نتایج جستجو برای: direct numerical simulation dns
تعداد نتایج: 1204992 فیلتر نتایج به سال:
The primary objective of this study is to evaluate the accuracy of using computational fluid dynamics (CFD) turbulence models to predict entropy generation rates in bypass transitional boundary layers flows under zero and adverse pressure gradients. Entropy generation rates in such flows are evaluated employing the commercial CFD software, ANSYS FLUENT. Various turbulence and transitional model...
Subfilter scalar variance is a critical indicator of small scale mixing in large eddy simulation LES of turbulent combustion and is an important parameter of conserved scalar based combustion models. Realistic combustion models have a highly nonlinear dependence on the conserved scalar, making the prediction of flow thermochemistry sensitive to errors in subfilter variance modeling, including e...
The interaction between vortical isotropic turbulence (IT) and a normal shock wave is studied using direct numerical simulation (DNS) and linear interaction analysis (LIA). In previous studies, agreement between the simulation results and the LIA predictions has been limited and, thus, the significance of LIA has been underestimated. In this paper, we present high-resolution simulations which a...
A novel parallel implementation of hybrid DNS (Direct Numerical Simulation) code for simulating collision-coalescence of aerodynamically interacting particles in a turbulent flow has been developed. An important application of this code is to quantify turbulent collisioncoalescence rate of cloud droplets, relevant to warm rain formation, under physically realistic conditions. The code enables p...
The local eddy diffusivity model for the turbulent scalar flux is widely used to understand and predict transport in turbulence. However, approximation space time not always valid actual flow. An exact non-local expression was previously derived by author using Green's function. Even though profile of a channel flow evaluated, its only discussed phenomenologically. In this study, approach valid...
We report direct numerical simulation (DNS) and large-eddy simulation (LES) of statistically stationary buoyancy-driven turbulent mixing of an active scalar. We use an adaptation of the fringe-region technique, which continually supplies the flow with unmixed fluids at two opposite faces of a triply periodic domain in the presence of gravity, effectively maintaining an unstably stratified, but ...
We report on the isogeometric residual-based variational multiscale (VMS) Large Eddy Simulation of a fully developed turbulent flow over a wavy wall. To assess the predictive capability of the VMS modeling framework, we compare its predictions against the results from direct numerical simulation (DNS) and, when available, against experimental measurements. We use C quadratic B-spline basis func...
Inviscid regularization modeling of turbulent flow is investigated. Homogeneous, isotropic, decaying turbulence is simulated at a range of filter widths. A coarse-graining of turbulent flow arises from the direct regularization of the convective nonlinearity in the Navier–Stokes equations. The regularization is translated into its corresponding sub-filter model to close the equations for large-...
The three-dimensional shear-driven cavity flow is numerically investigated at Reynolds numbers of 5000 and 10,000. This investigation focuses on the unsteadiness and turbulent characteristics of the flow. At the moderate Reynods number (Re = 5000) where the cavity flow is fully laminar, a direct numerical simulation (DNS) is used; at the higher Reynolds number (Re = 1 0,000), large-eddy simulat...
Bubble flows in non-Newtonian fluids were analyzed using first-principles methods with the aim to compute and predict mass transfer coefficients in such fermentation media. The method we used is a Direct Numerical Simulation (DNS) of the reactive multiphase flow with deformable boundaries and interfaces. With this method, we are able for the first time to calculate mass transfer coefficients in...
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