Fuzzy logic and artificial neural networks for nuclear power plant applications
Conference
·
· Proceedings of the American Power Conference; (United States)
OSTI ID:7308810
- Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering
This paper discusses the feasibility of applying fuzzy logic and neural networks to plant-wide monitoring, diagnostics, and control problems. Different data sets are gathered from several sources including two commercial Pressurized Water Reactors (PWR), the Experimental Breeder Reactor-II (EBR-II), and the conceptual design of Modular Liquid-Metal Reactor (PRISM). These data sets are used to illustrate applications to operating processes, and to PRISM design. The results show that the artificial intelligence approach to a number of operational tasks can considerably improve the safety and availability of nuclear power generation.
- OSTI ID:
- 7308810
- Report Number(s):
- CONF-920432--
- Conference Information:
- Journal Name: Proceedings of the American Power Conference; (United States) Journal Volume: 54:2
- Country of Publication:
- United States
- Language:
- English
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