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Emergency Procedures Tracking System for Nuclear Power Plants
Abstract This paper describes a computer-based emergency operating procedures (EOP) tracking system for nuclear power plant applications that is based on artificial intelligence technology. The project to develop and prove a decision support system for emergency procedure tracking was co-sponsored by the Electric Power Research Institute and the Taiwan Power Company for application to the Kuosheng BWR nuclear power plant. The software was developed by Nuclear Software Services of Los Gatos, CA and the system is being integrated into the overall Safety Parameter Display System (SPDS) developed by the General Electric Company of San Jose, CA. Because the BWR emergency procedures are symptom based, it is possible to be in many places in the procedures concurrently, a situation which may require the operating crew to take a number of different actions to control the plant. The EOP tracking system provides the capability to analyze and evaluate realtime plant conditions relative to the written operating procedures used during emergencies. As a result of the online logic processing, pointers or cues back to the written procedures are provided to the operator for guidance. Key design requirements, such as integration with the SPDS system, “realtime” operation, minimum computer resources, and verifiable and maintainable logic, were identified and evaluated. It was determined that these requirements were best met by using artificial intelligence technologies that are better suited than the conventional software technologies to solve this type of problem. As a result, a production rule, expert system was developed which includes a rule-based knowledge base and inference engine written in the “C” language for use on a DEC VAX computer containing the SPDS database. The system is to be evaluated in tests at the Kuosheng simulator and, when accepted, will be installed at the Kuosheng nuclear power plant in Taiwan, Republic of China.
Emergency Procedures Tracking System for Nuclear Power Plants
Abstract This paper describes a computer-based emergency operating procedures (EOP) tracking system for nuclear power plant applications that is based on artificial intelligence technology. The project to develop and prove a decision support system for emergency procedure tracking was co-sponsored by the Electric Power Research Institute and the Taiwan Power Company for application to the Kuosheng BWR nuclear power plant. The software was developed by Nuclear Software Services of Los Gatos, CA and the system is being integrated into the overall Safety Parameter Display System (SPDS) developed by the General Electric Company of San Jose, CA. Because the BWR emergency procedures are symptom based, it is possible to be in many places in the procedures concurrently, a situation which may require the operating crew to take a number of different actions to control the plant. The EOP tracking system provides the capability to analyze and evaluate realtime plant conditions relative to the written operating procedures used during emergencies. As a result of the online logic processing, pointers or cues back to the written procedures are provided to the operator for guidance. Key design requirements, such as integration with the SPDS system, “realtime” operation, minimum computer resources, and verifiable and maintainable logic, were identified and evaluated. It was determined that these requirements were best met by using artificial intelligence technologies that are better suited than the conventional software technologies to solve this type of problem. As a result, a production rule, expert system was developed which includes a rule-based knowledge base and inference engine written in the “C” language for use on a DEC VAX computer containing the SPDS database. The system is to be evaluated in tests at the Kuosheng simulator and, when accepted, will be installed at the Kuosheng nuclear power plant in Taiwan, Republic of China.
Emergency Procedures Tracking System for Nuclear Power Plants
Petrick, William (author) / Ng, Karen (author) / Stuart, Chuck (author) / Shen, David (author) / Cain, David (author) / Sun, Bill (author) / Christensen, Carl (author)
1988-01-01
8 pages
Article/Chapter (Book)
Electronic Resource
English
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