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Current OpenMC simulations for dispersed fuels (e.g., TRISO particles randomly distributed in a matrix material) require explicit geometric modeling of every fuel particle. For large-scale systems (e.g., pebble-bed reactors with tens of thousands of particles), this leads to:
High memory usage (storing coordinates of all particles).
Increased modeling complexity (additional tools needed for random distribution generation).
Proposed Solution
The core idea of Chord Length Sampling is to use probability distribution functions to describe the distance(i.e. the chord length) by which the particles will travel in the matric or in the fuel particles. By using the exponential distribution approximately, the positions of new fuel particles are sampled ‘‘on-the-fly’’ during the tracking process rather than being calculated explicitly
Reduces memory usage by >90% for systems with >10^5 particles.
Improves criticality calculation speed by 3–5× compared to explicit modeling.
Maintains accuracy within <100 pcm deviation from explicit benchmarks.
Target Use Cases
Advanced reactor designs like pebble-bed reactors, accident-tolerant fuels (ATFs), and other stochastic media applications require an efficient implicit modeling approach.
Compatibility
Implement Chord Length Sampling (CLS) to enable:
On-the-fly particle generation without explicit geometric modeling.
Seamless compatibility with existing CSG/DAGMC geometries.
Flexible configuration via XML input parameters.
Implementation Plan
1. Modifications to the Cell class
Parameters of the dispersed particle system will be added The Cell class , including Identifier for whether it is a diffusing region, packing fraction, particle radius, matrix material, particle material, etc.
2. Geometry Navigation
When particles are in the area of a CLSCell, they will follow the transport mode of the CLS method
Priority logic: Explicit surfaces override CLS-implicit boundaries. Material switching: Automatically update material when entering fuel particles.
This feature would significantly enhance OpenMC’s capability for modeling advanced reactor fuels. Feedback and collaboration from the community are welcome!
The text was updated successfully, but these errors were encountered:
Description
Current OpenMC simulations for dispersed fuels (e.g., TRISO particles randomly distributed in a matrix material) require explicit geometric modeling of every fuel particle. For large-scale systems (e.g., pebble-bed reactors with tens of thousands of particles), this leads to:
Proposed Solution
The core idea of Chord Length Sampling is to use probability distribution functions to describe the distance(i.e. the chord length) by which the particles will travel in the matric or in the fuel particles. By using the exponential distribution approximately, the positions of new fuel particles are sampled ‘‘on-the-fly’’ during the tracking process rather than being calculated explicitly
Advantages of CLS (validated in Liang et al., 2024):
Target Use Cases
Advanced reactor designs like pebble-bed reactors, accident-tolerant fuels (ATFs), and other stochastic media applications require an efficient implicit modeling approach.
Compatibility
Implement Chord Length Sampling (CLS) to enable:
Implementation Plan
1. Modifications to the Cell class
Parameters of the dispersed particle system will be added The Cell class , including Identifier for whether it is a diffusing region, packing fraction, particle radius, matrix material, particle material, etc.
2. Geometry Navigation
When particles are in the area of a CLSCell, they will follow the transport mode of the CLS method
Priority logic: Explicit surfaces override CLS-implicit boundaries.
Material switching: Automatically update material when entering fuel particles.
This feature would significantly enhance OpenMC’s capability for modeling advanced reactor fuels. Feedback and collaboration from the community are welcome!
The text was updated successfully, but these errors were encountered: