Empirical modeling of nuclear power plants using neural networks

Conference · Tue Jan 01 00:00:00 EST 1991 · Transactions of the American Nuclear Society; (United States)

OSTI ID:5855251

Parlos, A G; Atiya, A; Chong, K T ^[1]

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1. Texas A and M, College Station (United States)

A summary of a procedure for nonlinear identification of process dynamics encountered in nuclear power plant components is presented in this paper using artificial neural systems. A hybrid feedforward/feedback neural network, namely, a recurrent multilayer perceptron, is used as the nonlinear structure for system identification. In the overall identification process, the feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of time-dependent system nonlinearities. The standard backpropagation learning algorithm is modified and is used to train the proposed hybrid network in a supervised manner. The performance of recurrent multilayer perceptron networks in identifying process dynamics is investigated via the case study of a U-tube steam generator. The nonlinear response of a representative steam generator is predicted using a neural network and is compared to the response obtained from a sophisticated physical model during both high- and low-power operation. The transient responses compare well, though further research is warranted for training and testing of recurrent neural networks during more severe operational transients and accident scenarios.

• OSTI ID: 5855251
• Report Number(s): CONF-910603-; CODEN: TANSA
• Journal Information: Transactions of the American Nuclear Society; (United States), Vol. 63; Conference: Annual meeting of the American Nuclear Society (ANS), Orlando, FL (United States), 2-6 Jun 1991; ISSN 0003-018X
• Country of Publication: United States
• Language: English

Related Subjects

22 GENERAL STUDIES OF NUCLEAR REACTORS
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
NUCLEAR POWER PLANTS
REACTOR KINETICS
NEURAL NETWORKS
ARTIFICIAL INTELLIGENCE
FEEDBACK
KNOWLEDGE BASE
NONLINEAR PROBLEMS
REACTOR MONITORING SYSTEMS
STEAM GENERATORS
TIME DEPENDENCE
TRANSIENTS
BOILERS
KINETICS
NUCLEAR FACILITIES
POWER PLANTS
THERMAL POWER PLANTS
VAPOR GENERATORS
220400* - Nuclear Reactor Technology- Control Systems
220100 - Nuclear Reactor Technology- Theory & Calculation
990200 - Mathematics & Computers