期刊论文

Prediction of Core Physical Parameter Based on Decision Tree

Xie, Jinsen(xiejinsen@139.com)

中文

原子能科学技术

1000-6931

2020

54

2

296-301

10.7538/yzk.2019.youxian.0102

国防科技工业核动力技术创新中心研究课题资助项目(HDLCXZX-2018-ZH-031)。

本校为第一机构

反应堆堆芯核设计涉及大量方案的搜索与详细计算,缩短方案搜索时间有利于提高核设计效率.数据挖掘技术通过对大量数据进行学习与模式识别,可实现核设计方案物理参数的快速预测,更快地筛选出可行的备选堆芯方案.本文基于数据挖掘的决策树4种算法:C4.5、RepTree、Random Forest及Random Tree,在计算时以燃料富集度、含可燃毒物燃料棒数量及含量作为自变量,以寿期内keff不均匀系数偏差(KUCD)、径向功率不均匀系数偏差(RPNCD)、径向中子通量不均匀系数偏差(RFNCD)、堆芯寿期(CL)作为目标函数,构成目标函数符合度(CPF),利用大量已知核设计参数的组件及堆芯设计方案作为数据挖掘训练集,构建数据挖掘模...

The reactor core design involves search and detailed calculation of a large number of schemes. Shortening the search time is beneficial to improve the efficiency of nuclear design. Through learning and pattern recognition of large data, data mining technology can realize rapid prediction of physical parameters for nuclear design schemes, and fast screening of feasible alternative core schemes. Four decision tree algorithms were used in this paper, C4.5, RepTree, Random Forest and Random Tree, respectively. Fuel enrichment, and the number of fue...