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Institute
A widely occurring problem in fluid dynamics either in engineering or e.g. hydrology is the turbulent transport through channels and ducts. ODTLES, a stochastic based multi-scale and multi-dimensional model, is a promising tool to describe these flows even including scalar proper- ties like temperature. We are quantifying the ability of ODTLES to describe the heated channel flow with respect to the Prandtl number and the flow through squared ducts with respect to the Reynolds number.
We use ODTLES, a multi-dimensional extension of the One-Dimensional-Turbulence model (ODT). ODT describes turbulent
advection on a 1D sub-domain using a stochastic process for turbulent advection. These 1D sub-domains are coupled to obtain a 3D approach. ODTLES is applied to channel flow. Preliminary results for the pdf of the wall shear stress are compared to DNS.
The stochastic One-Dimensional Turbulence (ODT) model is used in combination with a Large Eddy Simulation (LES) approach in order to illustrate the potential of the fully coupled model (ODTLES) for highly turbulent flows. In this work, we use a new C++ implementation of the ODTLES code in order to analyze the computational performance in a classical incompressible turbulent channel flow problem. The parallelization potential of the model, as well as its physical and numerical consistency are evaluated and compared to Direct Numerical Simulations (DNSs). The numerical results show that the model is capable of reproducing a representative part of the DNS data at a cheaper computational cost. This advantage can be enhanced in the future by the implementation of a straightforward parallelization approach.
In turbulence research and flow applications, turbulence models like RaNS (Reynolds averaged Navier-Stokes) models and LES (Large Eddy Simulation) are used. Both models filter the governing flow equations. Thus a scale separation approach is introduced for modeling purposes with the large scales simulated using a numerical scheme while smaller scales are assumed to be less important and might be modeled more or less easily. Unfortunately small scales are frequently of big importance, e.g. in reactive flows, wall bounded flows, or flows with significant Prandtl or Schmidt number effects. Recent alternatives to these standard models are the class of models based on the one-dimensional turbulence (ODT) idea, like ODTLES. The ability of ODT to capture highly turbulent flows (recently up to Reτ=6×105) allows ODTLES to realize 3D resolutions basically independent of the turbulent intensity. In two papers we provide a formal theory and application of an innovative modeling strategy for highly turbulent flows in domains of moderate complexity: In part I (see Glawe et al. (2015)) a new general filtering approach, called XLES (extended LES), is introduced. Contrary to LES, XLES is based on 2D filtering of the governing equations, whereby additional small scale terms are interpreted numerically. In this work a new ansatz for the ODTLES model is introduced as one special approach in the XLES family of models by incorporating the ODT model into XLES. The ODT model introduces microstructures not captured by the XLES filtered equations. To illustrate the ODTLES model capabilities, turbulent channel and duct flows up to friction Reynolds number Reτ=10000 are studied.
Reynolds-averaged Navier–Stokes simulation (RaNS) is state-of-the-art for numerical analysis of complex flows at high Reynolds number. Standalone RaNS may yield a reasonable estimate of the wall-shear stress and turbulent drag if a proper wall-function is prescribed, but detailed turbulence statistics cannot be obtained, especially at the wall. This lack in modeling is addressed here by a stochastic deconvolution strategy based on a stochastic one-dimensional turbulence (ODT) model. Here, a one-way coupling strategy is proposed in which a forcing term is computed from the balanced RaNS solution that is in turn utilized in the ODT model. The temporally developing ODT solution exhibits turbulent perturbations but relaxes toward the local RaNS solution due to resolved molecular-diffusive processes. It is demonstrated that the approach is able to recover the distribution of positive wall-shear stress fluctuations in turbulent channel flow. When formulated as post-processing tool, it is suggested that RaNS can be enhanced by ODT providing economical means for local high-fidelity numerical modeling based on a low-fidelity flow solution.