Abstract
Nowadays, Nuclear Power Plant (NPP) is one of the intended energy resources for the world requirement energy in future, and nuclear power plants provided 11 percent of the world’s electricity production in 2014. Meanwhile, nuclear power plant safety has always been one of the most critical issues in the world. In this paper, the nuclear power plant safety improvement using Soft Computing Techniques were analyzed. For this purpose, the support system based on Neuro-Fuzzy Diagnosis System (NFDs) method and Genetic Algorithms (GAs) approach were used. The obtained result showed that the first symptom is P3 (pressurizer pressure) and second order symptom is P2 (core coolant average temperature) in both approaches. The comparison between the NFDs method and the GAs approaches indicated that the GAs in data test results was faster than the NFDs results.
Highlights
Nuclear Power Plants (NPP) are the world’s energy resources, along with hazardous radioactive material, that incident limited to a specific location and cover an extensive range
The support system based on Neuro-Fuzzy Diagnosis System (NFDs) method and Genetic Algorithms (GAs) approach were used
The obtained result showed that the first symptom is P3 and second order symptom is P2 in both approaches
Summary
Nuclear Power Plants (NPP) are the world’s energy resources, along with hazardous radioactive material, that incident limited to a specific location and cover an extensive range. One of the most critical issues in designing, manufacturing and operating time of NPP’s is the safety system. Updating and improving the safety of nuclear power plants is one of the most critical issues in the safety of Nuclear Reactors (NR). There is an always incremental demand for operating NPPs more cost-effectively with a high capacity factor. To improve the capacity factors, safety, and prophylactic actions are suitable to deal with potential accidents in NPPs. more cost-effectively with a high capacity factor increase the needs of techniques for diagnosing and prognosis the NPPs defect. Prognostic is an essential issue in Reliability, Availability, Maintainability, and Safety (RAMS). The primary aim of a prognostic system is to demonstrate whether the Structure, System or Component (SSC) of interest can perform its function throughout its lifetime with rational assurance and, vice versa, to evaluation the Remaining Useful Life (RUL) (Al-Dahidi et al 2016)
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