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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2017.1
- 수록면
- 1,172 - 1,180 (9page)
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The application of Monte Carlo (MC) to large-scale fixed-source problems has recently become possible with new hybrid methods that automate generation of parameters for variance reduction techniques. Two common variance reduction techniques, weight windows and source biasing, have been automated and popularized by the consistent adjoint-driven importance sampling (CADIS) method. This method uses the adjoint solution from an inexpensive deterministic calculation to define a consistent set of weight windows and source particles for a subsequent MC calculation. One of the motivations for source consistency is to avoid the splitting or rouletting of particles at birth, which requires computational resources. However, it is not always possible or desirable to implement such consistency, which results in inconsistent source biasing. This paper develops an original framework that mathematically expresses the coupling of the weight window and source biasing techniques, allowing the authors to explore the impact of inconsistent source sampling on the variance of MC results. A numerical experiment supports this new framework and suggests that certain classes of problems may be relatively insensitive to inconsistent source sampling schemes with moderate levels of splitting and rouletting.
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참고문헌 (7)
참고문헌 신청
G. I. Bell / 1967 / Nuclear Reactor Theory / Van Nostrand and Reinhold
J. C. Wagner / 1998 / Automated variance reduction of Monte Carlo shielding calculations using the discrete ordinates adjoint function / Nucl. Sci. Eng 128 : 186 ~ 208
J. C. Wagner / 2014 / FW-CADIS method for global and regional variance reduction of Monte Carlo radiation transport calculations / Nucl. Sci. Eng 176 : 37 ~ 57
J. Spanier / 2008 / Monte Carlo Principles and Neutron Transport Problems / Dover Publications
S. C. Wilson / 2009 / Rejection sampling from a spherical harmonics angular flux functional expansion for a discrete ordinates to Monte Carlo splice / Proc. International Conferenc
J. C. Wagner / 1998 / Automated variance reduction of Monte Carlo shielding calculations using the discrete ordinates adjoint function / Nucl. Sci. Eng 128 : 186 ~ 208
J. C. Wagner / 2014 / FW-CADIS method for global and regional variance reduction of Monte Carlo radiation transport calculations / Nucl. Sci. Eng 176 : 37 ~ 57
J. Spanier / 2008 / Monte Carlo Principles and Neutron Transport Problems / Dover Publications
S. C. Wilson / 2009 / Rejection sampling from a spherical harmonics angular flux functional expansion for a discrete ordinates to Monte Carlo splice / Proc. International Conferenc
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