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Development of Inherently Safe Technologies for Large Scale BWRs: (5) Operation Support System for Plant Accidents

[+] Author Affiliations
Masaki Kanada, Yoshihiko Ishii, Setsuo Arita, Kenichi Katono

Hitachi, Ltd., Hitachi, Ibaraki, Japan

Ryota Kamoshida, Tadaaki Ishikawa

Hitachi, Ltd., Kokubunji, Tokyo, Japan

Paper No. ICONE22-31104, pp. V003T06A049; 6 pages
  • 2014 22nd International Conference on Nuclear Engineering
  • Volume 3: Next Generation Reactors and Advanced Reactors; Nuclear Safety and Security
  • Prague, Czech Republic, July 7–11, 2014
  • Conference Sponsors: Nuclear Engineering Division
  • ISBN: 978-0-7918-4593-6
  • Copyright © 2014 by ASME


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.

Copyright © 2014 by ASME



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