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- W2315073497 abstract "Low dimensional mode ls have proven useful for feedback control and estimation of flow fields such as separated flow over airfoils, cavities and wakes. While feedback control based on global flow estimation can be very efficient, it is often difficult to estimate the flow stat e if structures of very different length scales are present in the flow . Proper Orthogonal Decomposition (POD) will not reliably separate the structures according to size, since it optimizes modes based on energy only. In this work, we investigate and comp are the use of hybrid POD methods employing both 2D and 3D modes, as well as the use of temporal and spatial filtering to precondition snapshot set s for the derivation of POD modes. Th ree dimensional flow data from the simulations of turbulent flow over a circular cylinder at Re=20,000 and Re=3,900 are used to evaluate the usefulness of both hybrid and filtered POD models of the wake flow for the purpose of flow state estimation . We demonstrate the ability of the hybrid POD models to estimate both strength and shedding phase of the von Karman modes . We compare these results to a filtered 3D POD, and show that it can achieve similar results for the circular cylinder wake. Both methods are able to capture the large features of the flow , while not being contam inated by small scale turbulent structures . Thu s, filtered 3D POD appears to be an alternative means for modeling of 3D flows ." @default.
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- W2315073497 date "2007-01-08" @default.
- W2315073497 modified "2023-10-17" @default.
- W2315073497 title "Low Dimensional POD Based Estimation of a 3D Turbulent Separated Flow" @default.
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- W2315073497 doi "https://doi.org/10.2514/6.2007-112" @default.
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