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Volume 4, Issue 3-4
Interval-Based Reduced-Order Models for Unsteady Fluid Flow

J. Borggaard, A. Hay & D. Pelletier

Int. J. Numer. Anal. Mod., 4 (2007), pp. 353-367.

Published online: 2007-04

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  • Abstract

A number of practical engineering problems require the repeated simulation of unsteady fluid flows. These problems include the control, optimization and uncertainty quantification of fluid systems. To make many of these problems tractable, reduced-order modeling has been used to minimize the simulation requirements. For nonlinear, time-dependent problems, such as the Navier-Stokes equations, reduced-order models are typically based on the proper orthogonal decomposition (POD) combined with Galerkin projection. We study several modifications to this reduced-order modeling approach motivated by the optimization problem underlying POD. Our discussion centers on a method known as the principal interval decomposition (PID) due to IJzerman.

  • Keywords

reduced-order modeling, proper orthogonal decomposition, principal interval decomposition, surrogate model, optimization.

  • AMS Subject Headings

37N10, 76D55, 76M25

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{IJNAM-4-353, author = {}, title = {Interval-Based Reduced-Order Models for Unsteady Fluid Flow}, journal = {International Journal of Numerical Analysis and Modeling}, year = {2007}, volume = {4}, number = {3-4}, pages = {353--367}, abstract = {

A number of practical engineering problems require the repeated simulation of unsteady fluid flows. These problems include the control, optimization and uncertainty quantification of fluid systems. To make many of these problems tractable, reduced-order modeling has been used to minimize the simulation requirements. For nonlinear, time-dependent problems, such as the Navier-Stokes equations, reduced-order models are typically based on the proper orthogonal decomposition (POD) combined with Galerkin projection. We study several modifications to this reduced-order modeling approach motivated by the optimization problem underlying POD. Our discussion centers on a method known as the principal interval decomposition (PID) due to IJzerman.

}, issn = {2617-8710}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/ijnam/866.html} }
TY - JOUR T1 - Interval-Based Reduced-Order Models for Unsteady Fluid Flow JO - International Journal of Numerical Analysis and Modeling VL - 3-4 SP - 353 EP - 367 PY - 2007 DA - 2007/04 SN - 4 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/ijnam/866.html KW - reduced-order modeling, proper orthogonal decomposition, principal interval decomposition, surrogate model, optimization. AB -

A number of practical engineering problems require the repeated simulation of unsteady fluid flows. These problems include the control, optimization and uncertainty quantification of fluid systems. To make many of these problems tractable, reduced-order modeling has been used to minimize the simulation requirements. For nonlinear, time-dependent problems, such as the Navier-Stokes equations, reduced-order models are typically based on the proper orthogonal decomposition (POD) combined with Galerkin projection. We study several modifications to this reduced-order modeling approach motivated by the optimization problem underlying POD. Our discussion centers on a method known as the principal interval decomposition (PID) due to IJzerman.

J. Borggaard, A. Hay & D. Pelletier. (1970). Interval-Based Reduced-Order Models for Unsteady Fluid Flow. International Journal of Numerical Analysis and Modeling. 4 (3-4). 353-367. doi:
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