TY - JOUR
T1 - A low-dimensional tool for predicting force decomposition coefficients for varying inflow conditions
AU - Ghommem, Mehdi
AU - Akhtar, Imran
AU - Hajj, Muhammad R.
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - FDC
KW - Force decomposition coefficient
KW - LSE
KW - Linear stochastic estimator
KW - POD
KW - Proper orthogonal decomposition
KW - Reduced-order modelling
KW - Unsteady inflow
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U2 - 10.1504/PCFD.2013.057101
DO - 10.1504/PCFD.2013.057101
M3 - Article
AN - SCOPUS:84885991204
SN - 1468-4349
VL - 13
SP - 368
EP - 381
JO - Progress in Computational Fluid Dynamics
JF - Progress in Computational Fluid Dynamics
IS - 6
ER -