Statistically Targeted Forcing (STF) Method for Synthetic Turbulence Generation of Initial Conditions in Three-Dimensional Turbulent Mixing Layer Flow

Abstract

Computational fluid dynamics (CFD) results are presented for synthetic turbulence generation of initial conditions for the canonical test case of a temporally-developing turbulent mixing layer (TTML) flow. This numerical study investigates the performance of a newly proposed Statistically Targeted Forcing (STF) method, and its capability to act as a restoring force to match the target mean velocity and turbulent stress in a temporally-developing flow where highly unsteady destabilizing mechanisms and influence are evident. Several previous investigations exist documenting vortex dynamics of the turbulent mixing layer, but limited investigations exist on synthetic turbulence generation forcing methods to prescribe initial conditions. The objective of this study is to evaluate the performance of the newly proposed STF method to capture the vortex dynamics and effectively match target mean velocity and resolved turbulent stress predictions using large-eddy simulation. Results are interrogated and compared to statistical velocity and turbulent stress distributions obtained from DNS simulations available in the literature. Results show that the STF method can successfully reproduce desired statistical distributions in a turbulent mixing layer flow.