In a breakthrough effort to accelerate engineering innovation, the University of Michigan has launched the Center for Prediction, Reasoning and Intelligence for Multiphysics Exploration (C-PRIME), a cutting-edge initiative funded by the U.S. Department of Energy’s National Nuclear Security Administration. This ambitious center aims to develop an artificial intelligence (AI) oracle capable of answering physics questions of unprecedented complexity, empowering engineers to leapfrog traditional computational bottlenecks and unlock new frontiers in design and simulation.
Contemporary physics, while governed by a rich tapestry of well-established equations, often confronts immense computational challenges when tasked with predicting real-world phenomena. Processes such as turbulent fuel-air mixing inside advanced engines or aerodynamic flows around vehicles involve physical interactions spanning many scales—from molecules to macroscopic structures—making direct solutions through brute-force simulation impractical. The scale and intricacy of these multiscale phenomena impose massive computational loads that exceed current capabilities, even with modern supercomputing resources.
C-PRIME’s strategy circumvents this barrier by leveraging a hybrid approach: rather than attempting to tackle raw physics problems from first principles directly, AI agents will first build trustworthy, physics-informed models rooted in foundational laws such as Newtonian mechanics and energy conservation (e.g., E=mc²). These agents will then generate reliable synthetic data by running simulations based on these models. From this data, streamlined yet highly accurate surrogate models can be constructed, tailored specifically for engineering purposes. This approach translates deeply complex physics into tractable, high-fidelity solutions accessible for iterative design workflows.
Venkat Raman, the center’s director and James Arthur Nicholls Collegiate Professor of Engineering, emphasizes the transformational role of “physics composition.” In this framework, AI systems integrate basic, trusted physical laws as building blocks, from which they autonomously construct multilayered concepts and predictive capabilities. The inherent trustworthiness of these core laws lends credibility to the AI-generated models, providing engineers with confidence in predictions that would otherwise be computationally prohibitive to obtain.
However, the process doesn’t stop at model construction; C-PRIME places substantial emphasis on verification, validation, and uncertainty quantification. Ensuring that AI-driven simulations truly reflect physical reality and accurately capture uncertainties is essential, especially considering the complexity involved. The center will deploy sequences of AI-designed simulations on some of the world’s most powerful supercomputers to delve into propulsion systems critical for hypersonic flight—vehicles traveling at speeds exceeding Mach 5, or five times the speed of sound.
A particular focus of the research is rotating detonation combustors, an emerging propulsion technology poised to revolutionize high-speed aerospace vehicles. These combustors operate through a continuous, ring-shaped sequence of explosions, creating shockwaves that compress and ignite incoming fuel-air mixtures in rapid succession. This cyclic detonation mechanism offers remarkable efficiency improvements—up to 25% better than conventional combustion systems—yet maintaining stable and controlled detonation waves in such environments remains an elusive challenge due to highly nonlinear flow dynamics.
Rotating detonation systems have broad applications in rocketry, air-breathing engines, and satellite thrusters, as well as in power generation through gas turbines. Their complex behavior makes them ideal testbeds for C-PRIME’s AI-integrated simulation framework, which aims to optimize performance and operational stability through sophisticated AI-guided design iterations validated by both computational and experimental means.
Karen A. Thole, Robert J. Vlasic Dean of Engineering at the University of Michigan, highlights the strategic importance of intertwining AI and hypersonics within the national security and scientific leadership context. This federal investment not only pushes the envelope of predictive science but also nurtures the next generation of engineers and scientists who will be adept in harnessing AI’s capabilities to advance science and technology in transformative ways.
To support this multidisciplinary endeavor, student researchers involved with C-PRIME will benefit from the University of Michigan’s pioneering Ph.D. program in Scientific Computing—America’s first established in 1988. Administered through the Michigan Institute for Computational Discovery and Engineering (MICDE), the program equips emerging scholars with rigorous expertise in numerical methods, high-performance computing, and data-driven science, consolidating the university’s leadership in the computational sciences.
The C-PRIME project is structured around five intertwined research thrusts that collectively span the breadth of its mission. First, foundational physics and data synthesis focuses on generating robust models of material behavior and chemical reactions under complex conditions. Second, verification, validation, and uncertainty quantification rigorously assess modeling accuracy and reliability, ensuring AI-generated predictions remain grounded in physical truth. Next, exascale supercomputing architecture optimizes algorithms and software to extract full value from high-performance computing platforms and lays groundwork for the next generation of AI-enhanced supercomputers.
Fourth, machine learning teams concentrate on developing innovative algorithms that accelerate the solution of complex physics problems, capitalizing on data created by autonomous AI agents. Finally, the AI-based integration thrust, led by Raman himself, centers on creating the AI agents responsible for composing physics equations and managing simulations autonomously, enabling seamless interaction between physics content and computational processes.
Complementing the computational approaches, experimental validation remains a foundational pillar at C-PRIME. Carefully designed laboratory combustor tests, carried out by University of Michigan experts Mirko Gamba and Carolyn Kuranz, will provide critical empirical feedback to benchmark and refine AI-driven combustor designs, anchoring simulations in experimental reality and closing the loop between theory, computation, and experiment.
Eric Johnsen, co-director of C-PRIME and a professor of mechanical engineering, underscores the imperative of educating new researchers capable of integrating AI tools into their scientific and engineering work. Given the rapid evolution of AI-driven methodologies, future success in academia and industry will depend heavily on the ability to harness AI as an integral component of the research toolkit, catalyzing innovation across disciplines.
The broader scientific community also recognizes C-PRIME’s potential. David Etim, representing the National Nuclear Security Administration’s Office of Advanced Simulation and Computing, affirms that the center’s AI-driven agenda complements the goals of the Predictive Science Academic Alliance Program (PSAAP). Its focus on high-fidelity simulations for national security priorities, including hypersonic flight and exascale computing, positions C-PRIME at the forefront of impactful scientific advances.
C-PRIME builds upon and extends the University of Michigan’s stature as a computational science powerhouse, anchored by MICDE and bolstered by strategic partnerships such as a $15 million collaboration with Los Alamos National Laboratory. With joint efforts that integrate national laboratory expertise and a newly announced $1.25 billion AI and high-performance computing research facility in Michigan, C-PRIME is well-positioned to redefine how AI accelerates the understanding and engineering of complex physical systems.
In sum, C-PRIME embodies a bold vision for the future of engineering and physics, uniting AI, high-performance computing, and rigorous scientific validation to deliver predictive models at scales and speeds previously unattainable. As AI systems compose, simulate, and refine physics from first principles upwards, the consequences for aerospace propulsion, energy conversion, and many other fields could be revolutionary, enabling breakthroughs that will shape technology and national security in decades to come.
Subject of Research: Artificial intelligence-driven computational physics and engineering simulations for hypersonic propulsion systems.
Article Title: Forging the Future of Engineering: AI and Multiphysics Converge at the Frontier of Hypersonic Propulsion
News Publication Date: Information not provided.
Web References:
- C-PRIME Center: http://c-prime.engin.umich.edu/
- University of Michigan Strategic Partnership with Los Alamos National Lab: https://record.umich.edu/articles/15m-to-fund-u-m-los-alamos-national-laboratory-collaboration/
- U-Michigan and LANL AI Research Complex: https://news.engin.umich.edu/2025/02/u-michigan-announces-most-advanced-ai-research-complex-with-historic-los-alamos-alliance/
Keywords: Artificial intelligence, physics, engineering, aerospace engineering, scientific computing, hypersonics, rotating detonation combustors, exascale supercomputing, machine learning, propulsion systems.
