in the file.
**/weight_windows/weight_windows_<uid>/**
:Datasets: - **mesh** (*int*) -- ID of the mesh associated with the weight window object.
- **particle_type** (*char[]*) -- Particle type to which the weight windows apply.
- **energy_bounds** (*double[]*) -- Energy bounds of the weight windows in [eV]
- **lower_ww_bounds** (*double[]*) -- Weight window lower bounds.
- **upper_ww_bounds** (*double[]*) -- Weight window upper bounds.
- **survival_ratio** (*double*) -- Weight window survival ratio.
- **max_lower_bound_ratio** (*double*) -- Maximum particle weight to lower weight window bound ratio.
- **max_split** (*int*) -- Maximum number of splits per weight window check.
- **weight_cutoff** (*double*) -- Particle weight cutoff.
**/meshes/**
:Attributes: - **n_meshes** (*int*) -- Number of meshes in the file.
- **ids** (*int[]*) -- User-defined unique ID of each mesh.
**/meshes/mesh <uid>/**
Please see the section on **/tallies/meshes/** in the :doc:`statepoint`.

View file

@ -4,7 +4,7 @@
License Agreement
=================
Copyright © 2011-2026 Massachusetts Institute of Technology, UChicago Argonne
Copyright © 2011-2022 Massachusetts Institute of Technology, UChicago Argonne
LLC, and OpenMC contributors
Permission is hereby granted, free of charge, to any person obtaining a copy of

View file

@ -1,362 +0,0 @@
.. _methods_charged_particle_physics:
========================
Charged Particle Physics
========================
OpenMC neglects the spatial transport of charged particles (electrons and
positrons), assuming they deposit all their energy locally and produce
bremsstrahlung photons at their birth location. This approximation, called
thick-target bremsstrahlung (TTB) approximation is justified by the fact that
charged particles have much shorter stopping ranges compared to neutrons and
photons, especially in high-density materials.
-----------------------------
Charged Particle Interactions
-----------------------------
Bremsstrahlung
--------------
When a charged particle is decelerated in the field of an atom, some of its
kinetic energy is converted into electromagnetic radiation known as
bremsstrahlung, or 'braking radiation'. In each event, an electron or positron
with kinetic energy :math:`T` generates a photon with an energy :math:`E`
between :math:`0` and :math:`T`. Bremsstrahlung is described by a cross section
that is differential in photon energy, in the direction of the emitted photon,
and in the final direction of the charged particle. However, in Monte Carlo
simulations it is typical to integrate over the angular variables to obtain a
single differential cross section with respect to photon energy, which is often
expressed in the form
.. math::
:label: bremsstrahlung-dcs
\frac{d\sigma_{\text{br}}}{dE} = \frac{Z^2}{\beta^2} \frac{1}{E}
\chi(Z, T, \kappa),
where :math:`\kappa = E/T` is the reduced photon energy and :math:`\chi(Z, T,
\kappa)` is the scaled bremsstrahlung cross section, which is experimentally
measured.
Because electrons are attracted to atomic nuclei whereas positrons are
repulsed, the cross section for positrons is smaller, though it approaches that
of electrons in the high energy limit. To obtain the positron cross section, we
multiply :eq:`bremsstrahlung-dcs` by the :math:`\kappa`-independent factor used
in Salvat_,
.. math::
:label: positron-factor
\begin{aligned}
F_{\text{p}}(Z,T) =
& 1 - \text{exp}(-1.2359\times 10^{-1}t + 6.1274\times 10^{-2}t^2 - 3.1516\times 10^{-2}t^3 \\
& + 7.7446\times 10^{-3}t^4 - 1.0595\times 10^{-3}t^5 + 7.0568\times 10^{-5}t^6 \\
& - 1.8080\times 10^{-6}t^7),
\end{aligned}
where
.. math::
:label: positron-factor-t
t = \ln\left(1 + \frac{10^6}{Z^2}\frac{T}{\text{m}_\text{e}c^2} \right).
:math:`F_{\text{p}}(Z,T)` is the ratio of the radiative stopping powers for
positrons and electrons. Stopping power describes the average energy loss per
unit path length of a charged particle as it passes through matter:
.. math::
:label: stopping-power
-\frac{dT}{ds} = n \int E \frac{d\sigma}{dE} dE \equiv S(T),
where :math:`n` is the number density of the material and :math:`d\sigma/dE` is
the cross section differential in energy loss. The total stopping power
:math:`S(T)` can be separated into two components: the radiative stopping
power :math:`S_{\text{rad}}(T)`, which refers to energy loss due to
bremsstrahlung, and the collision stopping power :math:`S_{\text{col}}(T)`,
which refers to the energy loss due to inelastic collisions with bound
electrons in the material that result in ionization and excitation. The
radiative stopping power for electrons is given by
.. math::
:label: radiative-stopping-power
S_{\text{rad}}(T) = n \frac{Z^2}{\beta^2} T \int_0^1 \chi(Z,T,\kappa)
d\kappa.
To obtain the radiative stopping power for positrons,
:eq:`radiative-stopping-power` is multiplied by :eq:`positron-factor`.
While the models for photon interactions with matter described above can safely
assume interactions occur with free atoms, sampling the target atom based on
the macroscopic cross sections, molecular effects cannot necessarily be
disregarded for charged particle treatment. For compounds and mixtures, the
bremsstrahlung cross section is calculated using Bragg's additivity rule as
.. math::
:label: material-bremsstrahlung-dcs
\frac{d\sigma_{\text{br}}}{dE} = \frac{1}{\beta^2 E} \sum_i \gamma_i Z^2_i
\chi(Z_i, T, \kappa),
where the sum is over the constituent elements and :math:`\gamma_i` is the
atomic fraction of the :math:`i`-th element. Similarly, the radiative stopping
power is calculated using Bragg's additivity rule as
.. math::
:label: material-radiative-stopping-power
S_{\text{rad}}(T) = \sum_i w_i S_{\text{rad},i}(T),
where :math:`w_i` is the mass fraction of the :math:`i`-th element and
:math:`S_{\text{rad},i}(T)` is found for element :math:`i` using
:eq:`radiative-stopping-power`. The collision stopping power, however, is a
function of certain quantities such as the mean excitation energy :math:`I` and
the density effect correction :math:`\delta_F` that depend on molecular
properties. These quantities cannot simply be summed over constituent elements
in a compound, but should instead be calculated for the material. The Bethe
formula can be used to find the collision stopping power of the material:
.. math::
:label: material-collision-stopping-power
S_{\text{col}}(T) = \frac{2 \pi r_e^2 m_e c^2}{\beta^2} N_A \frac{Z}{A_M}
[\ln(T^2/I^2) + \ln(1 + \tau/2) + F(\tau) - \delta_F(T)],
where :math:`N_A` is Avogadro's number, :math:`A_M` is the molar mass,
:math:`\tau = T/m_e`, and :math:`F(\tau)` depends on the particle type. For
electrons,
.. math::
:label: F-electron
F_{-}(\tau) = (1 - \beta^2)[1 + \tau^2/8 - (2\tau + 1) \ln2],
while for positrons
.. math::
:label: F-positron
F_{+}(\tau) = 2\ln2 - (\beta^2/12)[23 + 14/(\tau + 2) + 10/(\tau + 2)^2 +
4/(\tau + 2)^3].
The density effect correction :math:`\delta_F` takes into account the reduction
of the collision stopping power due to the polarization of the material the
charged particle is passing through by the electric field of the particle.
It can be evaluated using the method described by Sternheimer_, where the
equation for :math:`\delta_F` is
.. math::
:label: density-effect-correction
\delta_F(\beta) = \sum_{i=1}^n f_i \ln[(l_i^2 + l^2)/l_i^2] -
l^2(1-\beta^2).
Here, :math:`f_i` is the oscillator strength of the :math:`i`-th transition,
given by :math:`f_i = n_i/Z`, where :math:`n_i` is the number of electrons in
the :math:`i`-th subshell. The frequency :math:`l` is the solution of the
equation
.. math::
:label: density-effect-l
\frac{1}{\beta^2} - 1 = \sum_{i=1}^{n} \frac{f_i}{\bar{\nu}_i^2 + l^2},
where :math:`\bar{v}_i` is defined as
.. math::
:label: density-effect-nubar
\bar{\nu}_i = h\nu_i \rho / h\nu_p.
The plasma energy :math:`h\nu_p` of the medium is given by
.. math::
:label: plasma-frequency
h\nu_p = \sqrt{\frac{(hc)^2 r_e \rho_m N_A Z}{\pi A}},
where :math:`A` is the atomic weight and :math:`\rho_m` is the density of the
material. In :eq:`density-effect-nubar`, :math:`h\nu_i` is the oscillator
energy, and :math:`\rho` is an adjustment factor introduced to give agreement
between the experimental values of the oscillator energies and the mean
excitation energy. The :math:`l_i` in :eq:`density-effect-correction` are
defined as
.. math::
:label: density-effect-li
\begin{aligned}
l_i &= (\bar{\nu}_i^2 + 2/3f_i)^{1/2} ~~~~&\text{for}~~ \bar{\nu}_i > 0 \\
l_n &= f_n^{1/2} ~~~~&\text{for}~~ \bar{\nu}_n = 0,
\end{aligned}
where the second case applies to conduction electrons. For a conductor,
:math:`f_n` is given by :math:`n_c/Z`, where :math:`n_c` is the effective
number of conduction electrons, and :math:`v_n = 0`. The adjustment factor
:math:`\rho` is determined using the equation for the mean excitation energy:
.. math::
:label: mean-excitation-energy
\ln I = \sum_{i=1}^{n-1} f_i \ln[(h\nu_i\rho)^2 + 2/3f_i(h\nu_p)^2]^{1/2} +
f_n \ln (h\nu_pf_n^{1/2}).
.. _ttb:
Thick-Target Bremsstrahlung Approximation
+++++++++++++++++++++++++++++++++++++++++
Since charged particles lose their energy on a much shorter distance scale than
neutral particles, not much error should be introduced by neglecting to
transport electrons. However, the bremsstrahlung emitted from high energy
electrons and positrons can travel far from the interaction site. Thus, even
without a full electron transport mode it is necessary to model bremsstrahlung.
We use a thick-target bremsstrahlung (TTB) approximation based on the models in
Salvat_ and Kaltiaisenaho_ for generating bremsstrahlung photons, which assumes
the charged particle loses all its energy in a single homogeneous material
region.
To model bremsstrahlung using the TTB approximation, we need to know the number
of photons emitted by the charged particle and the energy distribution of the
photons. These quantities can be calculated using the continuous slowing down
approximation (CSDA). The CSDA assumes charged particles lose energy
continuously along their trajectory with a rate of energy loss equal to the
total stopping power, ignoring fluctuations in the energy loss. The
approximation is useful for expressing average quantities that describe how
charged particles slow down in matter. For example, the CSDA range approximates
the average path length a charged particle travels as it slows to rest:
.. math::
:label: csda-range
R(T) = \int^T_0 \frac{dT'}{S(T')}.
Actual path lengths will fluctuate around :math:`R(T)`. The average number of
photons emitted per unit path length is given by the inverse bremsstrahlung
mean free path:
.. math::
:label: inverse-bremsstrahlung-mfp
\lambda_{\text{br}}^{-1}(T,E_{\text{cut}})
= n\int_{E_{\text{cut}}}^T\frac{d\sigma_{\text{br}}}{dE}dE
= n\frac{Z^2}{\beta^2}\int_{\kappa_{\text{cut}}}^1\frac{1}{\kappa}
\chi(Z,T,\kappa)d\kappa.
The lower limit of the integral in :eq:`inverse-bremsstrahlung-mfp` is non-zero
because the bremsstrahlung differential cross section diverges for small photon
energies but is finite for photon energies above some cutoff energy
:math:`E_{\text{cut}}`. The mean free path
:math:`\lambda_{\text{br}}^{-1}(T,E_{\text{cut}})` is used to calculate the
photon number yield, defined as the average number of photons emitted with
energy greater than :math:`E_{\text{cut}}` as the charged particle slows down
from energy :math:`T` to :math:`E_{\text{cut}}`. The photon number yield is
given by
.. math::
:label: photon-number-yield
Y(T,E_{\text{cut}}) = \int^{R(T)}_{R(E_{\text{cut}})}
\lambda_{\text{br}}^{-1}(T',E_{\text{cut}})ds = \int_{E_{\text{cut}}}^T
\frac{\lambda_{\text{br}}^{-1}(T',E_{\text{cut}})}{S(T')}dT'.
:math:`Y(T,E_{\text{cut}})` can be used to construct the energy spectrum of
bremsstrahlung photons: the number of photons created with energy between
:math:`E_1` and :math:`E_2` by a charged particle with initial kinetic energy
:math:`T` as it comes to rest is given by :math:`Y(T,E_1) - Y(T,E_2)`.
To simulate the emission of bremsstrahlung photons, the total stopping power
and bremsstrahlung differential cross section for positrons and electrons must
be calculated for a given material using :eq:`material-bremsstrahlung-dcs` and
:eq:`material-radiative-stopping-power`. These quantities are used to build the
tabulated bremsstrahlung energy PDF and CDF for that material for each incident
energy :math:`T_k` on the energy grid. The following algorithm is then applied
to sample the photon energies:
1. For an incident charged particle with energy :math:`T`, sample the number of
emitted photons as
.. math::
N = \lfloor Y(T,E_{\text{cut}}) + \xi_1 \rfloor.
2. Rather than interpolate the PDF between indices :math:`k` and :math:`k+1`
for which :math:`T_k < T < T_{k+1}`, which is computationally expensive, use
the composition method and sample from the PDF at either :math:`k` or
:math:`k+1`. Using linear interpolation on a logarithmic scale, the PDF can
be expressed as
.. math::
p_{\text{br}}(T,E) = \pi_k p_{\text{br}}(T_k,E) + \pi_{k+1}
p_{\text{br}}(T_{k+1},E),
where the interpolation weights are
.. math::
\pi_k = \frac{\ln T_{k+1} - \ln T}{\ln T_{k+1} - \ln T_k},~~~
\pi_{k+1} = \frac{\ln T - \ln T_k}{\ln T_{k+1} - \ln T_k}.
Sample either the index :math:`i = k` or :math:`i = k+1` according to the
point probabilities :math:`\pi_{k}` and :math:`\pi_{k+1}`.
3. Determine the maximum value of the CDF :math:`P_{\text{br,max}}`.
3. Sample the photon energies using the inverse transform method with the
tabulated CDF :math:`P_{\text{br}}(T_i, E)` i.e.,
.. math::
E = E_j \left[ (1 + a_j) \frac{\xi_2 P_{\text{br,max}} -
P_{\text{br}}(T_i, E_j)} {E_j p_{\text{br}}(T_i, E_j)} + 1
\right]^{\frac{1}{1 + a_j}}
where the interpolation factor :math:`a_j` is given by
.. math::
a_j = \frac{\ln p_{\text{br}}(T_i,E_{j+1}) - \ln p_{\text{br}}(T_i,E_j)}
{\ln E_{j+1} - \ln E_j}
and :math:`P_{\text{br}}(T_i, E_j) \le \xi_2 P_{\text{br,max}} \le
P_{\text{br}}(T_i, E_{j+1})`.
We ignore the range of the electron or positron, i.e., the bremsstrahlung
photons are produced in the same location that the charged particle was
created. The direction of the photons is assumed to be the same as the
direction of the incident charged particle, which is a reasonable approximation
at higher energies when the bremsstrahlung radiation is emitted at small
angles.
Electron-Positron Annihilation
------------------------------
When a positron collides with an electron, both particles are annihilated and
generally two photons with equal energy are created. If the kinetic energy of
the positron is high enough, the two photons can have different energies, and
the higher-energy photon is emitted preferentially in the direction of flight
of the positron. It is also possible to produce a single photon if the
interaction occurs with a bound electron, and in some cases three (or, rarely,
even more) photons can be emitted. However, the annihilation cross section is
largest for low-energy positrons, and as the positron energy decreases, the
angular distribution of the emitted photons becomes isotropic.
In OpenMC, we assume the most likely case in which a low-energy positron (which
has already lost most of its energy to bremsstrahlung radiation) interacts with
an electron which is free and at rest. Two photons with energy equal to the
electron rest mass energy :math:`m_e c^2 = 0.511` MeV are emitted isotropically
in opposite directions.
.. _Kaltiaisenaho: https://aaltodoc.aalto.fi/bitstream/handle/123456789/21004/master_Kaltiaisenaho_Toni_2016.pdf
.. _Salvat: https://doi.org/10.1787/32da5043-en
.. _Sternheimer: https://doi.org/10.1103/PhysRevB.26.6067

View file

@ -178,27 +178,6 @@ been selected. There are three methods available:
section data is loaded for a single temperature and is used in the
unresolved resonance and fast energy ranges.
------------------
NCrystal materials
------------------
As an alternative of the standard thermal scattering treatment using
:math:`S(\alpha,\beta)` tables, OpenMC allows to create materials using
NCrystal_. In addition to the regular thermal elastic, and thermal inelastic
processes, NCrystal allows the generation of models for materials that cannot
currently included in ACE files such as oriented single crystals (see the
`NCrystal paper`_), and further extend the physics `using plugins`_. Thermal
scattering kernels are generated on the fly from dynamic and structural data, or
loaded from :math:`S(\alpha,\beta)` tables converted from ENDF6 evaluations.
These kernels are sampled in a direct way using a fast `rejection algorithm`_
that does not require previous processing. A `large library`_ of materials is
already included in the NCrystal distribution, and new materials can be easily
defined from scratch in the `NCMAT format`_ or `combining existing files`_.
The compositions of the materials defined in NCrystal are passed on to OpenMC
all other reactions except for thermal neutron scattering are handled by
continuous energy ACE libraries.
----------------
Multi-Group Data
----------------
@ -289,63 +268,14 @@ sections. This allows flexibility for the model to use highly anisotropic
scattering information in the water while the fuel can be simulated with linear
or even isotropic scattering.
Particle Speed
--------------
When using a multigroup representation of cross sections, the particle speed has
meaning only in an average sense. The particle speed is important when modeling
dynamic behavior. OpenMC calculates the particle speed using the inverse
velocity multigroup data if it is available. If such data is not available,
OpenMC uses an approximate velocity using the group energy bounds in the
following way:
.. math::
\frac{1}{v_g} = \int_{E_{\text{min}}^g}^{E_{\text{max}}^g} \frac{1}{v(E)} \frac{\alpha}{E} dE
Where :math:`E_{\text{min}}^g` and :math:`E_{\text{max}}^g` are the group energy
boundaries for group :math:`g`. :math:`v(E)` is the neutron velocity calculated
using relativistic kinematics, :math:`\alpha` is a normalization constant for the
:math:`\frac{1}{E}` spectrum.
This equation is valid when inside the group boundaries the neutron spectrum
follows a typical :math:`\frac{1}{E}` slowing down spectrum. This assumption is
widely used when generating fine group neutron cross section data libraries from
continuous energy data.
The solution to this equation is:
.. math::
\frac{1}{v_g} = \frac{1}{c \log\left(\frac{E_{\text{max}}^g}{E_{\text{min}}^g}\right)}
\left[ 2(\operatorname{arctanh}(k_{\text{max}}^{-1}) - \operatorname{arctanh}(k_{\text{min}}^{-1}))
- (k_{\text{max}}-k_{\text{min}}) \right]
where :math:`c` is the speed of light and :math:`k_{\text{max}}`,
:math:`k_{\text{min}}` are defined by a change of variables:
.. math::
k = \sqrt{1+\frac{2 m_n c^2}{E}}
where :math:`E` is the particle kinetic energy and :math:`m_n` is the neutron
rest mass.
.. _logarithmic mapping technique:
https://mcnp.lanl.gov/pdf_files/TechReport_2014_LANL_LA-UR-14-24530_Brown.pdf
https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-ur-14-24530.pdf
.. _Hwang: https://doi.org/10.13182/NSE87-A16381
.. _Josey: https://doi.org/10.1016/j.jcp.2015.08.013
.. _WMP Library: https://github.com/mit-crpg/WMP_Library
.. _MCNP: https://mcnp.lanl.gov
.. _Serpent: https://serpent.vtt.fi
.. _NJOY: https://www.njoy21.io/
.. _Serpent: http://montecarlo.vtt.fi
.. _NJOY: https://www.njoy21.io/NJOY21/
.. _ENDF/B data: https://www.nndc.bnl.gov/endf-b8.0/
.. _Leppanen: https://doi.org/10.1016/j.anucene.2009.03.019
.. _algorithms: http://ab-initio.mit.edu/faddeeva/
.. _NCrystal: https://github.com/mctools/ncrystal
.. _NCrystal paper: https://doi.org/10.1016/j.cpc.2019.07.015
.. _using plugins: https://doi.org/10.1016/j.cpc.2021.108082
.. _rejection algorithm: https://doi.org/10.1016/j.jcp.2018.11.043
.. _large library: https://github.com/mctools/ncrystal/wiki/Data-library
.. _NCMAT format: https://github.com/mctools/ncrystal/wiki/NCMAT-format
.. _combining existing files: https://github.com/mctools/ncrystal/wiki/Announcement-Release3.0.0#2-multiphase-materials
.. _algorithms: http://ab-initio.mit.edu/wiki/index.php/Faddeeva_Package

View file

@ -114,7 +114,7 @@ The predictor method only requires one evaluation and its error converges as
twice as expensive as the predictor method, but achieves an error of
:math:`\mathcal{O}(h^2)`. An exhaustive description of time integration methods
and their merits can be found in the `thesis of Colin Josey
<https://dspace.mit.edu/handle/1721.1/7582>`_.
<http://dspace.mit.edu/handle/1721.1/7582>`_.
OpenMC does not rely on a single time integration method but rather has several
classes that implement different algorithms. For example, the
@ -257,85 +257,3 @@ choose one of two methods for estimating the heating rate, including:
The method for normalization can be chosen through the ``normalization_mode``
argument to the :class:`openmc.deplete.CoupledOperator` class.
--------------
Transfer Rates
--------------
OpenMC allows continuous removal or feed of nuclides by adding an
extra transfer rate term to the depletion matrix. An application of this feature
is the chemical processing of Molten Salt Reactors (MSRs), where one can
model the removal of fission products or feeding fresh fuel into the system.
A transfer rate as defined here is the rate at which nuclides are
continuously removed/fed from/to a material.
.. note::
A transfer rate can be positive or negative, indicating removal or feed
respectively.
Mathematically, it can be thought of as an additional term :math:`\mathbf{T}`
in the depletion equation that is proportional to the nuclide density, which can be written as:
.. math::
\begin{aligned}\frac{dN_i(t)}{dt} = &\underbrace{\sum\limits_j f_{j\rightarrow i}
\int_0^\infty dE \; \sigma_j (E,t) \phi(E,t) N_j(t) - \int_0^\infty dE \; \sigma_i(E,t)
\phi(E,t) N_i(t)}_\textbf{R} \\
&+ \underbrace{\sum_j \left [ \lambda_{j\rightarrow i} N_j(t) - \lambda_{i\rightarrow j} N_i(t) \right ]}_\textbf{D} \\
&- \underbrace{t_i N_i(t)}_\textbf{T} \end{aligned}
where the reaction term :math:`\mathbf{R}`, the decay term :math:`\mathbf{D}`
and the new transfer term :math:`\mathbf{T}` have been grouped together so that
:math:`\mathbf{A} = \mathbf{R}+\mathbf{D}-\mathbf{T}`.
The transfer rate coefficient :math:`t_i` defines the continuous transfer of the
nuclide :math:`i`, which behaves similar to radioactive decay.
:math:`t_i` can also be defined as the reciprocal of a cycle time
:math:`T_{cyc}`, intended as the time needed to process the whole inventory.
Note that this formulation assumes homogeneous distribution of nuclide
:math:`i` throughout the material.
A more rigorous description of removal rate and its implementation can be found
in the paper by `Hombourger
<https://doi.org/10.1016/j.anucene.2020.107504>`_.
The resulting burnup matrix can be solved with the same integration algorithms
that are used in the absence of the transfer term.
.. note::
If no ``destination_material`` is specified, nuclides that are removed
or fed will not be tracked afterwards.
Coupling materials
------------------
To keep track of removed nuclides or to feed nuclides from one depletable material
to another, the respective depletion equations have to be coupled. This can be
achieved by defining one block matrix, with diagonal blocks corresponding to
depletion matrices :math:`\mathbf{A_{ii}}`, where the index :math:`i` indicates
the depletable material id, and off-diagonal blocks corresponding to inter-material
coupling matrices :math:`\mathbf{T_{ij}}`, positioned so that that the indices :math:`i` and
:math:`j` indicate the nuclides receiving and losing materials, respectively.
The nuclide vectors are assembled together in one single vector and the resulting
system is solved with the same integration algorithms seen before.
As an example, consider the case of two depletable materials and one
transfer defined from material 1 to material 2. The final system will look like:
.. math::
\begin{aligned}\frac{d}{dt}\begin{pmatrix}\vec{N_1}\\ \vec{N_2}\end{pmatrix} &=
\begin{pmatrix}\mathbf{A_{11}} & \mathbf{0}\\ \mathbf{T_{21}} & \mathbf{A_{22 }}
\end{pmatrix} \begin{pmatrix}\vec{N_1}\\ \vec{N_2}\end{pmatrix} \end{aligned}
where:
:math:`\mathbf{A_{11}} = \mathbf{R_{11}}+\mathbf{D_{11}}-\mathbf{T_{21}}`, and
:math:`\mathbf{A_{22}} = \mathbf{R_{22}}+\mathbf{D_{22}}`.
Note that mass conservation is guaranteed by transferring the number
of atoms directly.

View file

@ -55,17 +55,15 @@ in :ref:`fission-bank-algorithms`.
Source Convergence Issues
-------------------------
.. _methods-shannon-entropy:
Diagnosing Convergence with Shannon Entropy
-------------------------------------------
As discussed earlier, it is necessary to converge both :math:`k_{eff}` and the
source distribution before any tallies can begin. Moreover, the convergence rate
of the source distribution is in general slower than that of :math:`k_{eff}`.
One should thus examine not only the convergence of :math:`k_{eff}` but also the
convergence of the source distribution in order to make decisions on when to
start active batches.
of the source distribution is in general slower than that of
:math:`k_{eff}`. One should thus examine not only the convergence of
:math:`k_{eff}` but also the convergence of the source distribution in order to
make decisions on when to start active batches.
However, the representation of the source distribution makes it a bit more
difficult to analyze its convergence. Since :math:`k_{eff}` is a scalar
@ -110,13 +108,6 @@ at plots of :math:`k_{eff}` and the Shannon entropy. A number of methods have
been proposed (see e.g. [Romano]_, [Ueki]_), but each of these is not without
problems.
Shannon entropy is calculated differently for the random ray solver, as
described :ref:`in the random ray theory section
<methods-shannon-entropy-random-ray>`. Additionally, as the Shannon entropy only
serves as a diagnostic tool for convergence of the fission source distribution,
there is currently no diagnostic to determine if the scattering source
distribution in random ray is converged.
---------------------------
Uniform Fission Site Method
---------------------------
@ -151,7 +142,7 @@ than unity. By ensuring that the expected number of fission sites in each mesh
cell is constant, the collision density across all cells, and hence the variance
of tallies, is more uniform than it would be otherwise.
.. _Shannon entropy: https://mcnp.lanl.gov/pdf_files/TechReport_2006_LANL_LA-UR-06-3737_Brown.pdf
.. _Shannon entropy: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-ur-06-3737.pdf
.. [Lieberoth] J. Lieberoth, "A Monte Carlo Technique to Solve the Static
Eigenvalue Problem of the Boltzmann Transport Equation," *Nukleonik*, **11**,

View file

@ -25,38 +25,19 @@ KERMA (Kinetic Energy Release in Materials) [Mack97]_ coefficients for reaction
:math:`\times` cross-section (e.g., eV-barn) and can be used much like a reaction
cross section for the purpose of tallying energy deposition.
KERMA coefficients can be computed using the energy-balance method with a
nuclear data processing code like NJOY, which estimates the KERMA coefficients
using the following equation:
KERMA coefficients can be computed using the energy-balance method with
a nuclear data processing code like NJOY, which performs the following
iteration over all reactions :math:`r` for all isotopes :math:`i`
requested
.. math::
k_{i, r}(E) = \left(E + Q_{i, r} - \sum\limits_x \bar{E}_{i, r, x}
\right)\sigma_{i, r}(E),
where the summation is over each secondary particle type :math:`x`. This
equation states that the energy deposited is equal to the energy of the incident
particle plus the reaction :math:`Q` value less the energy of secondary
particles that are transported away from the reaction site. For neutron
interactions, the energy-balance KERMA coefficient is
.. math::
k_{i, r}(E) = \left(E + Q_{i, r} - \sum\limits_x \bar{E}_{i, r, n}
k_{i, r}(E) = \left(E + Q_{i, r} - \bar{E}_{i, r, n}
- \bar{E}_{i, r, \gamma}\right)\sigma_{i, r}(E),
where :math:`\bar{E}_{i, r, n}` is the average energy of secondary neutrons and
:math:`\bar{E}_{i, r, \gamma}` is the average energy of secondary photons. For
photon and charged particle interactions the KERMA coefficient is
.. math::
:label: energy-balance-photon
k_{i, r}(E) = \left(E + Q_{i, r} - \sum\limits_x \bar{E}_{i, r, x}
\right)\sigma_{i, r}(E).
where the :math:`Q` value is zero for all interactions except for pair
production and positron annihilation.
removing the energy of neutral particles (neutrons and photons) that are
transported away from the reaction site :math:`\bar{E}`, and the reaction
:math:`Q` value.
-------
Fission
@ -139,7 +120,7 @@ run with :math:`N918` reflecting fission heating computed from NJOY.
This modified heating data is stored as the MT=901 reaction and will be scored
if ``heating-local`` is included in :attr:`openmc.Tally.scores`.
Coupled Neutron-Photon Transport
Coupled neutron-photon transport
--------------------------------
Here, OpenMC instructs ``heatr`` to assume that energy from photons is not
@ -157,50 +138,6 @@ Let :math:`N301` represent the total heating number returned from this
This modified heating data is stored as the MT=301 reaction and will be scored
if ``heating`` is included in :attr:`openmc.Tally.scores`.
Photons and Charged Particles
-----------------------------
In OpenMC, energy deposition from photons or charged particles is scored using
the energy balance method based on Equation :eq:`energy-balance-photon`. Special
consideration is given to electrons and positrons as described below.
+++++++++++++++++
Charged Particles
+++++++++++++++++
OpenMC tracks photons interaction by interaction so the energy deposited in each
collision is easily attributed back to the nuclide and reaction for which the
photon interacted with. Charged particles (electrons and photons) aren't tracked
in the same way. For charged particles, OpenMC assumes that all their energy
(less the energy of bremsstrahlung radiation) is deposited in the material in
which they were born. In this way it is harder to trace how much energy should
be attributed in each nuclide.
According to the CSDA approximation (see :ref:`ttb`) the energy deposited by a
charged particle with kinetic energy :math:`T` in the :math:`i`-th element can
be calculated as:
.. math::
E_{i} = \int_{0}^{R(T)} w_{i}S_{\text{col,i}} dx
where :math:`R(T)` is the CSDA range of the charged particle,
:math:`S_{\text{col},i}` is the collision stopping power of the charged particle
in the :math:`i`-th element and :math:`w_i` is the mass fraction of the
:math:`i`-th element. According to the Bethe formula the collision stopping
power of the :math:`i`-th element is proportional to :math:`Z_i/A_i`, so the
fractional collision stopping power from the :math:`i`-th element is:
.. math::
\frac{w_{i}S_{\text{col},i}(T)}{S_{\text{col}}(T)} =
\frac{\frac{w_{i}Z_{i}}{A_{i}}}{\sum_{i}\frac{w_{i}Z_{i}}{A_{i}}} =
\frac{\gamma_i Z_{i}}{\sum_{i}\gamma_i Z_{i}}.
where :math:`\gamma_i` is the atomic fraction of the :math:`i`-th element.
Therefore, the energy deposited by charged particles should be attributed to
a given element according to its fractional charge density.
----------
References
----------

View file

@ -1066,5 +1066,5 @@ surface is known as in :ref:`reflection`.
.. _constructive solid geometry: https://en.wikipedia.org/wiki/Constructive_solid_geometry
.. _surfaces: https://en.wikipedia.org/wiki/Surface
.. _MCNP: https://mcnp.lanl.gov
.. _Serpent: https://serpent.vtt.fi
.. _Serpent: http://montecarlo.vtt.fi
.. _Monte Carlo Performance benchmark: https://github.com/mit-crpg/benchmarks/tree/master/mc-performance/openmc

View file

@ -14,12 +14,9 @@ Theory and Methodology
random_numbers
neutron_physics
photon_physics
charged_particles_physics
tallies
eigenvalue
depletion
energy_deposition
parallelization
cmfd
variance_reduction
random_ray

View file

@ -91,7 +91,7 @@ inelastic scattering reactions. The specific multi-group scattering
implementation is discussed in the :ref:`multi-group-scatter` section.
Elastic scattering refers to the process by which a neutron scatters off a
nucleus and does not leave it in an excited state. It is referred to as "elastic"
nucleus and does not leave it in an excited. It is referred to as "elastic"
because in the center-of-mass system, the neutron does not actually lose
energy. However, in lab coordinates, the neutron does indeed lose
energy. Elastic scattering can be treated exactly in a Monte Carlo code thanks
@ -290,10 +290,7 @@ create and store fission sites for the following generation. First, the average
number of prompt and delayed neutrons must be determined to decide whether the
secondary neutrons will be prompt or delayed. This is important because delayed
neutrons have a markedly different spectrum from prompt neutrons, one that has a
lower average energy of emission. Furthermore, in simulations where tracking
time of neutrons is important, we need to consider the emission time delay of
the secondary neutrons, which is dependent on the decay constant of the
delayed neutron precursor. The total number of neutrons emitted
lower average energy of emission. The total number of neutrons emitted
:math:`\nu_t` is given as a function of incident energy in the ENDF format. Two
representations exist for :math:`\nu_t`. The first is a polynomial of order
:math:`N` with coefficients :math:`c_0,c_1,\dots,c_N`. If :math:`\nu_t` has this
@ -309,8 +306,8 @@ interpolation law. The number of prompt neutrons released per fission event
:math:`\nu_p` is also given as a function of incident energy and can be
specified in a polynomial or tabular format. The number of delayed neutrons
released per fission event :math:`\nu_d` can only be specified in a tabular
format. In practice, we only need to determine :math:`\nu_t` and
:math:`\nu_d`. Once these have been determined, we can calculate the delayed
format. In practice, we only need to determine :math:`nu_t` and
:math:`nu_d`. Once these have been determined, we can calculated the delayed
neutron fraction
.. math::
@ -338,14 +335,8 @@ neutrons. Otherwise, we produce :math:`\lfloor \nu \rfloor + 1` neutrons. Then,
for each fission site produced, we sample the outgoing angle and energy
according to the algorithms given in :ref:`sample-angle` and
:ref:`sample-energy` respectively. If the neutron is to be born delayed, then
there is an extra step of sampling a delayed neutron precursor group to get the
associated secondary energy distribution and the decay constant
:math:`\lambda`, which is needed to sample the emission delay time :math:`t_d`:
.. math::
:label: sample-delay-time
t_d = -\frac{\ln \xi}{\lambda}.
there is an extra step of sampling a delayed neutron precursor group since they
each have an associated secondary energy distribution.
The sampled outgoing angle and energy of fission neutrons along with the
position of the collision site are stored in an array called the fission
@ -1752,19 +1743,19 @@ types.
.. _Watt fission spectrum: https://doi.org/10.1103/PhysRev.87.1037
.. _Foderaro: https://dspace.mit.edu/handle/1721.1/1716
.. _Foderaro: http://hdl.handle.net/1721.1/1716
.. _OECD: https://www.oecd-nea.org/tools/abstract/detail/NEA-1792
.. _NJOY: https://www.njoy21.io/NJOY2016/
.. _PREPRO: https://www-nds.iaea.org/public/endf/prepro/
.. _PREPRO: https://www-nds.iaea.org/ndspub/endf/prepro/
.. _ENDF-6 Format: https://www.oecd-nea.org/dbdata/data/manual-endf/endf102.pdf
.. _Monte Carlo Sampler: https://mcnp.lanl.gov/pdf_files/TechReport_1983_LANL_LA-9721-MS_EverettCashwell.pdf
.. _Monte Carlo Sampler: https://permalink.lanl.gov/object/tr?what=info:lanl-repo/lareport/LA-09721-MS
.. _LA-UR-14-27694: https://www.osti.gov/biblio/1159204
.. _LA-UR-14-27694: https://permalink.lanl.gov/object/tr?what=info:lanl-repo/lareport/LA-UR-14-27694
.. _MC21: https://www.osti.gov/biblio/903083
@ -1772,4 +1763,6 @@ types.
.. _Sutton and Brown: https://www.osti.gov/biblio/307911
.. _lectures: https://mcnp.lanl.gov/pdf_files/TechReport_2005_LANL_LA-UR-05-4983_Brown.pdf
.. _lectures: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-ur-05-4983.pdf
.. _MCNP Manual: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-ur-03-1987.pdf

View file

@ -609,17 +609,17 @@ is actually independent of the number of nodes:
.. _first paper: https://doi.org/10.2307/2280232
.. _work of Forrest Brown: https://deepblue.lib.umich.edu/handle/2027.42/24996
.. _work of Forrest Brown: http://hdl.handle.net/2027.42/24996
.. _Brissenden and Garlick: https://doi.org/10.1016/0306-4549(86)90095-2
.. _MPICH: https://www.mpich.org
.. _MPICH: http://www.mpich.org
.. _binomial tree: https://www.mcs.anl.gov/~thakur/papers/ijhpca-coll.pdf
.. _Geary: https://doi.org/10.2307/2342070
.. _Barnett: https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.51.7772
.. _Barnett: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.51.7772
.. _single-instruction multiple-data: https://en.wikipedia.org/wiki/SIMD

View file

@ -667,6 +667,342 @@ and Auger electrons:
5. Repeat from step 1 for vacancy left by the transition electron.
Electron-Positron Annihilation
------------------------------
When a positron collides with an electron, both particles are annihilated and
generally two photons with equal energy are created. If the kinetic energy of
the positron is high enough, the two photons can have different energies, and
the higher-energy photon is emitted preferentially in the direction of flight
of the positron. It is also possible to produce a single photon if the
interaction occurs with a bound electron, and in some cases three (or, rarely,
even more) photons can be emitted. However, the annihilation cross section is
largest for low-energy positrons, and as the positron energy decreases, the
angular distribution of the emitted photons becomes isotropic.
In OpenMC, we assume the most likely case in which a low-energy positron (which
has already lost most of its energy to bremsstrahlung radiation) interacts with
an electron which is free and at rest. Two photons with energy equal to the
electron rest mass energy :math:`m_e c^2 = 0.511` MeV are emitted isotropically
in opposite directions.
Bremsstrahlung
--------------
When a charged particle is decelerated in the field of an atom, some of its
kinetic energy is converted into electromagnetic radiation known as
bremsstrahlung, or 'braking radiation'. In each event, an electron or positron
with kinetic energy :math:`T` generates a photon with an energy :math:`E`
between :math:`0` and :math:`T`. Bremsstrahlung is described by a cross section
that is differential in photon energy, in the direction of the emitted photon,
and in the final direction of the charged particle. However, in Monte Carlo
simulations it is typical to integrate over the angular variables to obtain a
single differential cross section with respect to photon energy, which is often
expressed in the form
.. math::
:label: bremsstrahlung-dcs
\frac{d\sigma_{\text{br}}}{dE} = \frac{Z^2}{\beta^2} \frac{1}{E}
\chi(Z, T, \kappa),
where :math:`\kappa = E/T` is the reduced photon energy and :math:`\chi(Z, T,
\kappa)` is the scaled bremsstrahlung cross section, which is experimentally
measured.
Because electrons are attracted to atomic nuclei whereas positrons are
repulsed, the cross section for positrons is smaller, though it approaches that
of electrons in the high energy limit. To obtain the positron cross section, we
multiply :eq:`bremsstrahlung-dcs` by the :math:`\kappa`-independent factor used
in Salvat_,
.. math::
:label: positron-factor
\begin{aligned}
F_{\text{p}}(Z,T) =
& 1 - \text{exp}(-1.2359\times 10^{-1}t + 6.1274\times 10^{-2}t^2 - 3.1516\times 10^{-2}t^3 \\
& + 7.7446\times 10^{-3}t^4 - 1.0595\times 10^{-3}t^5 + 7.0568\times 10^{-5}t^6 \\
& - 1.8080\times 10^{-6}t^7),
\end{aligned}
where
.. math::
:label: positron-factor-t
t = \ln\left(1 + \frac{10^6}{Z^2}\frac{T}{\text{m}_\text{e}c^2} \right).
:math:`F_{\text{p}}(Z,T)` is the ratio of the radiative stopping powers for
positrons and electrons. Stopping power describes the average energy loss per
unit path length of a charged particle as it passes through matter:
.. math::
:label: stopping-power
-\frac{dT}{ds} = n \int E \frac{d\sigma}{dE} dE \equiv S(T),
where :math:`n` is the number density of the material and :math:`d\sigma/dE` is
the cross section differential in energy loss. The total stopping power
:math:`S(T)` can be separated into two components: the radiative stopping
power :math:`S_{\text{rad}}(T)`, which refers to energy loss due to
bremsstrahlung, and the collision stopping power :math:`S_{\text{col}}(T)`,
which refers to the energy loss due to inelastic collisions with bound
electrons in the material that result in ionization and excitation. The
radiative stopping power for electrons is given by
.. math::
:label: radiative-stopping-power
S_{\text{rad}}(T) = n \frac{Z^2}{\beta^2} T \int_0^1 \chi(Z,T,\kappa)
d\kappa.
To obtain the radiative stopping power for positrons,
:eq:`radiative-stopping-power` is multiplied by :eq:`positron-factor`.
While the models for photon interactions with matter described above can safely
assume interactions occur with free atoms, sampling the target atom based on
the macroscopic cross sections, molecular effects cannot necessarily be
disregarded for charged particle treatment. For compounds and mixtures, the
bremsstrahlung cross section is calculated using Bragg's additivity rule as
.. math::
:label: material-bremsstrahlung-dcs
\frac{d\sigma_{\text{br}}}{dE} = \frac{1}{\beta^2 E} \sum_i \gamma_i Z^2_i
\chi(Z_i, T, \kappa),
where the sum is over the constituent elements and :math:`\gamma_i` is the
atomic fraction of the :math:`i`-th element. Similarly, the radiative stopping
power is calculated using Bragg's additivity rule as
.. math::
:label: material-radiative-stopping-power
S_{\text{rad}}(T) = \sum_i w_i S_{\text{rad},i}(T),
where :math:`w_i` is the mass fraction of the :math:`i`-th element and
:math:`S_{\text{rad},i}(T)` is found for element :math:`i` using
:eq:`radiative-stopping-power`. The collision stopping power, however, is a
function of certain quantities such as the mean excitation energy :math:`I` and
the density effect correction :math:`\delta_F` that depend on molecular
properties. These quantities cannot simply be summed over constituent elements
in a compound, but should instead be calculated for the material. The Bethe
formula can be used to find the collision stopping power of the material:
.. math::
:label: material-collision-stopping-power
S_{\text{col}}(T) = \frac{2 \pi r_e^2 m_e c^2}{\beta^2} N_A \frac{Z}{A_M}
[\ln(T^2/I^2) + \ln(1 + \tau/2) + F(\tau) - \delta_F(T)],
where :math:`N_A` is Avogadro's number, :math:`A_M` is the molar mass,
:math:`\tau = T/m_e`, and :math:`F(\tau)` depends on the particle type. For
electrons,
.. math::
:label: F-electron
F_{-}(\tau) = (1 - \beta^2)[1 + \tau^2/8 - (2\tau + 1) \ln2],
while for positrons
.. math::
:label: F-positron
F_{+}(\tau) = 2\ln2 - (\beta^2/12)[23 + 14/(\tau + 2) + 10/(\tau + 2)^2 +
4/(\tau + 2)^3].
The density effect correction :math:`\delta_F` takes into account the reduction
of the collision stopping power due to the polarization of the material the
charged particle is passing through by the electric field of the particle.
It can be evaluated using the method described by Sternheimer_, where the
equation for :math:`\delta_F` is
.. math::
:label: density-effect-correction
\delta_F(\beta) = \sum_{i=1}^n f_i \ln[(l_i^2 + l^2)/l_i^2] -
l^2(1-\beta^2).
Here, :math:`f_i` is the oscillator strength of the :math:`i`-th transition,
given by :math:`f_i = n_i/Z`, where :math:`n_i` is the number of electrons in
the :math:`i`-th subshell. The frequency :math:`l` is the solution of the
equation
.. math::
:label: density-effect-l
\frac{1}{\beta^2} - 1 = \sum_{i=1}^{n} \frac{f_i}{\bar{\nu}_i^2 + l^2},
where :math:`\bar{v}_i` is defined as
.. math::
:label: density-effect-nubar
\bar{\nu}_i = h\nu_i \rho / h\nu_p.
The plasma energy :math:`h\nu_p` of the medium is given by
.. math::
:label: plasma-frequency
h\nu_p = \sqrt{\frac{(hc)^2 r_e \rho_m N_A Z}{\pi A}},
where :math:`A` is the atomic weight and :math:`\rho_m` is the density of the
material. In :eq:`density-effect-nubar`, :math:`h\nu_i` is the oscillator
energy, and :math:`\rho` is an adjustment factor introduced to give agreement
between the experimental values of the oscillator energies and the mean
excitation energy. The :math:`l_i` in :eq:`density-effect-correction` are
defined as
.. math::
:label: density-effect-li
\begin{aligned}
l_i &= (\bar{\nu}_i^2 + 2/3f_i)^{1/2} ~~~~&\text{for}~~ \bar{\nu}_i > 0 \\
l_n &= f_n^{1/2} ~~~~&\text{for}~~ \bar{\nu}_n = 0,
\end{aligned}
where the second case applies to conduction electrons. For a conductor,
:math:`f_n` is given by :math:`n_c/Z`, where :math:`n_c` is the effective
number of conduction electrons, and :math:`v_n = 0`. The adjustment factor
:math:`\rho` is determined using the equation for the mean excitation energy:
.. math::
:label: mean-excitation-energy
\ln I = \sum_{i=1}^{n-1} f_i \ln[(h\nu_i\rho)^2 + 2/3f_i(h\nu_p)^2]^{1/2} +
f_n \ln (h\nu_pf_n^{1/2}).
.. _ttb:
Thick-Target Bremsstrahlung Approximation
+++++++++++++++++++++++++++++++++++++++++
Since charged particles lose their energy on a much shorter distance scale than
neutral particles, not much error should be introduced by neglecting to
transport electrons. However, the bremsstrahlung emitted from high energy
electrons and positrons can travel far from the interaction site. Thus, even
without a full electron transport mode it is necessary to model bremsstrahlung.
We use a thick-target bremsstrahlung (TTB) approximation based on the models in
Salvat_ and Kaltiaisenaho_ for generating bremsstrahlung photons, which assumes
the charged particle loses all its energy in a single homogeneous material
region.
To model bremsstrahlung using the TTB approximation, we need to know the number
of photons emitted by the charged particle and the energy distribution of the
photons. These quantities can be calculated using the continuous slowing down
approximation (CSDA). The CSDA assumes charged particles lose energy
continuously along their trajectory with a rate of energy loss equal to the
total stopping power, ignoring fluctuations in the energy loss. The
approximation is useful for expressing average quantities that describe how
charged particles slow down in matter. For example, the CSDA range approximates
the average path length a charged particle travels as it slows to rest:
.. math::
:label: csda-range
R(T) = \int^T_0 \frac{dT'}{S(T')}.
Actual path lengths will fluctuate around :math:`R(T)`. The average number of
photons emitted per unit path length is given by the inverse bremsstrahlung
mean free path:
.. math::
:label: inverse-bremsstrahlung-mfp
\lambda_{\text{br}}^{-1}(T,E_{\text{cut}})
= n\int_{E_{\text{cut}}}^T\frac{d\sigma_{\text{br}}}{dE}dE
= n\frac{Z^2}{\beta^2}\int_{\kappa_{\text{cut}}}^1\frac{1}{\kappa}
\chi(Z,T,\kappa)d\kappa.
The lower limit of the integral in :eq:`inverse-bremsstrahlung-mfp` is non-zero
because the bremsstrahlung differential cross section diverges for small photon
energies but is finite for photon energies above some cutoff energy
:math:`E_{\text{cut}}`. The mean free path
:math:`\lambda_{\text{br}}^{-1}(T,E_{\text{cut}})` is used to calculate the
photon number yield, defined as the average number of photons emitted with
energy greater than :math:`E_{\text{cut}}` as the charged particle slows down
from energy :math:`T` to :math:`E_{\text{cut}}`. The photon number yield is
given by
.. math::
:label: photon-number-yield
Y(T,E_{\text{cut}}) = \int^{R(T)}_{R(E_{\text{cut}})}
\lambda_{\text{br}}^{-1}(T',E_{\text{cut}})ds = \int_{E_{\text{cut}}}^T
\frac{\lambda_{\text{br}}^{-1}(T',E_{\text{cut}})}{S(T')}dT'.
:math:`Y(T,E_{\text{cut}})` can be used to construct the energy spectrum of
bremsstrahlung photons: the number of photons created with energy between
:math:`E_1` and :math:`E_2` by a charged particle with initial kinetic energy
:math:`T` as it comes to rest is given by :math:`Y(T,E_1) - Y(T,E_2)`.
To simulate the emission of bremsstrahlung photons, the total stopping power
and bremsstrahlung differential cross section for positrons and electrons must
be calculated for a given material using :eq:`material-bremsstrahlung-dcs` and
:eq:`material-radiative-stopping-power`. These quantities are used to build the
tabulated bremsstrahlung energy PDF and CDF for that material for each incident
energy :math:`T_k` on the energy grid. The following algorithm is then applied
to sample the photon energies:
1. For an incident charged particle with energy :math:`T`, sample the number of
emitted photons as
.. math::
N = \lfloor Y(T,E_{\text{cut}}) + \xi_1 \rfloor.
2. Rather than interpolate the PDF between indices :math:`k` and :math:`k+1`
for which :math:`T_k < T < T_{k+1}`, which is computationally expensive, use
the composition method and sample from the PDF at either :math:`k` or
:math:`k+1`. Using linear interpolation on a logarithmic scale, the PDF can
be expressed as
.. math::
p_{\text{br}}(T,E) = \pi_k p_{\text{br}}(T_k,E) + \pi_{k+1}
p_{\text{br}}(T_{k+1},E),
where the interpolation weights are
.. math::
\pi_k = \frac{\ln T_{k+1} - \ln T}{\ln T_{k+1} - \ln T_k},~~~
\pi_{k+1} = \frac{\ln T - \ln T_k}{\ln T_{k+1} - \ln T_k}.
Sample either the index :math:`i = k` or :math:`i = k+1` according to the
point probabilities :math:`\pi_{k}` and :math:`\pi_{k+1}`.
3. Determine the maximum value of the CDF :math:`P_{\text{br,max}}`.
3. Sample the photon energies using the inverse transform method with the
tabulated CDF :math:`P_{\text{br}}(T_i, E)` i.e.,
.. math::
E = E_j \left[ (1 + a_j) \frac{\xi_2 P_{\text{br,max}} -
P_{\text{br}}(T_i, E_j)} {E_j p_{\text{br}}(T_i, E_j)} + 1
\right]^{\frac{1}{1 + a_j}}
where the interpolation factor :math:`a_j` is given by
.. math::
a_j = \frac{\ln p_{\text{br}}(T_i,E_{j+1}) - \ln p_{\text{br}}(T_i,E_j)}
{\ln E_{j+1} - \ln E_j}
and :math:`P_{\text{br}}(T_i, E_j) \le \xi_2 P_{\text{br,max}} \le
P_{\text{br}}(T_i, E_{j+1})`.
We ignore the range of the electron or positron, i.e., the bremsstrahlung
photons are produced in the same location that the charged particle was
created. The direction of the photons is assumed to be the same as the
direction of the incident charged particle, which is a reasonable approximation
at higher energies when the bremsstrahlung radiation is emitted at small
angles.
.. _photon_production:
@ -723,14 +1059,16 @@ emitted photon.
.. _anomalous scattering: http://pd.chem.ucl.ac.uk/pdnn/diff1/anomscat.htm
.. _Kahn's rejection method: https://doi.org/10.2172/4353680
.. _Kahn's rejection method: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/aecu-3259_kahn.pdf
.. _Klein-Nishina: https://en.wikipedia.org/wiki/Klein%E2%80%93Nishina_formula
.. _LA-UR-04-0487: https://mcnp.lanl.gov/pdf_files/TechReport_2004_LANL_LA-UR-04-0487_Sood.pdf
.. _LA-UR-04-0487: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-ur-04-0487.pdf
.. _LA-UR-04-0488: https://mcnp.lanl.gov/pdf_files/TechReport_2004_LANL_LA-UR-04-0488_SoodWhite.pdf
.. _LA-UR-04-0488: https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-ur-04-0488.pdf
.. _Kaltiaisenaho: https://aaltodoc.aalto.fi/bitstream/handle/123456789/21004/master_Kaltiaisenaho_Toni_2016.pdf
.. _Salvat: https://doi.org/10.1787/32da5043-en
.. _Salvat: https://www.oecd-nea.org/globalsearch/download.php?doc=77434
.. _Sternheimer: https://doi.org/10.1103/PhysRevB.26.6067

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