672 citations · 702 across the 8 of their papers we have counts for
9 papers
Robust Model Reduction Of Hyperbolic Problems by -norm Minimization and Dictionary Approximation
Remi Abgrall, David Amsallem, Roxana Crisonovan
We propose a novel model reduction approach for the approximation of non linear hyperbolic equations in the scalar and the system cases. The approach relies on an offline computati…
Linearized Aeroelastic Computations in the Frequency Domain Based on Computational Fluid Dynamics
David Amsallem, Daniel Neumann, Youngsoo Choi +1
An iterative, CFD-based approach for aeroelastic computations in the frequency domain is presented. The method relies on a linearized formulation of the aeroelastic problem and a f…
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…
Robust Model Reduction by -norm Minimization and Approximation via Dictionaries: Application to Linear and Nonlinear Hyperbolic Problems
Remi Abgrall, David Amsallem
We propose a novel model reduction approach for the approximation of non linear hyperbolic equations in the scalar and the system cases. The approach relies on an offline computati…
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…
Projection-based model reduction for contact problems
Maciej Balajewicz, David Amsallem, Charbel Farhat
To be feasible for computationally intensive applications such as parametric studies, optimization and control design, large-scale finite element analysis requires model order redu…
High-order accurate difference schemes for the Hodgkin-Huxley equations
David Amsallem, Jan Nordstrom
A novel approach for simulating potential propagation in neuronal branches with high accuracy is developed. The method relies on high-order accurate difference schemes using the Su…
On the stability of projection-based linear reduced-order models: Descriptor vs non-descriptor forms
David Amsallem, Charbel Farhat
Two comprehensive approaches are considered for constructing projection-based reduced-order computational models for linear dynamical systems. The first one reduces the governing e…
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…