基于键能算法的AHWR堆芯探测器位置优化

Anupreethi Balajiranganathan, Anurag Gupta, Umasankari Kannan, A. Tiwari
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引用次数: 0

摘要

对先进重水堆堆芯内探测器布置优化问题进行了研究。AHWR的堆芯探测器单元具有轴向分布的自供电中子探测器(SPND),其测量结果作为在线通量测绘系统(OFMS)的输入,用于监测三维中子通量分布。要求将这些堆芯内探测器放置在最佳位置,以获取有关反应堆的最大信息,同时将其数量保持在最低限度。本文试图通过应用键能算法(BEA)来优化SPND的放置,BEA是一种基于相关性对SPND进行分组的聚类技术。这是基于将强相关的SPND分组为块并从每个块中选择一个SPND作为最优位置的概念。最优spnd之间的不相关性越高,有关反应堆实际配置的独立信息检索越高。从这项工作可以推断,SPND的数量和位置高度依赖于SPND位置的初始集合和相关阈值。可以看出,随着相关阈值的增加,最优位置的数量也在增加。利用不同的通量映射算法(FMA)对不同的运行反应堆配置进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of In-Core Detector Locations in AHWR Using Bond Energy Algorithm
A solution to optimization of in-core detectors placement for Advanced Heavy Water Reactor (AHWR) has been attempted. AHWR houses in-core detector units with Self-Powered Neutron Detectors (SPND) distributed axially and their measurement serves as an input to Online Flux Mapping System (OFMS) to monitor the three-dimensional neutron flux distribution. There is a requirement of placing these in-core detectors at optimum locations to retrieve maximum information about the reactor while keeping their number to the minimum. This paper attempts to optimize SPND placement through the application of Bond Energy Algorithm (BEA), a clustering technique which groups the SPNDs based on correlation. This works on the concept of grouping strongly correlated SPNDs into blocks and choosing one SPND from each block as the optimal location. The higher the uncorrelation among optimal SPNDs, the higher the independent information retrieved about the actual configuration of the reactor. It can be inferred from this work that the number and location of SPNDs are highly dependent on the initial set of SPND locations and the correlation threshold. It can be seen that as the correlation threshold increases, the number of optimal locations increases. The obtained optimal locations have been validated for various operational reactor configurations using different Flux Mapping Algorithms (FMA).
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