Hyperreduced Reduced Basis Element Method for Component-Based Nonlinear Systems
A model-reduction method for parameterized, component-based continuum-mechanics systems governed by nonlinear PDEs. Offline, component-wise empirical training builds a library of archetype components, each with a local reduced basis (via POD) and empirical-quadrature hyperreduction rules at multiple fidelities. Online, an adaptive scheme grounded in the Brezzi-Rappaz-Raviart theorem selects a hyperreduction fidelity per component so the assembled system meets a user-prescribed solution-error tolerance, giving topological and parametric flexibility for globally nonlinear problems. Demonstrated on a nonlinear thermal fin system with up to 225 components and 68 parameters.
A hyperreduced reduced basis element method for reduced-order modeling of component-based nonlinear
We introduce a hyperreduced reduced basis element method for model reduction of parameterized, component-based systems in continuum mechanics governed by nonlinear partial differential equations. In …