Automated generation of nuclear power plant safety information (qualitative simulation and derivation of failure symptom knowledge)

The aim of this study is to develop a general purpose information generating (GPIG) system for nuclear power plant (NPP) safety by using the artificial intelligence technique. This system makes it possible to derive safety-related knowledge necessary for the transient analysis, the risk analysis and the failure diagnosis in an unified manner, utilizing the design information database (DID) of an NPP as the common information resource. The goal of this study is to establish a basic technique for automated generation of safety information for an NPP. This technique can enhance the credibility of the derived safety information by minimizing the risk of introducing human error during the tasks such as construction of simulation code, FT generation and CCT generation