[PDF] Autonomous Nuclear Power Plants With Artificial Intelligence eBook

Author : Jonghyun Kim
Publisher : Springer Nature
Page : 280 pages
File Size : 24,85 MB
Release : 2023-02-20
Category : Technology & Engineering
ISBN : 3031223861

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This book introduces novel approaches and practical examples of autonomous nuclear power plants that minimize operator intervention. Autonomous nuclear power plants with artificial intelligence presents a framework to enable nuclear power plants to autonomously operate and introduces artificial intelligence (AI) techniques to implement its functions. Although nuclear power plants are already highly automated to reduce human errors and guarantee the reliability of system operations, the term “autonomous” is still not popular because AI techniques are regarded as less proven technologies. However, the use of AI techniques and the autonomous operation seems unavoidable because of their great advantages, especially, in advanced reactors and small modular reactors. The book includes the following topics: Monitoring, diagnosis, and prediction. Intelligent control. Operator support systems. Operator-autonomous system interaction. Integration into the autonomous operation system. This book will provides useful information for researchers and students who are interested in applying AI techniques in the fields of nuclear as well as other industries. This book covers broad practical applications of AI techniques from the classical fault diagnosis to more recent autonomous control. In addition, specific techniques and modelling examples are expected to be very informative to the beginners in the AI studies.

Author :
Publisher :
Page : 28 pages
File Size : 11,13 MB
Release : 1989
Category :
ISBN :

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In the summer of 1988, the Department of Nuclear Engineering (NE) at the University of Tennessee (UT) in Knoxville was selected to carry out a research program in ''Enhancing the Operation of Nuclear Power plants through the use of Artificial Intelligence, This program is sponsored by the Department of Energy's Office of Energy Research under 10CFR605 for Nuclear Engineering Research. The objective of the research is to advance the state-of-the-art of nuclear power plant control, safety, management, and instrumentation systems through the use of artificial intelligence (AI) techniques, including both expert systems and neural networks. The emphasis will be placed on methods that can be implemented on a rapid or real-time basis. A second, but equally important, objective is to build a broadly based critical mass of expertise in the artificial intelligence, field that can be brought to bear on the technology of nuclear power plants. Both of these goals are being met. This overview and the attached technical reports describe the work that is being carried out. Although in some cases, the scope of the work differs somewhat from the specific tasks described in the original proposal, all activities are clearly within the overall scope of the contract.

Author :
Publisher :
Page : 28 pages
File Size : 43,3 MB
Release : 1989
Category :
ISBN :

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In the summer of 1988, the Department of Nuclear Engineering (NE) at the University of Tennessee (UT) in Knoxville was selected to carry out a research program in Enhancing the Operation of Nuclear Power plants through the use of Artificial Intelligence, This program is sponsored by the Department of Energy's Office of Energy Research under 10CFR605 for Nuclear Engineering Research. The objective of the research is to advance the state-of-the-art of nuclear power plant control, safety, management, and instrumentation systems through the use of artificial intelligence (AI) techniques, including both expert systems and neural networks. The emphasis will be placed on methods that can be implemented on a rapid or real-time basis. A second, but equally important, objective is to build a broadly based critical mass of expertise in the artificial intelligence, field that can be brought to bear on the technology of nuclear power plants. Both of these goals are being met. This overview and the attached technical reports describe the work that is being carried out. Although in some cases, the scope of the work differs somewhat from the specific tasks described in the original proposal, all activities are clearly within the overall scope of the contract.

Author : Xiangyi Chen
Publisher :
Page : 0 pages
File Size : 22,69 MB
Release : 2022
Category :
ISBN :

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By 2050, the United States is expected to achieve carbon neutralization, which would require nuclear energy to play a key role in compensating for the high penetration of renewable energy in the future energy mix. Specifically, nuclear energy is expected to be responsible for electricity dispatch to maintain the reliability and resilience of large and small grids. To face this new challenge, nuclear power plants in the future should be designed for high maneuverability, improved resilience, and autonomous-control compatibility. In this context, intelligent techniques, such as automated planning & decision-making, self-prognosis & adaptation, and fault tolerance, need to be developed. To this end, this dissertation concentrates on two closely related areas regarding resilient operation and autonomous control of nuclear power plants, which are listed below: The first topic concentrates on early anomaly detection, which is necessary for future condition-based maintenance and resilient operation of nuclear power plants. The second topic is fault-tolerant control of future-generation nuclear power plants for superbly safe and reliable operations. This means that the nuclear power plant can undergo much fewer plant trips and yet not compromise safety under both anticipated and unanticipated hazards. The work in this dissertation will balance the advantage of the developed technology of nuclear power generation and the benefit of the state-of-the-art in artificial intelligence (AI). This will be achieved by retaining most of the conventional safety requirements of the plant and, at the same time, incorporating state-of-the-art technologies in AI. The innovation in this dissertation is expected to help nuclear power plants to fulfill their new role in mixed-grid power systems.