scholarly journals Variance-Reduction Methods for Monte Carlo Simulation of Radiation Transport

2021 ◽  
Vol 9 ◽  
Author(s):  
Salvador García-Pareja ◽  
Antonio M. Lallena ◽  
Francesc Salvat
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Variance Reduction ◽  
Radiation Transport ◽  
Scattering Method ◽  
Variance Reduction Techniques ◽  
Simulation Efficiency ◽  
Reduction Techniques ◽  
Exponential Transform ◽  
Reduction Methods

After a brief description of the essentials of Monte Carlo simulation methods and the definition of simulation efficiency, the rationale for variance-reduction techniques is presented. Popular variance-reduction techniques applicable to Monte Carlo simulations of radiation transport are described and motivated. The focus is on those techniques that can be used with any transport code, irrespective of the strategies used to track charged particles; they operate by manipulating either the number and weights of the transported particles or the mean free paths of the various interaction mechanisms. The considered techniques are 1) splitting and Russian roulette, with the ant colony method as builder of importance maps, 2) exponential transform and interaction-forcing biasing, 3) Woodcock or delta-scattering method, 4) interaction forcing, and 5) proper use of symmetries and combinations of different techniques. Illustrative results from analog simulations (without recourse to variance-reduction) and from variance-reduced simulations of various transport problems are presented.

scholarly journals Some variance reduction methods for numerical stochastic homogenization

2016 ◽  
Vol 374 (2066) ◽  
pp. 20150168 ◽  
Author(s):  
X. Blanc ◽  
C. Le Bris ◽  
F. Legoll
Keyword(s):  
Monte Carlo ◽  
Variance Reduction ◽  
Stochastic Homogenization ◽  
Numerical Homogenization ◽  
Variance Reduction Techniques ◽  
Reduction Techniques ◽  
Effective Coefficients ◽  
Engineering Sciences ◽  
Reduction Methods ◽  
The Cost

We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here.

scholarly journals Monte Carlo Simulation and Experimental Validation for Radiation Protection with Multiple Complex Source Terms and Deep Penetration for a Radioactive Liquid Waste Cementation Facility

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Wenqian Li ◽  
Xuegang Liu ◽  
Sheng Fang ◽  
Xueliang Fu ◽  
Kaiqiang Guo
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Radiation Protection ◽  
Experimental Measurement ◽  
Variance Reduction ◽  
Liquid Waste ◽  
Deep Penetration ◽  
Radioactive Liquid Waste ◽  
Variance Reduction Techniques ◽  
Reduction Techniques

A new radioactive liquid waste cementation facility was under commissioning recently in the Institute of Nuclear and New Energy Technology of Tsinghua University, which is designed to simultaneously process multiple intermediate-level radioactive waste drums. Therefore, the multiple volume sources and the scattering effect becomes a key issue in its radiation protection. For this purpose, the Monte Carlo program FLUKA code and experimental measurement were both adopted. In the FLUKA simulation, five different scenarios were considered, i.e., one drum, two drums, four drums, six drums, and eight drums. For the multiple volume sources, the source subroutine code of FLUKA was rewritten to realize the sampling. The complex shielding also leads to a deep penetration problem; hence, the optimization algorithm and variance reduction techniques were adopted. During the measurement, two scenarios, outdoor and indoor, were carried out separately representing the dose field when only one drum is considered and when the scattering effect is considered. A comparison between the experiments and calculations shows very good agreement. From both of the Monte Carlo simulation and the experimental measurement, it can be drawn that, in the horizontal direction, with the increase of the drum number, the dose rate increases very little, while in the vertical direction, the increase of the dose rate is very obvious with the increase of the drum number. The complicated source term sampling methods, the optimization algorithm and variance reduction techniques, and the experimental verification can provide valuable references for the similar scattering problem in radiation protection and shielding design.

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