Features of far-downstream asymptotic velocity fluctuations in a round jet: A one-dimensional turbulence study

Abstract

An accurate prediction of the turbulent jet noise is usually only possible with direct numerical simulation (DNS) or high-resolution large-eddy simulation (LES) of the turbulent sources in the acoustic near field. The required level of fidelity comes at the price of high numerical resolution requirements, a severe restriction of the accessible parameter space, and high computational costs in general. These limitations can be partially mitigated by reduced-order models. In the present work, the stochastic one-dimensional turbulence (ODT) model is utilized as a stand-alone tool in order to study turbulent fluctuations in the far downstream region of turbulent round jets with finite co-flow velocity. ODT is a dimensionally reduced turbulence model that aims to resolve flow-field over a broad range of scales and, thus, the turbulent noise sources at all relevant scales, but only for a single, radially oriented, physical coordinate that is advected downstream with the flow during a simulation run. Here, unheated round jets with nozzle diameter D, nominal Mach number Ma = 0.9 but Reynolds number ReD∈{9×104,2×105,4×105} are studied as a canonical problem. An ensemble of ODT realizations is used to obtain flow statistics from a detailed representation of fluctuations that may be used to estimate turbulent noise by small-scale resolved sources in the near future. As the first step in this direction, we analyze the model representation of the flow field and the participating flow scales in detail. This is done even far downstream of the nozzle, which is not possible with high-resolution LES or DNS. The present ODT results agree well with the available reference data. The model accurately reproduces the asymptotic mean and fluctuating velocity behavior, and radial turbulence spectra of the jet that approximately obey large-scale jet similarity but are modified by axially decreasing the turbulence intensity. Based on these results, an outlook on the model application for turbulent jet noise prediction is given.