This investigation compared the application and accuracy of single- and multi-time-delay linear stochastic estimation-proper orthogonal decomposition (LSE-POD) methods in the temporal domain. These methods were considered for low-dimensional estimations of the dynamics of the energy-containing structures in a high Reynolds number flow. The near wake dynamics of a bluff body were used to demonstrate the robustness and accuracy of the investigated LSE-POD methods. Statistically independent two-dimensional particle image velocimetry (PIV) measurements were used to determine spatial POD modes, and time-resolved surface pressure measurements were used to determine LSE coefficients required for estimating the time-varying POD coefficients. A low-order, time-resolved reconstruction of the wake dynamics was accomplished using these estimated time-varying POD coefficients. The paper also provides details concerning the accuracy of the estimation using multi-time-delay LSE-POD. The results demonstrate that the multi-time LSE-POD technique is successful in capturing and reconstructing the important near wake dynamics. It is also shown that optimizing the time delays used for the estimations increases the accuracy of the reconstruction. As a result of its capabilities, the multi-time-delay implementation of the LSE-POD approach offers an alternate method for low-dimensional modeling that is attractive for real-time flow estimation.
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The authors wish to acknowledge constructive discussions about LSE-POD with Daniel Ewing, Lawrence Ukeiley, and Charles Tinney, as well as the suggestions provided by the reviewers.
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Durgesh, V., Naughton, J.W. Multi-time-delay LSE-POD complementary approach applied to unsteady high-Reynolds-number near wake flow. Exp Fluids 49, 571–583 (2010) doi:10.1007/s00348-010-0821-4
- Particle Image Velocimetry
- Pressure Signal
- Particle Image Velocimetry Measurement
- Stochastic Estimation
- Wake Flow