A Moment-Based Condensed History Algorithm
''Condensed History'' algorithms are Monte Carlo models for electron transport problems, They describe the aggregate effect of multiple collisions that occur when an electron travels a path length s{sub 0}. This path length is the distance each Monte Carlo electron travels between Condensed History steps. Conventional Condensed History schemes employ a splitting routine over the range 0 {le} s {le} s{sub 0}. For example, the Random Hinge method splits each path length step into two substeps; one with length {xi}s{sub 0} and one with length (1-{xi})s{sub 0}, where {xi} is a random number from 0 < {xi} < 1. Here we develop a new Condensed History algorithm to improve the accuracy of electron transport simulations by preserving the mean position and the variance in the mean of electrons that have traveled a path length s and are traveling with the direction cosine {mu}. These means and variances are obtained from the zeroth-, first-, and second-order spatial moments of the Boltzmann transport equation. Hence, our method is a Monte Carlo application of the ''Method of Moments''.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE Office of Defense Programs (DP) (US)
- DOE Contract Number:
- W-7405-Eng-48
- OSTI ID:
- 793626
- Report Number(s):
- UCRL-JC-139318; TRN: US200222%%344
- Resource Relation:
- Conference: American Nuclear Society 2000 Winter Meeting, Washington, DC (US), 11/12/2000--11/16/2000; Other Information: PBD: 15 Jun 2000
- Country of Publication:
- United States
- Language:
- English
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