Session: 15-06

Paper Number: 134863

134863 - Reliability Quantification of Passive Containment Cooling System Through Response Surface Methodology 

Abstract: 

In nuclear power plant safety research, probabilistic safety analysis (PSA) methods have been widely used, becoming an important tool for safety evaluation and safety decision-making. However, for the new generation of nuclear power plants that widely adopt passive system design, the reliability analysis of passive safety systems shows their important impact increasingly. In addition to hardware failure, functional failure of passive systems is a special and important type of failure modes, which is physical process failure caused by the uncertainty of design functions. In order to quantitatively analyze the reliability of passive systems, it is necessary to determine the key parameters that affect system operation based on the evaluation objects. At the same time, each analysis evaluates the passive system based on specific accident scenarios.

This study took the probabilistic safety analysis study of the Passive Containment Cooling System (PCCS) as an example, taking loss of coolant accident (LOCA) as passive system reliability analysis scenario. The functional criteria was based on the pressure within the containment during the long-term cooling period after the PCCS was put into use. The study determined the key operating parameters and design parameters that affect PCCS based on the above scenario and criteria. The Latin Hypercube Sampling Method (LHS) was used to determine the input parameter combination. The best estimate procedure was used to complete the uncertainty transfer calculation. The study used rank correlation coefficient to accomplish the sensitivity analysis of key parameters on system functions, sorted the impact of each parameter on the uncertainty of model output, found out the key influencing factors, and simplified the model. After reducing the number of parameters involved in the study and focusing on key parameters, the artificial neural network (ANN) method was adopted. Based on the finite best estimation procedure calculation results, the ANN obtained an accurate limit surface with respect to the functional criterion, that is, the pressure within the containment during the long-term cooling period. Then, by quantifying the uncertainty of key parameters, a large number of samples were obtained to complete the response surface calculation, and the failure probability of the system under corresponding accident conditions was obtained. By combining this failure probability with the event tree method, passive system reliability can be brought into the scope of analysis of traditional PSA. Compared with traditional probability evaluation methods, this research provided a new method to quantify the safety of passive systems, which has higher calculation efficiency and ensured calculation accuracy.

Presenting Author: Chen Shikang Xi'an Jiaotong University

Presenting Author Biography: Chen Shikang is a Ph.D. majoring in nuclear science and technology at the School of Energy and Power Engineering, Xi'an Jiaotong University.

Authors:

Chen Shikang Xi'an Jiaotong University
Chen Ronghua Xi'an Jiaotong University
Qiu Suizheng Xi'an Jiaotong University