Title: A low-dimensional tool for predicting force decomposition coefficients for varying inflow conditions
Authors: Mehdi Ghommem; Imran Akhtar; Muhammad R. Hajj
Division of Physical Sciences and Engineering (PSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
Department of Mechanical Engineering, NUST College of Electrical and Mechanical Engineering, National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan
Department of Engineering Science and Mechanics, Virginia Tech, Blacksburg, VA 24061, USA
Abstract: We develop a low-dimensional tool to predict the effects of unsteadiness in the inflow on force coefficients acting on a circular cylinder using proper orthogonal decomposition (POD) modes from steady flow simulations. The approach is based on combining POD and linear stochastic estimator (LSE) techniques. We use POD to derive a reduced-order model (ROM) to reconstruct the velocity field. To overcome the difficulty of developing a ROM using Poisson's equation, we relate the pressure field to the velocity field through a mapping function based on LSE. The use of this approach to derive force decomposition coefficients (FDCs) under unsteady mean flow from basis functions of the steady flow is illustrated. For both steady and unsteady cases, the final outcome is a representation of the lift and drag coefficients in terms of velocity and pressure temporal coefficients. Such a representation could serve as the basis for implementing control strategies or conducting uncertainty quantification.
Keywords: reduced-order modelling; proper orthogonal decomposition; POD; linear stochastic estimator; LSE; force decomposition coefficients; FDC; unsteady inflow; circular cylinders; flow simulation; pressure field; velocity field; lift coefficient; drag coefficient; computational fluid dynamics; CFD.
Progress in Computational Fluid Dynamics, An Int. J., 2013 Vol.13, No.6, pp.368 - 381
Available online: 08 Oct 2013