Publications by Mengwu Guo | EPFL Graph Search

A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

Jan Sickmann Hesthaven, Mariella Kast, Mengwu Guo

We propose a non-intrusive reduced basis (RB) method for parametrized nonlinear partial differential equations (PDEs) that leverages models of different accuracy. From a collection of low-fidelity (LF) snapshots, parameter locations are extracted for the e ...

ELSEVIER SCIENCE SA2020

Non-intrusive reduced-order modeling for fluid problems: A brief review

Mengwu Guo

Despite tremendous progress seen in the computational fluid dynamics community for the past few decades, numerical tools are still too slow for the simulation of practical flow problems, consuming thousands or even millions of computational core-hours. To ...

SAGE PUBLICATIONS LTD2019

Model order reduction for large-scale structures with local nonlinearities

Jan Sickmann Hesthaven, Mengwu Guo, Zhenying Zhang

In solid mechanics, linear structures often exhibit (local) nonlinear behavior when close to failure. For instance, the elastic deformation of a structure becomes plastic after being deformed beyond recovery. To properly assess such problems in a real-life ...

ELSEVIER SCIENCE SA2019

Data-driven reduced order modeling for time-dependent problems

Jan Sickmann Hesthaven, Mengwu Guo

A data-driven reduced basis (RB) method for parametrized time-dependent problems is proposed. This method requires the offline preparation of a database comprising the time history of the full-order solutions at parameter locations. Based on the full-order ...

2018

Reduced order modeling for nonlinear structural analysis using Gaussian process regression

Jan Sickmann Hesthaven, Mengwu Guo

A non-intrusive reduced basis (RB) method is proposed for parametrized nonlinear structural analysis undergoing large deformations and with elasto-plastic constitutive relations. In this method, a reduced basis is constructed from a set of full-order snaps ...

2018