论文标题

机器学习和人工智能驱动的多尺度建模,用于轻度水基SMR应用的高燃烧事故燃料

Machine Learning and Artificial Intelligence-Driven Multi-Scale Modeling for High Burnup Accident-Tolerant Fuels for Light Water-Based SMR Applications

论文作者

Hassan, Md. Shamim, Khan, Abid Hossain, Verma, Richa, Kumar, Dinesh, Kobayashi, Kazuma, Usman, Shoaib, Alam, Syed

论文摘要

小型模块化反应堆的概念改变了解决未来能源危机的前景。考虑到其较低的投资要求,模块化,设计简单性和增强的安全功能,这种新的反应堆技术非常有希望。人工智能驱动的多尺度建模(中子,热液压,燃料性能等)的应用是一个概念。在这项工作中,进行了一项有关耐亡燃料的多尺度建模的全面研究。探索了这些燃料在轻水的小型模块化反应堆中的应用。本章还重点介绍了机器学习和人工智能在设计优化,控制和监视小型模块反应器中的应用。最后,简要评估了有关人工智能在高燃烧复合事故耐受燃料的发展中的应用差距。还讨论了实现这些差距的必要行动。

The concept of small modular reactor has changed the outlook for tackling future energy crises. This new reactor technology is very promising considering its lower investment requirements, modularity, design simplicity, and enhanced safety features. The application of artificial intelligence-driven multi-scale modeling (neutronics, thermal hydraulics, fuel performance, etc.) incorporating Digital Twin and associated uncertainties in the research of small modular reactors is a recent concept. In this work, a comprehensive study is conducted on the multiscale modeling of accident-tolerant fuels. The application of these fuels in the light water-based small modular reactors is explored. This chapter also focuses on the application of machine learning and artificial intelligence in the design optimization, control, and monitoring of small modular reactors. Finally, a brief assessment of the research gap on the application of artificial intelligence to the development of high burnup composite accident-tolerant fuels is provided. Necessary actions to fulfill these gaps are also discussed.

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