An improved algorithm for the shallow water equations model reduction: Dynamic Mode Decomposition vs POD

Recent years have seen increased emphasis on mathematical model reduction using modal decomposition techniques of high dimensional flow field data from experiments as well as numerical simulations. These tools decode the complex unsteady flow-field into several modes. Different tools highlight different flow dynamics. In the experimental community, Proper Orthogonal Decomposition (POD) has been the most commonly used technique, ranking modes by their relative energy content, without concern for temporal aspects. However, many dynamics are not highlighted by the most energetic structures. In transitional flows for example, structure growth is a more a more important indicator of the turbulent effects. The Dynamic Mode Decomposition (DMD) technique highlighted by Schmid [1] achieves this by ranking modes by the most dynamically varying flow features. In this work, we use DMD and POD to analyze flow past a NACA0015 airfoil at Reynolds number of 100,000 and AoA=15 degree, without and with control. The specific control technique employed is based on the Nano-second Pulsed Dielectric Barrier Discharge (NS-DBD) actuator. Experimentally validated high fidelity 3-D numerical simulations are employed to generate the required snapshots. From the DMD modes, the dominant time-varying flow structures associated with the two cases are identified, and their stability characteristics are compared. DMD and POD modes are compared to each other. The DMD modes highlight the dynamically varying nature of the flow-field. A Floquet stability analysis of the eigenvalues from DMD for both the no-control and control cases is presented. Further, the original flow field is reconstructed from the DMD modes and their individual modal behavior has been analyzed to show the effect of control authority on the flow.

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Parameter space and model reduction with shape parametrization, by means of active subspace and POD-Galerkin methods for industrial and biomedical applications

10.14293/p2199-8442.1.sop-math.zkdilb.v1 ◽

2018 ◽

Author(s):

Marco Tezzele ◽

Francesco Ballarin ◽

Andrea Mola ◽

Gianluigi Rozza

Keyword(s):

Model Reduction ◽

Parameter Space ◽

Biomedical Applications ◽

Engineering Problem ◽

Dynamic Mode Decomposition ◽

Free Form ◽

Dynamic Mode ◽

Space Reduction ◽

Mode Decomposition ◽

Wide Range

In this work we present both industrial and biomedical applications, focusing on shape parametrization and parameter space reduction by means of active subspaces. In particular we introduce a combined parameter and model reduction methodology using a POD-Galerkin approach, and its application to the efficient numerical estimation of a pressure drop in a set of deformed carotids [2]. The aim is to simulate a wide range of possible occlusions after the bifurcation of the carotid artery. A parametric description of the admissible deformations, based on radial basis functions interpolation technique implemented in the PyGeM python package, is introduced. The use of the reduced order model acting on the reduced parameter space allows significant computational savings and better performances. Moreover we present the reduction of heterogeneous parameter space in a naval engineering problem, that is the hydrodynamic flow past the hull of a ship advancing in calm water [3], considering structural and shape parameters. The geometrical parametrization is done via free form deformation. Some perspectives on a complete shape optimization pipeline by means of Dynamic Mode Decomposition (DMD) and POD with interpolation (PODI) are presented [1], together with the integration of the python packages PyDMD and EZyRB respectively.

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Experimental Measurement of In-Plane Rolling Nonpneumatic Tire Vibrations Using High-Speed Imaging

Tire Science and Technology ◽

10.2346/tire.18.470101 ◽

2019 ◽

Vol 47 (3) ◽

pp. 196-210

Author(s):

Meghashyam Panyam ◽

Beshah Ayalew ◽

Timothy Rhyne ◽

Steve Cron ◽

John Adcox

Keyword(s):

High Speed ◽

Image Correlation ◽

Dynamic Mode Decomposition ◽

Dynamic Mode ◽

High Speed Imaging ◽

Correlation Algorithm ◽

Mode Decomposition ◽

Series Of Experiments ◽

Plane Deformations ◽

Dominant Frequencies

ABSTRACT This article presents a novel experimental technique for measuring in-plane deformations and vibration modes of a rotating nonpneumatic tire subjected to obstacle impacts. The tire was mounted on a modified quarter-car test rig, which was built around one of the drums of a 500-horse power chassis dynamometer at Clemson University's International Center for Automotive Research. A series of experiments were conducted using a high-speed camera to capture the event of the rotating tire coming into contact with a cleat attached to the surface of the drum. The resulting video was processed using a two-dimensional digital image correlation algorithm to obtain in-plane radial and tangential deformation fields of the tire. The dynamic mode decomposition algorithm was implemented on the deformation fields to extract the dominant frequencies that were excited in the tire upon contact with the cleat. It was observed that the deformations and the modal frequencies estimated using this method were within a reasonable range of expected values. In general, the results indicate that the method used in this study can be a useful tool in measuring in-plane deformations of rolling tires without the need for additional sensors and wiring.

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Coherency Identification in Multimachine Power Systems Using Dynamic Mode Decomposition

2020 European Control Conference (ECC) ◽

10.23919/ecc51009.2020.9143708 ◽

2020 ◽

Author(s):

A. Saija ◽

K. Sonam ◽

F. Kazi ◽

N. M. Singh

Keyword(s):

Power Systems ◽

Dynamic Mode Decomposition ◽

Dynamic Mode ◽

Mode Decomposition

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