基于Relap5的自适应采样软件开发

Haoyin Chen, He Wang, Mohamedelmogtabh Omer Elfadni Suliman, Xinyue Wang, Qiang Zhao
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摘要

RISMC分析方法是一种确定性安全分析与概率安全分析相结合的耦合动态安全分析方法。通过蒙特卡罗采样和动态事件树方法,全面模拟了核电站在事故下的动态响应过程。为了充分反映核电站的响应过程,保证计算结果的准确性,需要对大量的输入空间参数进行采样,这将造成难以承受的时间成本。自适应采样可以通过少量前向采样计算结果预测位置输入空间参数的状态,并通过生成极限曲面对输入空间进行划分来计算失效概率,可以大大节省计算时间。在研究国内外RISMC分析工具的基础上,实现了自适应采样与RELAP5耦合计算软件的研究与开发。秦山核电站停电事故的试验实例表明,实现了通过少量采样计算故障空间概率的自适应采样函数,提高了RISMC分析计算的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of Adaptive Sampling Software Based on Relap5
The RISMC analysis method is a coupled dynamic safety analysis method that combines deterministic safety analysis and probabilistic safety analysis. It comprehensively simulates the dynamic response process of nuclear power plants under accidents through Monte Carlo sampling and dynamic event tree methods. In order to fully reflect the response process of the nuclear power plant and ensure the accuracy of the calculation results, it is necessary to sample a large number of input space parameters, which will result in unbearable time costs. Adaptive sampling can predict the state of the position input space parameters through a small number of forward sampling calculation results and divide the input space by generating limit surfaces to calculate the failure probability, which can greatly save computing time. Based on researching RISMC analysis tools at home and abroad, the research and development of adaptive sampling and RELAP5 coupling calculation software is realized. The test case of the Qinshan nuclear power plant station blackout accident shows that the adaptive sampling function of calculating failure space probability through a small amount of sampling is realized, and the efficiency of RISMC analysis and calculation is improved.
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