672 citations · 1.2k across the 19 of their papers we have counts for
9 papers · 1 filter
Mesh sampling and weighting for the hyperreduction of nonlinear Petrov-Galerkin reduced-order models with local reduced-order bases
Sebastian Grimberg, Charbel Farhat, Radek Tezaur +1
The energy-conserving sampling and weighting (ECSW) method is a hyperreduction method originally developed for accelerating the performance of Galerkin projection-based reduced-ord…
In-situ adaptive reduction of nonlinear multiscale structural dynamics models
Wanli He, Philip Avery, Charbel Farhat
Conventional offline training of reduced-order bases in a predetermined region of a parameter space leads to parametric reduced-order models that are vulnerable to extrapolation. T…
Model Reduction Framework with a New Take on Active Subspaces for Optimization Problems with Linearized Fluid-Structure Interaction Constraints
Gabriele Boncoraglio, Charbel Farhat, Charbel Bou-Mosleh
In this paper, a new take on the concept of an active subspace for reducing the dimension of the design parameter space in a multidisciplinary analysis and optimization (MDAO) prob…
On the stability of projection-based model order reduction for convection-dominated laminar and turbulent flows
Sebastian Grimberg, Charbel Farhat, Noah Youkilis
In the literature on projection-based nonlinear model order reduction for fluid dynamics problems, it is often claimed that due to modal truncation, a projection-based reduced-orde…
Learning Constitutive Relations from Indirect Observations Using Deep Neural Networks
Daniel Z. Huang, Kailai Xu, Charbel Farhat +1
We present a new approach for predictive modeling and its uncertainty quantification for mechanical systems, where coarse-grained models such as constitutive relations are derived…
Real-time solution of computational problems using databases of parametric linear reduced-order models with arbitrary underlying meshes
David Amsallem, Radek Tezaur, Charbel Farhat
A comprehensive approach for real-time computations using a database of parameterized linear reduced-order models (ROMs) is proposed. The method proceeds by sampling offline ROMs f…
Gradient-based Constrained Optimization Using a Database of Linear Reduced-Order Models
Youngsoo Choi, Gabriele Boncoraglio, Spenser Anderson +2
A methodology grounded in model reduction is presented for accelerating the gradient-based solution of a family of linear or nonlinear constrained optimization problems where the c…
A practical factorization of a Schur complement for PDE-constrained Distributed Optimal Control
Youngsoo Choi, Charbel Farhat, Walter Murray +1
A distributed optimal control problem with the constraint of a linear elliptic partial differential equation is considered. A necessary optimality condition for this problem forms…
The GNAT method for nonlinear model reduction: effective implementation and application to computational fluid dynamics and turbulent flows
Kevin Carlberg, Charbel Farhat, Julien Cortial +1
The Gauss--Newton with approximated tensors (GNAT) method is a nonlinear model reduction method that operates on fully discretized computational models. It achieves dimension reduc…