A low-dimensional tool for predicting force decomposition coefficients for varying inflow conditions. (1st January 2013)

• Record Type: Journal Article
• Authors: Ghommem, Mehdi; Akhtar, Imran; Hajj, Muhammad R.
• Is Part Of: Progress in computational fluid dynamics. Volume 13:Number 6(2013)
• Page Start: 368
• Page End: 381
• Publication Date: 2013-01-01
• Subjects: reduced-order modelling -- proper orthogonal decomposition -- POD -- linear stochastic estimator -- LSE -- force decomposition coefficient -- FDC -- unsteady inflow; Fluid dynamics -- Data processing -- Periodicals; Fluid dynamics -- Mathematics -- Periodicals; 620.10640285
• Languages: English
• ISSNs: 1468-4349

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.