University of Houston Leads $750,000 DOE Project Using AI to Advance Next-Generation Energy Systems

The University of Houston has been selected by the US Department of Energy (DOE) to lead a nearly $750,000 collaborative research project that will harness artificial intelligence (AI) to accelerate the design of next-generation nuclear and fusion energy systems. Funded through the DOE’s Genesis Mission, this project brings together researchers from UH, Lawrence Livermore National Laboratory, and the University of Pennsylvania to develop AI-powered engineering tools capable of dramatically reducing the time needed to model complex heat-transfer systems critical to advanced nuclear reactors and future fusion technologies.

The award builds on UH’s growing leadership in AI and energy innovation. By combining AI with fundamental laws of physics, researchers aim to improve the accuracy and speed of computer models used to accelerate the development of reliable, carbon-free energy technologies. This project is a prime example of how data analysis tools can be leveraged to drive breakthroughs in energy research.

The interdisciplinary project focuses on molten salts, whose unique characteristics make it uniquely suited for applications in energy production and storage technologies like nuclear reactors and hybrid energy systems. The goal for the project, titled “Physics-Informed AI Surrogates for Turbulent Forced Convection in Energy Systems,” is to develop a faster, more reliable AI tool that predicts how heat moves through turbulent liquid coolants used in advanced nuclear-fission reactors and future fusion systems.

According to Myoungkyu Lee, a professor at UH’s Cullen College of Engineering, molten salts are attractive for several advanced reactor and fusion blanket concepts but are also among the hardest ones to model. Today’s standard engineering tools were developed for fluids like water and air, and can significantly misjudge heat flow in molten salts. The most accurate simulations are too computationally expensive for everyday design work, so engineers currently bridge the gap with conservative safety margins.

The project aims to cut down this guesswork by developing an AI-assisted model that reproduces results much faster while still following actual laws of fluid flow and heat transfer. Unlike many AI systems, this model would flag areas where its predictions may be unreliable. The goal is to develop a tool that runs much faster than today’s most detailed simulations while keeping errors small.

The award adds to UH’s growing portfolio of energy research, and the broader commitment to bringing together world-class researchers, cutting-edge technologies, and collaborative partnerships with industry, government agencies, and laboratories to advance AI applications across energy, engineering, manufacturing, and other critical industries. This latest award further strengthens UH’s leadership in energy innovation.

The project will receive $180,000 from the DOE, while Lawrence Livermore National Laboratory and University of Pennsylvania will each receive $380,000 and $190,000 respectively. By combining some of its greatest assets – leadership in energy and engineering, world-class research, and national partnerships – UH is solidifying its role as a leader in AI applications for businesses.

According to Ramanan Krishnamoorti, Vice President for Energy and Innovation at UH, this project combines the university’s strengths. ‘Being part of this effort will continue to solidify UH’s role as The Energy University,’ he said.

The development of reliable, carbon-free energy technologies is a pressing challenge that requires innovative solutions. By harnessing AI to accelerate design processes, researchers can make significant strides in advancing next-generation nuclear and fusion energy systems.