USC has been selected as one of the first institutions to help lead the U.S. Department of Energy’s Genesis Mission, a national effort that links 17 DOE national laboratories, universities, and industry to use artificial intelligence for scientific discovery. The program aims to move AI from experimental capability toward reliable scientific workflows across disciplines.
In this initiative, USC will coordinate a multi-institution research team developing a new AI approach for predicting turbulence—one of the hardest problems in physics and engineering. Turbulence influences airflow around aircraft and wind turbines, as well as fuel and flow behavior in engines and pipelines, and it also underpins storm dynamics, ocean currents, and smoke transport.
The core challenge is that turbulence is extremely sensitive to initial conditions. Even small differences can diverge rapidly, producing outcomes that conventional modeling struggles to capture accurately or at feasible computational cost. While turbulence follows physical laws, the number of interacting motions that must be tracked makes brute-force simulation prohibitively expensive.
The project targets turbulence prediction by training AI on governing physical principles and advanced simulation data. Rather than relying solely on generic statistical approximations, the team teaches the model to recognize recurring flow structures—coherent swirling patterns that appear in phenomena such as waterfalls or certain clouds—and to forecast how these structures evolve over time.
Project investigators will emphasize the computational bottleneck: accurate turbulence prediction requires resolving millions of interacting micro-motions, beyond what today’s fastest supercomputers can practically compute for realistic scenarios. If successful, the AI could reduce runtime while improving predictive fidelity, enabling studies that would otherwise take years or remain out of reach.
Although AI has been applied to turbulence before, the team’s strategy is positioned as more structure-aware. By focusing on physical flow organization, the approach aims to strengthen generalization and support faster, more accurate simulations in real engineering and scientific settings.
Beyond the technical work, the Genesis Mission is also designed to strengthen the AI workforce. USC graduate students participate in DOE-aligned extreme-scale computing training programs at Argonne, and summer schools supported by USC Viterbi’s departments and computing centers provide hands-on experience with AI and high-performance tools.
At USC, the effort aligns with the university’s broader investments in human-centered AI and cross-sector collaboration, building on partnerships with national laboratories and industry to translate AI research into impact. For turbulence modeling, that translation could accelerate design cycles in aerospace and infrastructure while improving scientific understanding.
By connecting university innovation, laboratory supercomputing expertise, and industry AI development momentum, USC expects the combined ecosystem to outperform what any single organization could achieve alone. The Genesis Mission’s Phase I RFA phase will evaluate whether integrated AI-science workflows can accelerate discovery, enhance prediction, improve experimentation, and generate new scientific insights.
Subject of Research: AI-driven turbulence prediction using physics-informed learning
Article Title: USC Leads Genesis Mission Effort to Advance AI for Scientific Turbulence Modeling
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Web References: https://genesis.energy.gov
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Keywords: USC, DOE Genesis Mission, turbulence prediction, AI for science, supercomputing, physics-informed machine learning, extreme-scale computing
