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A time-dependent diffusion model of a three-dimensional, multi-energy group kinetic analysis program STAND has been verified by using neutron detector responses in the subcritical condition. The responses were obtained from a BWR start-up examination. STAND is based on a polynomial nodal expansion method and an improved quasi-static model. It can simulate transients and reactivity accidents of boiling water reactors in critical and subcritical conditions, and works efficiently on a vector computer.This paper describes the core neutronic model including treatment of external neutron sources and verification results tracing about a 10-min control rod operation during the BWR start-up examination. Calculated transient detector responses had good agreement with experimental ones. The CPU time necessary to calculate 1 s of behavior for a full core ( 460 radial meshes x 30 axial meshes) with three energy groups was about 13 s on the HITACHI S-3800 vector computer when the shape function time step was set to 0.1-0.2 s.

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When accident events are caused by a large-scale natural disaster, conditions beyond those at the plant site may affect the accident. As well, quick diagnosis and recognition of damaged equipment are necessary. We have been developing inherently safe technologies for boiling water reactor (BWR) plants in response to these. An operation support system for plant accident events is one of these technologies. Our operation support system identifies accident events and predicts the progression of plant behavior. The system consists of three main functions: sensor integrity diagnosis, accident event identification, and plant simulation functions. The sensor integrity diagnosis function diagnoses whether sensor signals have maintained their integrity by correlating redundant sensors with the plant design information. The accident event identification function extracts a few of candidate accident events using alarm and normal sensor signals received by the sensor integrity diagnosis function. The scale and position of the accident event are determined by comparing plant simulation results with normal sensor signals. The plant simulation function uses a detailed three-dimensional model of the nuclear reactor and plant. This simulation can predict future plant behavior on the basis of identified accident events. This proposed operation support system provides available results of accident event identification and plant condition prediction to plant operators. This system will reduce the occurrence of false identifications of accident events and human errors of operators.

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