Application of Artificial Intelligence in Detection and Mitigation of Human Factor Errors in Nuclear Power Plants: A Review

Human factors and ergonomics have played an essential role in increasing the safety and performance of operators in the nuclear energy industry. In this critical review, we examine how artificial intelligence (AI) technologies can be leveraged to mitigate human errors, thereby improving the safety and performance of operators in nuclear power plants (NPPs). First, we discuss the various causes of human errors in NPPs. Next, we examine the ways in which AI has been introduced to and incorporated into different types of operator support systems to mitigate these human errors. We specifically examine (1) operator support systems, including decision support systems, (2) sensor fault detection systems, (3) operation validation systems, (4) operator monitoring systems, (5) autonomous control systems, (6) predictive maintenance systems, (7) automated text analysis systems, and (8) safety assessment systems. Finally, we provide some of the shortcomings of the existing AI technologies and discuss the challenges still ahead for their further adoption and implementation to provide future research directions

Framework to Develop Artificial Intelligent Autonomous Operating System for Nuclear Power Plants

As artificial intelligent (AI) technology has been dramatically developed, various industries have been challenged to apply it. In a view of nuclear power plants (NPP), it seems that AI technology applies to NPPs at the last because NPPs are required the most stringent level of regulatory guideline for safety. To overcome it, AI technology should be applied incrementally into the NPPs rather than all at once. According to the unintended shutdown records during startup and shutdown operation from 1997 to 2017 in Korea, it is reported that human errors accounts for 40% of the total. This is because operators feel heavy burden to monitor hundreds of parameters for a long time of operating time. Also, there are lots of startup and shutdown operating history that can be used for correcting the data from the NPP simulator. Therefore, this work proposes a framework to develop AI automatic operating system for startup and shutdown operations of NPPs. Operating procedures of startup and shutdown operations are categorized. In addition, AI technologies will be introduced to find out the most suitable learning algorithm. It is expected that economic loss from human error during startup and shutdown operation will be reduced as AI system developed