Adaptive training of local reduced bases for unsteady incompressible Navier-Stokes flows

作者：Wu Yuqi; Hetmaniuk Ulrich^*

来源：International Journal for Numerical Methods in Engineering, 2015, 103(3): 183-204.

DOI：10.1002/nme.4883

• nonlinear model order reduction
• local basis
• proper orthogonal decomposition
• reduced-order basis generation

This report presents a numerical study of reduced-order representations for simulating incompressible Navier-Stokes flows over a range of physical parameters. The reduced-order representations combine ideas of approximation for nonlinear terms, of local bases, and of least-squares residual minimization. To construct the local bases, temporal snapshots for different physical configurations are collected automatically until an error indicator is reduced below a user-specified tolerance. An adaptive time-integration scheme is also employed to accelerate the generation of snapshots as well as the simulations with the reduced-order representations. The accuracy and efficiency of the different representations is compared with examples with parameter sweeps.

• 出版日期2015-7-20