Power Plant Surveillance and Diagnostics : Applied Research With Artificial Intelligence. This item is unavailable.Power Plant Surveillance and Diagnostics : Applied Research With Artificial Intelligence

In little more than a decade, the availability of nuclear power plants in the United States and most European and Pacific Rim countries has increased dramatically­ from around 60% to about 90%. Such improvement is equivalent to adding approximately 30,000 MW e of new generating capacity in this period in the United States and perhaps an equal amount elsewhere. Some of this improvement has been due to longer fuel cycles-increases from 12 months to 18 or 24 months, but the major gains have been due to on-line maintenance and improved operation and planning by the utilities, accomplished primarily by training of plant operators and support personnel. However, there are emerging indications that the benefits of training are asymptotically approaching the limit beyond which it cannot improve availability and that plant personnel errors may also be approaching a comparable lower limit. Indeed, further improvement appears to be dependent upon the effective introduction and use of plant operational support systems. The Halden Reactor Project (HRP) historically has focused on plant operational support system, i. e. , such tools as COPMA (Computerized OPeration MAnuals), PEANO (Process Evaluation and Analysis by Neural Operators), TEMPO (ThErMal Performance and Optimization), PLASMA (PLAnt Safety Monitoring and Assessment system), and others.

This edited book is directed primarily to the discussion of the most recent developments and on-going research related to all areas pertaining to plant surveillance and diagnosis. The secondary aim of this book is to identify the successful applications of already well-settled methodological tools in the field. It will highlight advantages of intelligent systems, AI techniques, and integration of soft computing tools and traditional tools, for a better service in all aspects related to power plant surveillance and diagnostics. It also reports recent research results and provides a state of the art on AI in power plant surveillance and diagnostics. The book especially focuses on theoretical and analytical solutions to the problems of real interest in AI techniques, possibly combined with other traditional computing tools.