Quantitative Risk Analysis of Disconnect Operations in a Marine Nuclear Power Platform Using Fuzzy Bayesian Network

Abstract

Marine nuclear power platforms can continuously supply electricity and fresh water for marine resource exploration and surrounding islands. China’s first marine nuclear power platform uses a soft yoke multi-joint connect mode as the mooring positioning device. When the marine nuclear power platform needs repair, maintenance, nuclear fuel replacement, or a different operation area, a mooring disconnect operation must be carried out. The traditional mooring disconnect process consists of four stages: cable limiting, yoke offloading, yoke dropping, and equipment recovery stages. The entire disconnect process is a high-risk nuclear-related operation that could result in a collision accident between the yoke and hull structure, resulting in nuclear fuel leaks and casualties. Therefore, it is necessary to evaluate the risk factors of the disconnect process and to assess the risk level together with the consequence of each risk. In this paper, a quantitative risk analysis of nuclear power platform disconnect operations is carried out based on a fuzzy Bayesian network approach for risk events in each stage of the disconnect operations. Based on the forward fuzzy Bayesian inference, the criticality of each risk event to the disconnect process is evaluated and compared. The main risk factors that may cause a disconnect accident are then determined based on the reverse Bayesian inference rule. The results indicate that human error is the most likely factor leading to the failure of the disconnect process, requiring strict control of personnel operation procedures during this process. The yoke colliding with the hull and stern antifriction chain-breaking are the most significant hazards caused by the disconnect failing. Thus, the distance between the yoke and hull, stern tug tensile force, and maintenance of the antifriction chain should receive particular attention.