Research Topic

Artificial Intelligence Applications in Nuclear Energy

About this Research Topic

As a highly complex man-machine-network integration system, the development, construction and operation of nuclear power plant are still facing many obstacles and risks. Firstly, plant instruments and equipment may fail during operation, which will affect the performance and safety of nuclear power plant. Secondly, although nuclear power plants have been digitalized after decades of development, most of them still adopt traditional and inefficient operation and control methods. Finally, due to the above reasons and high control requirements, human operators are under great pressure.

In the past decades, artificial intelligence (AI), especially methods related to deep learning, has made great progress and has been widely used in computer vision, automatic control and other fields. At present, many researchers begin to apply AI to the field of nuclear energy to overcome the above obstacles and risks. Potential application scenarios include nuclear power software development, equipment prognostics and health management, reactor autonomous control and operation, nuclear safety analysis and accident management.

This topic will explore the application of the latest AI technologies in nuclear energy to promote research, sharing and development. Research topics include but are not limited to the following areas:

1. AI for nuclear power software development
2. Intelligent prognostics and health management of plant equipment
3. AI for reactor automatic control and autonomous operation
4. Nuclear digital twin technology
5. AI for nuclear safety analysis and accident management


Keywords: artificial intelligence, software development, prognostics and health management, autonomous control and operation, digital twin, safety analysis and accident management


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

As a highly complex man-machine-network integration system, the development, construction and operation of nuclear power plant are still facing many obstacles and risks. Firstly, plant instruments and equipment may fail during operation, which will affect the performance and safety of nuclear power plant. Secondly, although nuclear power plants have been digitalized after decades of development, most of them still adopt traditional and inefficient operation and control methods. Finally, due to the above reasons and high control requirements, human operators are under great pressure.

In the past decades, artificial intelligence (AI), especially methods related to deep learning, has made great progress and has been widely used in computer vision, automatic control and other fields. At present, many researchers begin to apply AI to the field of nuclear energy to overcome the above obstacles and risks. Potential application scenarios include nuclear power software development, equipment prognostics and health management, reactor autonomous control and operation, nuclear safety analysis and accident management.

This topic will explore the application of the latest AI technologies in nuclear energy to promote research, sharing and development. Research topics include but are not limited to the following areas:

1. AI for nuclear power software development
2. Intelligent prognostics and health management of plant equipment
3. AI for reactor automatic control and autonomous operation
4. Nuclear digital twin technology
5. AI for nuclear safety analysis and accident management


Keywords: artificial intelligence, software development, prognostics and health management, autonomous control and operation, digital twin, safety analysis and accident management


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

06 September 2021 Abstract
04 January 2022 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

06 September 2021 Abstract
04 January 2022 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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