Application of Monte Carlo Chord-Length Sampling Algorithms to Transport Through a 2-D Binary Stochastic Mixture
Monte Carlo algorithms are developed to calculate the ensemble-average particle leakage through the boundaries of a 2-D binary stochastic material. The mixture is specified within a rectangular area and consists of a fixed number of disks of constant radius randomly embedded in a matrix material. The algorithms are extensions of the proposal of Zimmerman et al., using chord-length sampling to eliminate the need to explicitly model the geometry of the mixture. Two variations are considered. The first algorithm uses Chord-Length Sampling (CLS) for both material regions. The second algorithm employs Limited Chord Length Sampling (LCLS), only using chord-length sampling in the matrix material. Ensemble-average leakage results are computed for a range of material interaction coefficients and compared against benchmark results for both accuracy and efficiency. both algorithms are exact for purely absorbing materials and provide decreasing accuracy as scattering is increased in the matrix material. The LCLS algorithm shows a better accuracy than the CLS algorithm for all cases while maintaining an equivalent or better efficiency. Accuracy and efficiency problems with the CLS algorithm are due principally to assumptions made in determining the chord-length distribution within the disks.
- Research Organization:
- Lockheed Martin, Inc., Schenectady, NY (US)
- Sponsoring Organization:
- US Department of Energy (US)
- DOE Contract Number:
- AC12-00SN39357
- OSTI ID:
- 820707
- Report Number(s):
- LM-02K012; TRN: US200405%%109
- Resource Relation:
- Other Information: PBD: 15 Mar 2002
- Country of Publication:
- United States
- Language:
- English
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