Screening key parameters related to passive system performance based on Analytic Hierarchy Process

被引:10
作者
Ma, Guohang [1 ]
Yu, Yu [1 ]
Huang, Xiong [1 ]
Peng, Yuan [1 ]
Ma, Nan [1 ]
Shan, Zuhua [1 ]
Niu, Fenglei [1 ]
Wang, Shengfei [1 ]
机构
[1] North China Elect Power Univ, Beijing Key Lab Pass Safety Technol Nucl Energy, Sch Nucl Sci & Technol, Beijing 102206, Peoples R China
基金
中国国家自然科学基金;
关键词
Analytic Hierarchy Process; Passive system reliability; Natural circulation; Thermal-hydraulic performance; Probabilistic density distribution; DECISION;
D O I
10.1016/j.anucene.2015.07.032
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
Passive safety system is widely used in the new generation nuclear power plant (NPP) designs such as AP1000 to improve the reactor safety benefitting from its simple construction and less request for human intervene. However, the functional failure induced by uncertainty in the system thermal hydraulic (T-H) performance becomes one of the main contributors to system operational failure since the system operates based on natural circulation, which should be considered in the system reliability evaluation. In order to improve the calculation efficiency the key parameters which significantly affect the system T-H characteristics can be screened and then be analyzed in detail. The Analytical Hierarchy Process (AHP) is one of the efficient methods to analyze the influence of the parameters on a passive system based on the experts' experience. The passive containment cooling system (PCCS) in AP1000 is one of the typical passive safety systems, nevertheless too many parameters need to be analyzed and the T-H model itself is more complicated, so the traditional AHP method should be mended to use for screening key parameters efficiently. In this paper, we adapt the improved method in hierarchy construction and experts' opinions integration, some parameters at the bottom justly in the traditional hierarchy are studied as criterion layer in improved AHP, the rationality of the method and the effect of abrupt change with the data are verified. The passive containment cooling system (PCCS) in AP1000 is evaluated as an example, and four key parameters are selected from 49 inputs. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1141 / 1151
页数:11
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