Machine Learning May Be Key to the Future of Nuclear Energy

Dr. Yang Liu, a professor in the Department of Nuclear Engineering, received a Distinguished Early Career Award from the U.S. Department of Energy for a proposal to investigate the use of machine learning in designing and understanding new nuclear reactors.

As in many areas of modern life, big data has become a big deal in nuclear engineering. A Texas A&M nuclear engineering professor will investigate artificial intelligence’s ability to harness data to improve the next generation of nuclear reactors.

Yang Liu, an assistant professor in the Texas A&M Department of Nuclear Engineering, is one of four researchers chosen for this year’s Distinguished Early Career Award from the U.S. Department of Energy’s Nuclear Energy University Program. This annual award provides funding for outstanding university faculty early in their careers who will help advance nuclear energy research.

Liu’s research focuses on the role of artificial intelligence (AI) and machine learning (ML) in designing and controlling nuclear reactors. At Texas A&M, he established the Scientific Machine Learning for Advanced Reactor Technologies (SMART) laboratory, where he and his students focus on using ML to enhance simulations, engineering decisions, and the operation of nuclear systems.

During his doctoral studies at North Carolina State University, Liu used ML to research how fluids behave in a nuclear reactor. While a postdoctoral researcher at the University of Michigan, he complemented his computational expertise with more hands-on experimental thermal hydraulics.

“This project is a natural extension of my previous research experience and interests,” Liu said. “We’re trying to bring some innovation into a very traditional, but very important, area: reactor thermal hydraulics, which deals with the safety of a reactor system.”

While some popular AI applications, like ChatGPT, focus on generating text through natural language processing, the role of AI and ML in nuclear engineering is quite different. Here, AI processes and learns vast amount of data from simulations and experiments, enabling researchers to refine their understanding and enhance the design and safety of nuclear reactors.

This project is a natural extension of my previous research experience and interests. We’re trying to bring some innovation into a very traditional, but very important, area: reactor thermal hydraulics, which deals with the safety of a reactor system.

-Dr. Yang Liu

“We are in the era of big data, like on the internet, where people are generating texts, images, and videos on the level of terabytes every day,” Liu said. “In the nuclear engineering community, we're also entering an era of big data, which come from high-fidelity simulations and high-resolution experiments.”

To read the full story visit: https://engineering.tamu.edu/news/2024/07/machine-learning-may-be-key-to-the-future-of-nuclear-energy.html