Risk Analysis of Nuclear Power Plant (NPP) Operations by Artificial Intelligence (AI) in Robot

Abstract

The cognitive architecture is investigated for the management in the nuclear power plant (NPP) site in which artificial intelligence (AI) is incorporated. The normal operation and accident are modeled for the simulations incorporated with the robot intelligence algorithm, where random sampling plays a major role in the quantifications. The Accident Dynamics Simulator paired with the Information, Decision, and Action in a Crew context cognitive model (ADS-IDAC) and the Cognitive skill for plant operations are calculated for the study. Simulations show the ADS-IDAC modeling and simulation results of two peaks in 21st and 21.75th sequences. Otherwise, there are several peaks with one big peak in 13.25th sequences. The big peak is in the 25.75th sequence in Mental State, Circumstances, and Identity. The accident situation is related to actions through the cognitive systems. In the operation case, a variety of signals are shown in which the operations of the plant could show several kinds of actions to be done by the robot. The figure shows the procedure of nuclear cognitive architecture. A nuclear accident is investigated by the designed modeling in which the actions of robots are quantified by the artificial brain. The developed algorithm of this paper could be applied to the other kinds of complex industrial systems like airplane operations and safety systems, spacecraft systems, and so on.