Chain segmentation for the Monte Carlo solution of particle transport problems
Journal Article
·
· Nucl. Technol./Fusion; (United States)
OSTI ID:6189424
A Monte Carlo approach is proposed where the random walk chains generated in particle transport simulations are segmented. Forward and adjoint-mode estimators are then used in conjunction with the firstevent source density on the segmented chains to obtain multiple estimates of the individual terms of the Neumann series solution at each collision point. The solution is then constructed by summation of the series. The approach is compared to the exact analytical and to the Monte Carlo nonabsorption weighting method results for two representative slowing down and deep penetration problems. Application of the proposed approach leads to unbiased estimates for limited numbers of particle simulations and is useful in suppressing an effective bias problem observed in some cases of deep penetration particle transport problems.
- Research Organization:
- The Univ. of Illinois Nuclear Eng. Program, Urbana, IL
- OSTI ID:
- 6189424
- Journal Information:
- Nucl. Technol./Fusion; (United States), Journal Name: Nucl. Technol./Fusion; (United States) Vol. 5:1; ISSN NTFUD
- Country of Publication:
- United States
- Language:
- English
Similar Records
A contribution Monte Carlo method
Generalized approach to the biased adjoint Monte Carlo calculation
Monte Carlo techniques for analyzing deep-penetration problems
Journal Article
·
Mon Oct 31 23:00:00 EST 1994
· Nuclear Science and Engineering; (United States)
·
OSTI ID:7022944
Generalized approach to the biased adjoint Monte Carlo calculation
Thesis/Dissertation
·
Tue Dec 31 23:00:00 EST 1985
·
OSTI ID:6630011
Monte Carlo techniques for analyzing deep-penetration problems
Journal Article
·
Fri Jan 31 23:00:00 EST 1986
· Nucl. Sci. Eng.; (United States)
·
OSTI ID:5903948