摘要
为了实现对反应堆三维空间内详细功率分布和物理、热工等安全状态参数的实时在线监测,基于反应性跟踪与预测的动态数据驱动模型,中国核动力研究设计院和海南核电有限公司共同研发了反应性辅助决策系统RAINBOW—PET.本文对反应性辅助决策系统的设计实现等进行了研究,包括系统总体架构设计、数据库方案、多任务支持、可靠性设计等,在此基础上完成了反应性辅助决策系统的编码实现.目前,该系统已成功应用于海南昌江1、2号机组的在线监测,为反应堆运行人员进行堆芯控制提供参考.
Abstract
In order to achieve real-time online monitoring of detailed power distribution,and physical,thermal and other safety parameters in the three-dimensional space of the reactor,a dynamic data-driven model based on reactivity tracking and prediction has been jointly developed by Nuclear Power Institute of China and Hainan Nuclear Power Co.,Ltd.The reactivity assisted decision support system,known as RAINBOW-PET,has been developed.This article studies the design and implementation of the reactivity assisted decision support system,including the overall system architecture design,database scheme,multi-task support,reliability design,etc.Base on this,the coding implementation of the reactivity assisted decision support system has been completed.Currently,the system has been successfully applied to online monitoring of Unit 1&2 Changjiang NPP,providing reference for core control by reactor operators.
NETL
NSTL
万方数据