A New Automatic Biasing Technique for Transport Monte Carlo Methods

Application of the Monte Carlo method to deep-penetration transport problems often requires a biasing technique based on the use of an importance function. Here, in the framework of a multigroup model, we use an importance function in the form I g (⃗x, ⃗Ω) = e K g ⃗Ω.⃗x φ g (⃗Ω), where g is the ener...

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Bibliographic Details
Published inNuclear science and engineering Vol. 152; no. 1; pp. 48 - 55
Main Authors Depinay, Jean-Marc, Caillaud, Michel, Sentis, Remi
Format Journal Article
LanguageEnglish
Published La Grange Park, IL Taylor & Francis 01.01.2006
American Nuclear Society
Subjects
Applied sciences
Energy
Exact sciences and technology
Fuels
Nuclear fuels
Transport equation
Neutron flux
Monte Carlo method
Accuracy
Multigroup theory
Algorithm
Modeling
Pipeline
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Summary:Application of the Monte Carlo method to deep-penetration transport problems often requires a biasing technique based on the use of an importance function. Here, in the framework of a multigroup model, we use an importance function in the form I g (⃗x, ⃗Ω) = e K g ⃗Ω.⃗x φ g (⃗Ω), where g is the energy group index that ranges from 1 to G and ⃗Ω is a vector usually fixed empirically. We describe an algorithm to find a good set of coefficients K g and a good set of functions φ g . To do this, we solve a system derived from the homogenous adjoint equations. We give two numerical examples where we show how these importance functions can enhance the accuracy of the computation.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0029-5639
1943-748X
DOI:10.13182/NSE06-A2562