Skip to main content
Journal cover image

Improving the predictable accuracy of fluid Galerkin reduced-order models using two POD bases

Publication ,  Journal Article
Lee, MW; Dowell, EH
Published in: Nonlinear Dynamics
July 1, 2020

A fundamental limitation of fluid flow reduced-order models (ROMs) which utilize the proper orthogonal decomposition is that there is little capability to determine one’s confidence in the fidelity of the ROM a priori. One reason why fluid ROMs are plagued by this issue is that nonlinear fluid flows are fundamentally multi-scale, often chaotic dynamical systems and a single linear spatial basis, however carefully selected, is incapable of ensuring that these characteristics are captured. In this paper, the velocity and the velocity gradient were decomposed using differently optimized linear bases. This enabled an optimization for several dynamically significant flow characteristics within the modal bases. This was accomplished while still ensuring the resulting model is accurate and without iterative methods for constructing the modal bases.

Duke Scholars

Published In

Nonlinear Dynamics

DOI

EISSN

1573-269X

ISSN

0924-090X

Publication Date

July 1, 2020

Volume

101

Issue

2

Start / End Page

1457 / 1471

Related Subject Headings

  • Acoustics
  • 49 Mathematical sciences
  • 40 Engineering
  • 09 Engineering
  • 01 Mathematical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Lee, M. W., & Dowell, E. H. (2020). Improving the predictable accuracy of fluid Galerkin reduced-order models using two POD bases. Nonlinear Dynamics, 101(2), 1457–1471. https://doi.org/10.1007/s11071-020-05833-x
Lee, M. W., and E. H. Dowell. “Improving the predictable accuracy of fluid Galerkin reduced-order models using two POD bases.” Nonlinear Dynamics 101, no. 2 (July 1, 2020): 1457–71. https://doi.org/10.1007/s11071-020-05833-x.
Lee MW, Dowell EH. Improving the predictable accuracy of fluid Galerkin reduced-order models using two POD bases. Nonlinear Dynamics. 2020 Jul 1;101(2):1457–71.
Lee, M. W., and E. H. Dowell. “Improving the predictable accuracy of fluid Galerkin reduced-order models using two POD bases.” Nonlinear Dynamics, vol. 101, no. 2, July 2020, pp. 1457–71. Scopus, doi:10.1007/s11071-020-05833-x.
Lee MW, Dowell EH. Improving the predictable accuracy of fluid Galerkin reduced-order models using two POD bases. Nonlinear Dynamics. 2020 Jul 1;101(2):1457–1471.
Journal cover image

Published In

Nonlinear Dynamics

DOI

EISSN

1573-269X

ISSN

0924-090X

Publication Date

July 1, 2020

Volume

101

Issue

2

Start / End Page

1457 / 1471

Related Subject Headings

  • Acoustics
  • 49 Mathematical sciences
  • 40 Engineering
  • 09 Engineering
  • 01 Mathematical Sciences