A reduced-order model for heat transfer in multiphase flow and practical aspects of the proper orthogonal decomposition

Brenner, Thomas A.; Fontenot, Raymond L.; Cizmas, Paul G. A.; O’Brien, Thomas J.; Breault, Ronald W.

doi:10.1016/j.compchemeng.2012.04.003

Cited by 35 publications

(13 citation statements)

References 51 publications

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“…Of the twenty attempted basis function amounts (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20), the ROM using the static average with static basis functions diverged for six attempted amounts of basis functions (3)(4)(5)(6)(7)(8). The ROMs using the dynamic average converged for all cases.…”

Section: % Plunging Amplitudementioning

confidence: 94%

The Use of Dynamic Basis Functions in Proper Orthogonal Decomposition

Freno

Fontenot

Matula

et al. 2014

52nd Aerospace Sciences Meeting

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Currently, the usefulness of proper orthogonal decomposition (POD) is limited to computational domains with fixed meshes and fixed boundaries. This paper presents a new POD method that enables the modeling of flow through computational domains with deforming meshes and/or moving boundaries. To achieve this goal, the solution is approximated using basis functions which, although not explicitly functions of time, depend on parameters associated with flow unsteadiness. Results are shown for transonic flow through the Tenth Standard Configuration. Comparisons are made between this method and the standard approach for on-and off-reference flow conditions. This method properly captured flow nonlinearities and shock motion for cases in which the classical POD method failed.

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Section: % Plunging Amplitudementioning

confidence: 94%

The Use of Dynamic Basis Functions in Proper Orthogonal Decomposition

Freno

Fontenot

Matula

et al. 2014

52nd Aerospace Sciences Meeting

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“…Unlike the projection method defined by Eq. (13) and used by Brenner et al (2012) in the evaluation of the sampling strategy onto the ROM performance, the error calculated for the solution obtained from dynamic ROM determined by Galerkin projection accounts not only for the effect of spatial approximation but also numerical integration (e.g. time lag with respect to FOM).…”

Section: Resultsmentioning

confidence: 99%

Sampling related issues in pod-based model reduction of simplified circulating fluidised bed combustor model

Bizon¹

2015

Chemical and Process Engineering

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Over the last decades the method of proper orthogonal decomposition (POD) has been successfully employed for reduced order modelling (ROM) in many applications, including distributed parameter models of chemical reactors. Nevertheless, there are still a number of issues that need further investigation. Among them, the policy of the collection of representative ensemble of experimental or simulation data, being a starting and perhaps most crucial point of the POD-based model reduction procedure. This paper summarises the theoretical background of the POD method and briefly discusses the sampling issue. Next, the reduction procedure is applied to an idealised model of circulating fluidised bed combustor (CFBC). Results obtained confirm that a proper choice of the sampling strategy is essential for the modes convergence however, even low number of observations can be sufficient for the determination of the faithful dynamical ROM.

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“…That is, as a design moves from the conceptual phase to the preliminary phase and finally to the detailed phase with this progression, the number of different analysis methods increases along with the level of refinement for each method. Proper orthogonal decomposition works in a similar way for creating reduced order models; as more snapshots are added to the ROM the higher the accuracy the ROM outputs (Brenner et al 2012). The snapshots that are used to construct the ROM are taken from the analysis methods used during the design process.…”

Section: Proper Orthogonal Decompositionmentioning

confidence: 99%

Orthogonal decomposition as a design tool: With application to a mixing impeller

Sloan

2013

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A reduced-order model for heat transfer in multiphase flow and practical aspects of the proper orthogonal decomposition

Cited by 35 publications

References 51 publications

The Use of Dynamic Basis Functions in Proper Orthogonal Decomposition

The Use of Dynamic Basis Functions in Proper Orthogonal Decomposition

Sampling related issues in pod-based model reduction of simplified circulating fluidised bed combustor model

Orthogonal decomposition as a design tool: With application to a mixing impeller

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