Towards Intelligent Variational Multiscale Reduced-Order Modeling for Low-Carbon Energy Systems
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Disruptive advances in artificial intelligence, machine learning, and high-performance computing are transforming how we model, simulate, and optimize complex physical systems. In this work, we present a numerical framework that integrates Variational Multiscale (VMS) stabilized finite element formulation with parametric reduced-order modeling (ROM) to accelerate predictive simulations in low-carbon energy applications, including wind turbine wake dynamics, buoyancy-driven flows in thermal systems and hydrokinetic systems. Recent results will be presented and future directions will be discussed.