Development of Monte Carlo Machine for Particle Transport Problem

1995 ◽  
Vol 32 (10) ◽  
pp. 953-964 ◽  
Author(s):  
Kenji HIGUCHI ◽  
Kiyoshi ASAI ◽  
Masayuki AKIMOTO
2018 ◽  
Vol 24 (2) ◽  
pp. 147-151 ◽  
Author(s):  
Ilya M. Sobol ◽  
Boris V. Shukhman

Abstract We considered average dimensions of the weighted Monte Carlo algorithm for a particle transport problem with multi-scattering setting and estimated the probability of particles penetration through a layer. The average dimension {\hat{d}} of the algorithm turned out to be small so that quasi-Monte Carlo estimates of the probability converge much faster than the Monte Carlo estimates. We justified the reasons to expect that the convergence of quasi-Monte Carlo estimates continue to be faster as the thickness of the layer increases. Here we calculated {\hat{d}} without the use of the ANOVA expansion.


2017 ◽  
Vol 3 ◽  
pp. 29 ◽  
Author(s):  
Henri Louvin ◽  
Eric Dumonteil ◽  
Tony Lelièvre ◽  
Mathias Rousset ◽  
Cheikh M. Diop

2014 ◽  
Vol 9 (05) ◽  
pp. C05016-C05016 ◽  
Author(s):  
K Sedlačková ◽  
B Zat'ko ◽  
A Šagátová ◽  
M Pavlovič ◽  
V Nečas ◽  
...  

2017 ◽  
Vol 44 (11) ◽  
pp. 6061-6073 ◽  
Author(s):  
Darshana Patel ◽  
Lawrence Bronk ◽  
Fada Guan ◽  
Christopher R. Peeler ◽  
Stephan Brons ◽  
...  

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