Research Output per Year
Research Output per Year
Research Activity per Year
Marc Henry de Frahan is helping to improve next-generation wind and combustion processes. As part of the Exascale Computing Project, Marc develops high-fidelity turbulence models to enhance simulation accuracy and efficient numerical algorithms for future high-performance computing hardware architectures. In addition to traditional physics-based modeling, he is integrating deep neural networks into modeling and reinforcement learning into advanced control strategies. Beyond his research, Marc is passionate about making science accessible to a broad audience and wrote a children's book about cavitation science. He delights in seeing people's eyes light up when they understand a concept, sparking the desire to learn more.
High-performance computing, GPU computing
High order numerical methods for computational fluid dynamics
Fluid mechanics (turbulence, multiphase flows, combustion)
Deep learning for computational fluid mechanics
Computational combustion
Certificate, Deep Learning Specialization, Coursera
Master, Applied Mathematics, Universite Catholique de Louvain
Bachelor, Applied Mathematics, Universite Catholique de Louvain
PhD, Mechanical Engineering, University of Michigan
Research output: Contribution to journal › Article › peer-review
Research output: NREL › Presentation
Research output: Contribution to journal › Article › peer-review
Research output: NREL › Presentation
Research output: Contribution to journal › Article › peer-review