Sirod Sirisup

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Low-dimensional flow dynamical systems may converge to erroneous states after long-time integration, even if they are initialized with the correct state. In this paper, we investigate the accuracy of such two-dimensional models constructed from Karhunen–Loeve expansions for flows past a circular cylinder. We first demonstrate that although the short-term(More)
Data recovery and reconstruction methods for unsteady flow fields with spatio-temporal missing data are studied based on proper orthogonal decomposition (POD) and on Kriging interpolation. It is found that for sufficient temporal resolution, POD-based methods outperform Kriging interpolation. However, for insufficient temporal resolution, large spatial(More)
Stochastic low dimensional modeling of random laminar wake past a circular cylinder " , A reconstruction method for gappy and noisy arterial flow data " , IEEE A spectral viscosity method for correcting the long-term behavior of POD models " , J.Driven simulation: A new computational paradigm " , Proc.Driven convective heat transfer simulation " , Int. A(More)
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