Novel Monte Carlo weight window generator for global tallying problems based on maximization of global efficiency indicator

IF 3.8 2区物理与天体物理 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Computational Physics Pub Date : 2025-09-16 DOI:10.1016/j.jcp.2025.114383

Xian Zhang , Shu Li , Xin Wang , DanHua ShangGuan

{"title":"Novel Monte Carlo weight window generator for global tallying problems based on maximization of global efficiency indicator","authors":"Xian Zhang , Shu Li , Xin Wang , DanHua ShangGuan","doi":"10.1016/j.jcp.2025.114383","DOIUrl":null,"url":null,"abstract":"<div><div>Weight window method is powerful in seeking precise global tallies or single target tally of particle transport problems within a reasonable time cost when its parameters are suitable. But how to get excellent parameters is not trivial, especially for complex transport models. Various strategies are proposed to set numerous parameters of this method based on various considerations. But this challenging problem is still open for new exploration despite all the progress which have been achieved. This paper aims to solve the global tallying problem, which is more difficult in the vast majority of all cases, by a novel weight window generator which supplies excellent parameters of weight window method. This generator relies on the maximization of global efficiency indicator and a natural adaptive strategy. The efficiency and reliability of this generator are validated on the Winfrith Water benchmark and AP1000 full-core model, respectively. Compared to the classical MAGIC method, this proposed method can enhance global efficiency by 2-3 times magnitude when measured by the same global efficiency indicator.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"542 ","pages":"Article 114383"},"PeriodicalIF":3.8000,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Physics","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0021999125006655","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}

引用次数: 0

Abstract

Weight window method is powerful in seeking precise global tallies or single target tally of particle transport problems within a reasonable time cost when its parameters are suitable. But how to get excellent parameters is not trivial, especially for complex transport models. Various strategies are proposed to set numerous parameters of this method based on various considerations. But this challenging problem is still open for new exploration despite all the progress which have been achieved. This paper aims to solve the global tallying problem, which is more difficult in the vast majority of all cases, by a novel weight window generator which supplies excellent parameters of weight window method. This generator relies on the maximization of global efficiency indicator and a natural adaptive strategy. The efficiency and reliability of this generator are validated on the Winfrith Water benchmark and AP1000 full-core model, respectively. Compared to the classical MAGIC method, this proposed method can enhance global efficiency by 2-3 times magnitude when measured by the same global efficiency indicator.

查看原文本刊更多论文

基于全局效率指标最大化的全局理货问题蒙特卡罗加权窗口生成器

权窗法在参数合适的情况下，能够在合理的时间成本内寻求粒子输运问题的精确全局或单目标统计。但如何获得最佳参数并非易事，特别是对于复杂的输运模型。基于各种考虑，提出了各种策略来设置该方法的众多参数。但是，尽管已经取得了种种进展，这个具有挑战性的问题仍有待新的探索。本文提出了一种新的权窗生成器，该生成器提供了权窗法的优良参数，旨在解决在绝大多数情况下比较困难的全局理货问题。该生成器依赖于全局效率指标的最大化和自然自适应策略。该发电机的效率和可靠性分别在Winfrith Water基准和AP1000全核模型上进行了验证。与传统的MAGIC方法相比，在使用相同的全局效率指标时，该方法可以将全局效率提高2-3倍。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Journal of Computational Physics 物理-计算机：跨学科应用

CiteScore

7.60

自引率

14.60%

发文量

763

审稿时长

5.8 months

期刊介绍： Journal of Computational Physics thoroughly treats the computational aspects of physical problems, presenting techniques for the numerical solution of mathematical equations arising in all areas of physics. The journal seeks to emphasize methods that cross disciplinary boundaries. The Journal of Computational Physics also publishes short notes of 4 pages or less (including figures, tables, and references but excluding title pages). Letters to the Editor commenting on articles already published in this Journal will also be considered. Neither notes nor letters should have an abstract.