Autonomous Nuclear Power Plants with Artificial Intelligence

2023
ISBN: 978-3-031-22385-3
Verlag: Springer International Publishing

Buch, Englisch, Band 94, 269 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 652 g

Reihe: Lecture Notes in Energy

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.

Integrationinto 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.

Zielgruppe

Research

Autoren/Hrsg.

Kim, Jonghyun

Seong, Poong Hyun

Lee, Seungjun

Fachgebiete

• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Energie- & Versorgungswirtschaft Kernenergieindustrie
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Technische Wissenschaften Energietechnik | Elektrotechnik Atomenergietechnik

Inhaltsverzeichnis

Introduction.- Artificial Intelligence and Methods.- Signal Validation.- Diagnosis.- Prediction.

Über Autor(innen)

Prof. Jonghyun Kim is currently an associate professor at the department of nuclear engineering in Chosun University, South Korea. He received B.S., M.S., and Ph.D at the department of nuclear and quantum engineering, KAIST. His research areas are human factors engineering, human reliability engineering, and AI applications in nuclear power plants. In those areas, he published more than 40 SCIE journal articles and more than 100 conference papers.
Prof. Seung Jun Lee is currently an associate professor at the department of nuclear engineering in UNIST, South Korea. He received B.S., M.S., and Ph.D at the department of nuclear and quantum engineering, KAIST. His research areas are probabilistic safety assessment, human reliability engineering, and AI applications in nuclear power plants. In those areas, he published more than 50 SCIE journal articles and more than 100 conference papers.

Prof. Poong Hyun Seong

Professor Poong Hyun Seong is a professor emeritus at the department of nuclear and quantum engineering in KAIST. He received his B.S from Seoul National University, Seoul, Korea and M.S and Ph.D from M.I.T, Cambridge, MA in the USA, all in nuclear engineering. His research areas are human factors engineering, nuclear instrumentation and control system development, nuclear power plant cyber security, and AI application in nuclear power plants. He has published more than 150 SCIE journal papers and 200 international conference proceedings.

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