Neural networks and their potential application to nuclear power plants
- Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering
A network of artificial neurons, usually called an artificial neural network is a data processing system consisting of a number of highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain. Hence, neural networks are often capable of doing things which humans or animals do well but which conventional computers often do poorly. Neural networks exhibit characteristics and capabilities not provided by any other technology. Neural networks may be designed so as to classify an input pattern as one of several predefined types or to create, as needed, categories or classes of system states which can be interpreted by a human operator. Neural networks have the ability to recognize patterns, even when the information comprising these patterns is noisy, sparse, or incomplete. Thus, systems of artificial neural networks show great promise for use in environments in which robust, fault-tolerant pattern recognition is necessary in a real-time mode, and in which the incoming data may be distorted or noisy. The application of neural networks, a rapidly evolving technology used extensively in defense applications, alone or in conjunction with other advanced technologies, to some of the problems of operating nuclear power plants has the potential to enhance the safety, reliability and operability of nuclear power plants. The potential applications of neural networking include, but are not limited to diagnosing specific abnormal conditions, identification of nonlinear dynamics and transients, detection of the change of mode of operation, control of temperature and pressure during start-up, signal validation, plant-wide monitoring using autoassociative neural networks, monitoring of check valves, modeling of the plant thermodynamics, emulation of core reload calculations, analysis of temporal sequences in NRC`s ``licensee event reports,`` and monitoring of plant parameters.
- Research Organization:
- Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering
- Sponsoring Organization:
- USDOE, Washington, DC (United States); Electric Power Research Inst., Palo Alto, CA (United States)
- DOE Contract Number:
- FG07-88ER12824; AC05-84OR21400
- OSTI ID:
- 10104395
- Report Number(s):
- CONF-9109110-16; ON: DE93003559
- Resource Relation:
- Conference: International conference on frontiers in innovative computing for the nuclear industry,Jackson, WY (United States),15-18 Sep 1991; Other Information: PBD: [1991]
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
NEURAL NETWORKS
NUCLEAR POWER PLANTS
REACTOR CONTROL SYSTEMS
LEARNING
DIAGNOSTIC USES
REACTOR MONITORING SYSTEMS
VALVES
220900
220400
990200
REACTOR SAFETY
CONTROL SYSTEMS
MATHEMATICS AND COMPUTERS