Virtual special issue on artificial intelligence technology in nuclear energy
Published 18 July, 2022
The vigorous development of ‘Internet plus’ technologies, such as artificial intelligence, big data and the Internet of Things, has made the application of ‘data-driven’ a major trend in the field of nuclear energy globally. Artificial intelligence has a wide range of applications in nuclear power system design, engineering construction and operation. For example, intelligent technology has been applied in fault diagnosis, life prediction and design optimisation of nuclear power equipment. In fact, intelligent technologies cover the entire industrial chain of nuclear energy, from fully digital uranium exploration and mining, to the decommissioning of nuclear power plants. In addition, artificial intelligence algorithms, represented by machine learning and deep learning, have been applied to areas such as parameter prediction, operating state identification and flow field prediction. The integration of artificial intelligence algorithms and nuclear engineering provides ideas and possibilities for solving major problems in the field of nuclear energy.
This special issue will present novel insights and techniques for intelligent applications in nuclear energy. We particularly encourage submissions on emerging theories and innovative algorithms in applications, as well as academic papers on the application of mature artificial intelligence technologies in any field of nuclear energy.
These include, but are not limited to:
- Intelligent design, research and development, optimisationand manufacturing of materials and equipment in the field of nuclear power
- Intelligent maintenance and decommissioning of nuclear power plant facilities
- Situational awareness, anomaly detection and fault diagnosis of the operating status of nuclear power plants
- Control strategy optimisationand intelligent decision making for advanced nuclear power design
- Turbulence modelling based on machine learning
- Fusion modelling of the physics model and machine learning model
- Prediction and analysis of flow and heat transfer characteristics,based on machine learning
- Experimental images and other results,post-processing, based on intelligent algorithms
Submission deadline: 30 May 2023
Please read the Guide for Authors before submitting. All articles should be submitted online; please select VSI: Artificial intelligence technology in nuclear energy on submission.
Professor Tan Sichao
Harbin Engineering University, China. Email: email@example.com
Associate professor Yin Junlian
Shanghai Jiao Tong University, China. Email: firstname.lastname@example.org
Associate professor Wang Bo
Harbin Engineering University, China. Email: email@example.com