Temperature majorant cross sections in Monte Carlo neutron tracking

Tuomas Viitanen, Jaakko Leppänen

    Research output: Contribution to journalArticleScientificpeer-review

    3 Citations (Scopus)


    This paper discusses the generation of temperature majorant cross sections, the type of cross sections required by two separate techniques related to Monte Carlo neutron tracking, namely, the Dopplerbroadening rejection correction (DBRC) and target motion sampling (TMS) temperature treatment methods. In the generation of these cross sections, the theoretically infinite range of thermal motion must be artificially limited by applying some sort of a cutoff condition, which affects both the accuracy and the performance of the calculations. In this paper, a revised approach for limiting thermal motion is first introduced, and then, optimal cutoff conditions are determined for both the traditional majorant, commonly used in DBRC implementations and old implementations of the TMS method, and the revised majorant. Using the revised type of temperature majorant cross sections increases the performance of the TMS method slightly, but no practical difference is observed with the DBRC method. It is also discovered that in ordinary reactor physical calculations, the cutoff conditions originally adopted from the SIGMA1 Dopplerbroadening code can be significantly relieved without compromising the accuracy of the results. By updating the cutoff conditions for majorant generation, the CPU time requirement of Serpent 2.1.17 is reduced by 8% to 23% in TMS calculations and by 1% to 6% in problems involving DBRC.
    Original languageEnglish
    Pages (from-to)209-223
    JournalNuclear Science and Engineering
    Issue number2
    Publication statusPublished - 2015
    MoE publication typeA1 Journal article-refereed


    • target tracking
    • CPU time
    • cut-off conditions
    • majorant
    • Monte Carlo neutron
    • reactor physical calculation
    • target motions
    • temperature treatments
    • thermal motion
    • Monte Carlo methods


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