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Title: Knowledge base expert system control of spatial xenon oscillations in pressurized water reactors

Miscellaneous ·
OSTI ID:7269997

Nuclear reactor operators are required to pay special attention to spatial xenon oscillations during the load-follow operation of pressurized water reactors. They are expected to observe the axial offset of the core, and to estimate the correct time and amount of necessary control action based on heuristic rules given in axial xenon oscillations are knowledge intensive, and heuristic in nature. An expert system, ACES (Axial offset Control using Expert Systems) is developed to implement a heuristic constant axial offset control procedure to aid reactor operators in increasing the plant reliability by reducing the human error component of the failure probability. ACES is written in a production system language, OPS5, based on the forward chaining algorithm. It samples reactor data with a certain time interval in terms of measurable parameters, such as the power, period, and the axial offset of the core. It then processes the core status utilizing a set of equations which are used in a back of the envelope calculations by domain experts. Heuristic rules of ACES identify the control variable to be used among the full and part length control rods and boron concentration, while a knowledge base is used to determine the amount of control. ACES is designed as a set of generic rules to avoid reducing the system into a set of patterns. Instead ACES evaluates the system, determines the necessary corrective actions in terms of reactivity insertion, and provides this reactivity insertion using the control variables. The amount of control action is determined using a knowledge base which consists of the differential rod worth curves, and the boron reactivity worth of a given reactor. Having the reactor dependent parameters in its knowledge base, ACES is applicable to an arbitrary reactor for axial offset control purposes.

Research Organization:
Iowa State Univ. of Science and Technology, Ames, IA (United States)
OSTI ID:
7269997
Resource Relation:
Other Information: Thesis (Ph.D.)
Country of Publication:
United States
Language:
English