Stabilization of projection‐based reduced‐order models
By David Amsallem, Charbel Farhat. 2012
232 citations recorded by the source corpus.
Subfields: Computational Mechanics, Statistical and Nonlinear Physics, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/c7a7aa539cad9b55728dfbfa4a5e42bfdca809fa
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Mechanics
- David Amsallem
- Charbel Farhat
- Matthew J. Zahr
- Sankaran Mahadevan
- Zhen Hu
- Kevin T. Carlberg
- Philip Avery
- Steven L. Brunton
In Statistical and Nonlinear Physics
- David Amsallem
- Charbel Farhat
- Matthew J. Zahr
- Zhen Hu
- Sankaran Mahadevan
- Kevin T. Carlberg
- Philip Avery
- Andrea Manzoni
In Statistics and Probability
- Sankaran Mahadevan
- David Amsallem
- Zhen Hu
- Charbel Farhat
- Matthew J. Zahr
- Kevin T. Carlberg
- Anthony Nouy
- Danny C. Sorensen
Citations in the corpus
- Time-Dependent System Reliability Analysis Using Random Field Discretization (2015, methodology): “During the past several decades, many approaches have been proposed for the modeling of Gaussian random fields, such as Karhunen–Loève (KL) and polynomial chaos expansions (PCE), the shape function method [23], optimal linear estimation, expansion optimal linear estimation (EOLE) [23], and proper or”
- Stabilization of projection-based reduced order models for linear time-invariant systems via optimization-based eigenvalue reassignment (2014, unknown): “In [2], Amsallem et al.”
- Nonlinear model order reduction based on local reduced‐order bases (2012, methodology): “For this reason, MOR methods search for the solution of a set of governing equations in a subspace, thereby offering a potential for significant CPU time reductions [1–8].”