  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.
