Session: 12-02 Risk Assessments and Management - Session 2

Paper Number: 134510

134510 - Analysis of Mobile Equipment Configuration for Severe Accidents in Nuclear Power Plants Based on Multi-Unit Psa 

Abstract: 

The mobile equipment in nuclear power plants includes emergency diesel generators, mobile pumps, fire trucks, mobile hydrogen abatement units, etc., which play an important role in preventing and mitigating multi-unit severe accidents. Multi-unit severe accidents are important factors affecting the safety of multi-unit nuclear power plants, and the analysis of multi-unit severe accidents plays a key role in the safety analysis against severe external disasters and external damages.

 

Like most of the nuclear power plants around the world, China's nuclear power plants are mostly composed of multiple units, and the multi-unit safety analysis is of great significance for the safety improvement of all nuclear power plants. Meanwhile, the configuration method of mobile equipment is diverse in different nuclear power plants, and there is a lack of mature configuration evaluation methods and systems in the industry.

 

Probabilistic safety assessment (PSA) technology, after years of domestic and international application experience, has been proven to be an effective technology capable of evaluating the safety performance of power plants from a probabilistic point of view and discovering the safety weaknesses of power plants from a mathematical point of view. Multi-unit probabilistic safety assessment (MUPSA) technology is a research direction in its infancy, and the study of MUPSA helps to integrate the existing technologies such as PSA for level-one internal events, PSA for level-one external events, and level-two PSA, and helps to promote the application of risk-informed technology as a whole.

 

Using MUPSA technology to evaluate and analyze the configuration of mobile equipment in multi-unit nuclear power plants can provide reliable quantitative parameters, and quantitatively evaluate the configuration of mobile equipment in multi-unit nuclear power plants through the analysis of CDF/LERF. The quantitative analysis is combined with other qualitative analyses to provide a mobile equipment configuration scheme and configuration recommendations for a particular multi-unit site.

 

This paper develops a modeling methodology to build a MUPSA model for level-one internal events based on existing SUPSA models, and applies it to the analysis of severe accident mobile equipment configurations at a multi-unit nuclear power site. In this paper, Tianwan nuclear power plant, which has six operating units, is taken as a pilot plant, and the Fukushima nuclear accident in Japan is taken as a hypothetical accident scenario, and the working conditions of simultaneous loss of off-site power supply and simultaneous loss of heat sinks of multiple units are selected as hypothetical accident scenarios to evaluate the severe accident response capability of multiple units. By utilizing the MUPSA model for sensitivity analysis of mobile equipment, recommendations for the configuration of mobile equipment for multi-unit severe accidents are given to support the decision-making.

 

The configuration evaluation method proposed in this paper can effectively solve the pain point of the lack of sufficient theoretical analysis basis and the lack of systematic and effective method when configuring mobile equipment in nuclear power plants. It can help power plants to configure mobile devices according to their own risk conditions, avoid over- or under-allocation, and improve overall safety and save costs for power plants. The method is basically applicable to all operating reactor types and all nuclear power bases, which has good universality and is targeted and specialized for the specific analysis of each nuclear power plants.

Presenting Author: Dalin Liu Nuclear Power Operations Research Institute (NPRI)

Presenting Author Biography: Institution: Nuclear Power Operations Research Institute (NPRI).
Main research areas: probabilistic safety analysis and application of risk-informed techniques.

Authors:

Dalin Liu Nuclear Power Operations Research Institute (NPRI)
Jiangguo Wang Nuclear Power Operations Research Institute (NPRI)
Zhen Yan Nuclear Power Operations Research Institute (NPRI)
Shuting Wang Nuclear Power Operations Research Institute (NPRI)
Ling Zhao Nuclear Power Operations Research Institute (NPRI)