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John A. Bernard
Nuclear Reactor Laboratory, Massachusetts Institute of Technology, 138 Albany Street Cambridge, MA 02139, USA


Factors relevant to the design and acceptance of intelligent support systems for the operation of nuclear power plants are enumerated and discussed. The central premise is that conventional expert systems which encode experiential knowledge in production rules are not a suitable vehicle for the creation of practical operator support systems. The principal difficulty is the need for real-time operation. This in turn means that intelligent support systems will have knowledge bases derived from temporally-accurate plant models, inference engines that permit revisions in die search process so as to accommodate revised or new data, and man-machine interfaces that do not require any human input. Such systems will have to be heavily instrumented and die associated knowledge bases will require a hierarchical organization so as to emulate human approaches to analysis. Arguments to support the above findings are made by first examining the needs of licensed reactor operators and then reviewing the capabilities of conventional expert systems. Factors relevant to die design of intelligent support systems are then identified. Also described are possible applications of these systems, including training, signal validation, alarm filtering, predictive displays, and human-centered machine oversight. The paper concludes with a plea for additional experimental evaluations of intelligent support technologies.

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