The robustness analysis of nuclear reactor control system

Author(s):  
Wang Yuanlong
1959 ◽  
Vol PGIE-8 (0) ◽  
pp. 38-45
Author(s):  
D. J. Niehaus ◽  
R. R. Hoge ◽  
A. B. Van Rennes

Author(s):  
Chenhui Wang ◽  
Wei Chen ◽  
Xiaoming Jin ◽  
Yan Liu ◽  
Chao Qi ◽  
...  

The bipolar operational amplifier is an important kind of electronic device used in the nuclear reactor control system and its radiation damage threatens the reliability of nuclear operation. In order to explore the degradation of the bipolar operational amplifier induced by reactor neutron and gamma irradiation, radiation experiments were accomplished on particular bipolar operational amplifiers OP07 manufactured by Texas Instruments and Analog Devices. The amplifiers were irradiated in three different environments respectively: individual neutrons, individual gamma rays and mixed irradiation of reactor neutrons and gamma rays simultaneously. The results indicate that for both types of bipolar operational amplifiers, the degradations of the input bias current and the input offset voltage induced by the mixed irradiation of reactor neutrons and gamma rays simultaneously are notably more severe than the simple sum of neutron and gamma degradations measured individually. The mixed irradiation of reactor neutron and gamma rays simultaneously leads to degradation enhancement compared to individual ones and induce ionizing/displacement synergistic effects in the amplifiers. Enough attention should be paid to the degradation enhancement induced by the mixed irradiation for devices may exhibit unexpected failure during reactor operation and accelerate the aging of the nuclear reactor control system.


2021 ◽  
Vol 2113 (1) ◽  
pp. 012030
Author(s):  
Jing Li ◽  
Yanyang Liu ◽  
Xianguo Qing ◽  
Kai Xiao ◽  
Ying Zhang ◽  
...  

Abstract The nuclear reactor control system plays a crucial role in the operation of nuclear power plants. The coordinated control of power control and steam generator level control has become one of the most important control problems in these systems. In this paper, we propose a mathematical model of the coordinated control system, and then transform it into a reinforcement learning model and develop a deep reinforcement learning control algorithm so-called DDPG algorithm to solve the problem. Through simulation experiments, our proposed algorithm has shown an extremely remarkable control performance.


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