论文标题
分析时间依赖性和特征值蒙特卡洛中子传输计算的人口控制技术
Analysis of Population Control Techniques for Time-Dependent and Eigenvalue Monte Carlo Neutron Transport Calculations
论文作者
论文摘要
提出了一项对时间依赖性和特征值蒙特卡洛（MC）中子传输计算的人口控制技术（PCT）的广泛研究。我们将PCT定义为一种需要普及的人口并返回受控，公正的人口的技术。探索了基于粒子普查和种群控制的抽象的新观点，为改善概念的理解和应用铺平了道路。综述了从文献中鉴定出的五个不同的PCT：简单采样（SS），拆分 - roulette（sr），梳子（CO），修改梳子（COX）和重复 - 迪斯卡德（DD）。提出了每个PCT向人群引入多少不确定性的理论分析。提出了适用于时间依赖性和特征值MC模拟的PCTS的并行算法。通过解决时间依赖性和特征值测试问题来评估PCT的相对性能以及基于运行时和均值误差或标准偏差的相对性能。发现SR和CO同样是性能最多的技术，紧随其后的是DD。
An extensive study of population control techniques (PCTs) for time-dependent and eigenvalue Monte Carlo (MC) neutron transport calculations is presented. We define PCT as a technique that takes a censused population and returns a controlled, unbiased population. A new perspective based on an abstraction of particle census and population control is explored, paving the way to improved understanding and application of the concepts. Five distinct PCTs identified from the literature are reviewed: Simple Sampling (SS), Splitting-Roulette (SR), Combing (CO), modified Combing (COX), and Duplicate-Discard (DD). A theoretical analysis of how much uncertainty is introduced to a population by each PCT is presented. Parallel algorithms for the PCTs applicable for both time-dependent and eigenvalue MC simulations are proposed. The relative performances of the PCTs based on runtime and tally mean error or standard deviation are assessed by solving time-dependent and eigenvalue test problems. It is found that SR and CO are equally the most performant techniques, closely followed by DD.
