Imperial College London

ProfessorPeterSchmid

Faculty of Natural SciencesDepartment of Mathematics

Chair in Applied Mathematics
 
 
 
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Contact

 

peter.schmid

 
 
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Location

 

753Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Fosas:2016:10.1016/j.jcp.2016.08.004,
author = {Fosas, de Pando M and Schmid, PJ and Sipp, D},
doi = {10.1016/j.jcp.2016.08.004},
journal = {Journal of Computational Physics},
pages = {194--209},
title = {Nonlinear model-order reduction for compressible flow solvers using the Discrete Empirical Interpolation Method},
url = {http://dx.doi.org/10.1016/j.jcp.2016.08.004},
volume = {324},
year = {2016}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Nonlinear model reduction for large-scale flows is an essential component in many fluid applications such as flow control, optimization, parameter space exploration and statistical analysis. In this article, we generalize the POD–DEIM method, introduced by Chaturantabut & Sorensen [1], to address nonlocal nonlinearities in the equations without loss of performance or efficiency. The nonlinear terms are represented by nested DEIM-approximations using multiple expansion bases based on the Proper Orthogonal Decomposition. These extensions are imperative, for example, for applications of the POD–DEIM method to large-scale compressible flows. The efficient implementation of the presented model-reduction technique follows our earlier work [2] on linearized and adjoint analyses and takes advantage of the modular structure of our compressible flow solver. The efficacy of the nonlinear model-reduction technique is demonstrated to the flow around an airfoil and its acoustic footprint. We could obtain an accurate and robust low-dimensional model that captures the main features of the full flow.
AU - Fosas,de Pando M
AU - Schmid,PJ
AU - Sipp,D
DO - 10.1016/j.jcp.2016.08.004
EP - 209
PY - 2016///
SN - 0021-9991
SP - 194
TI - Nonlinear model-order reduction for compressible flow solvers using the Discrete Empirical Interpolation Method
T2 - Journal of Computational Physics
UR - http://dx.doi.org/10.1016/j.jcp.2016.08.004
UR - http://hdl.handle.net/10044/1/39080
VL - 324
ER -