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Advanced Monte Carlo Methods in Reactor Physics, Eigenvalue and Steady State Problems
KTH, School of Engineering Sciences (SCI), Physics.ORCID iD: 0000-0002-7943-7517
2007 (English)Licentiate thesis, comprehensive summary (Other scientific)
Place, publisher, year, edition, pages
Stockholm: KTH , 2007. , viii, 27 p.
Series
Trita-FYS, ISSN 0280-316X ; 2007:40
National Category
Subatomic Physics
Identifiers
URN: urn:nbn:se:kth:diva-4458ISBN: 978-91-7178-716-3 (print)OAI: oai:DiVA.org:kth-4458DiVA: diva2:12366
Presentation
2007-06-07, FA32, AlvaNova, Roslagstullsbacken 21, Stockholm, 11:00
Note
QC 20101104Available from: 2007-07-10 Created: 2007-07-10 Last updated: 2010-11-04Bibliographically approved
List of papers
1. Parallelization of Monte Carlo Eigenvalue Callculations by the Stabilized Fission Matrix Method.
Open this publication in new window or tab >>Parallelization of Monte Carlo Eigenvalue Callculations by the Stabilized Fission Matrix Method.
(English)Article in journal (Other academic) Submitted
National Category
Subatomic Physics
Identifiers
urn:nbn:se:kth:diva-7362 (URN)
Note
QS 20120326Available from: 2007-07-10 Created: 2007-07-10 Last updated: 2012-03-26Bibliographically approved
2. Stochastic Approximation for Monte Carlo Calculation of Steady-State Conditions in Thermal Reactors
Open this publication in new window or tab >>Stochastic Approximation for Monte Carlo Calculation of Steady-State Conditions in Thermal Reactors
2006 (English)In: Nuclear science and engineering, ISSN 0029-5639, E-ISSN 1943-748X, Vol. 152, 274-283 p.Article in journal (Refereed) Published
Abstract [en]

A new adaptive stochastic approximation method for an efficient Monte Carlo calculation of steady-state conditions in thermal reactor cores is described The core conditions that we consider are spatial distributions of power, neutron flux, coolant density, and strongly absorbing fission products like Xe-135. These distributions relate to each other; thus, the steady-state conditions are described by a system of nonlinear equations. When a Monte Carlo method is used to evaluate the power or neutron flux, then the task turns to a nonlinear stochastic root-finding problem that is usually solved in the iterative manner by stochastic optimization methods. One of those methods is stochastic approximation where efficiency depends on a sequence of stepsize and sample size parameters. The stepsize generation is often based on the well-known Robbins-Monro algorithm; however, the efficient generation of the sample size (number of neutrons simulated at each iteration step) was not published yet. The proposed method controls both the stepsize and the sample size in an efficient way; according to the results, the method reaches the highest possible convergence rate.

Keyword
ROBBINS-MONRO PROCEDURE
National Category
Physical Sciences
Identifiers
urn:nbn:se:kth:diva-7363 (URN)000235833100003 ()2-s2.0-33645138278 (Scopus ID)
Note
QC 20100709Available from: 2007-07-10 Created: 2007-07-10 Last updated: 2017-12-14Bibliographically approved

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Dufek, Jan

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