ECCOMAS 2024
Date:
We adopt a hybrid approach that alternates between a high-fidelity model and a reduced-order model to speedup numerical simulations while maintaining accurate approximations. In particular, we develop an error indicator to determine when the reduced-order model is not sufficiently accurate and the high-fidelity model needs to be solved. Then, we propose an adaptive version of the hybrid approach to update the reduced-order model with the high-fidelity snapshots generated when the reduced-order model was not sufficiently accurate. The performance of the method is evaluated on parametrized, time-dependent, nonlinear problems governed by the 1D Burgers’ equation and 2D compressible Euler equations. The results demonstrate the accuracy and computational efficiency of the adaptive hybrid approach.