Use of proper orthogonal decomposition for time interpolation from PIV data

Use of proper orthogonal decomposition for time interpolation from PIV data Based on time-resolved PIV (TRPIV) data, a new proper orthogonal decomposition (POD) application is developed to recover the time information between two consecutive PIV time measurements. Indeed, by performing a POD over the full PIV velocity field snapshots, POD coefficients are time-interpolated providing a continuous space–time description of the turbulent flow field. An application of this interpolation method is proposed from TRPIV velocity fields obtained in the tumble plane of in-cylinder engine flow. Available flow dynamical representations then allow some cycle-to-cycle variation analyses based on the instantaneous flow pictures as well as on the statistical data. It has been shown that the cyclic variabilities increase during the compression process and at the end of the compression stage, they decrease to reach those obtained during the intake process. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Experiments in Fluids Springer Journals

Use of proper orthogonal decomposition for time interpolation from PIV data

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Publisher
Springer-Verlag
Copyright
Copyright © 2005 by Springer-Verlag
Subject
Engineering; Engineering Fluid Dynamics; Fluid- and Aerodynamics; Engineering Thermodynamics, Heat and Mass Transfer
ISSN
0723-4864
eISSN
1432-1114
D.O.I.
10.1007/s00348-005-0035-3
Publisher site
See Article on Publisher Site

Abstract

Based on time-resolved PIV (TRPIV) data, a new proper orthogonal decomposition (POD) application is developed to recover the time information between two consecutive PIV time measurements. Indeed, by performing a POD over the full PIV velocity field snapshots, POD coefficients are time-interpolated providing a continuous space–time description of the turbulent flow field. An application of this interpolation method is proposed from TRPIV velocity fields obtained in the tumble plane of in-cylinder engine flow. Available flow dynamical representations then allow some cycle-to-cycle variation analyses based on the instantaneous flow pictures as well as on the statistical data. It has been shown that the cyclic variabilities increase during the compression process and at the end of the compression stage, they decrease to reach those obtained during the intake process.

Journal

Experiments in FluidsSpringer Journals

Published: Sep 14, 2005

References

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