Data-driven maintenance priority and resilience evaluation of performance loss in a main coolant system

Dui, Hongyan and Xu, Zhe and Chen, Liwei and Xing, Liudong and Liu, Bin (2022) Data-driven maintenance priority and resilience evaluation of performance loss in a main coolant system. Mathematics, 10 (4). 563. ISSN 2227-7390 (https://doi.org/10.3390/math10040563)

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Abstract

The main coolant system (MCS) plays a vital role in the stability and reliability of a nuclear power plant. However, human errors and natural disasters may cause some reactor coolant system components to fail, resulting in severe consequences such as nuclear leakage. Therefore, it is crucial to perform a resilience analysis of the MCS, to effectively reduce and prevent losses. In this paper, a resilience importance measure (RIM) for performance loss is proposed to evaluate the performance of the MCS. Specifically, a loss importance measure (LIM) is first proposed to indicate the component maintenance priority of the MCS under different failure conditions. Based on the LIM, RIMs for single component failure and multiple component failures were developed to measure the recovery efficiency of the system performance. Finally, a case study was conducted to demonstrate the proposed resilience measure for system reliability. Results provide a valuable reference for increasing the system security of the MCS and choosing the appropriate total maintenance cost.

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