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At least 73 records · Page 4

Modeling of Cube Array Roughness: RANS, Large Eddy Simulation, and Direct Numerical Simulation

Abstract Flow over arrays of cubes is an extensively studied model problem for rough wall turbulent boundary layers. While considerable research has been performed in computationally investigating these topologies using direct numerical simulation (DNS) and large eddy simulation (LES), the ability of sublayer-resolved Reynolds-averaged Navier–Stokes (RANS) to predict the bulk flow phenomena of these systems is relatively unexplored, especially at low and high packing densities. Here, RANS simulations are conducted on six different packing densities of cubes in aligned and staggered configurations. The packing densities investigated span from what would classically be defined as isolated, up to those in the d-type roughness regime, filling in the gap in the present literature. Three different sublayer-resolved turbulence closure models were tested for each case: a low Reynolds number k–ϵ model, the Menter k–ω SST model, and a full Reynolds stress model. Comparisons of the velocity fields, secondary flow features, and drag coefficients are made between the RANS results and existing LES and DNS results. There is a significant degree of variability in the performance of the various RANS models across all comparison metrics. However, the Reynolds stress model demonstrated the best accuracy in terms of the mean velocity profile as well as drag partition across the range of packing densities.

Engineering↗

Co-optimized machine-learned manifold models for large eddy simulation of turbulent combustion

Many modeling approaches in large eddy simulation (LES) of turbulent combustion employ a projection of the thermochemical state onto a low-dimensional manifold within state space to reduce the number of transported variables and hence computational cost. Flamelet-generated manifolds (FGM) is an example of a well-established, physics-based approach, but increasingly, principal component analysis (PCA) is being used as a data-driven method for generating manifold models. For both approaches, the nonlinear relationship between the location on the predefined manifold and the outputs of interest, such as reaction rates, can be tabulated or encoded in a neural network. This work proposes a new approach for manifold modeling that extends these existing approaches. A modified neural network structure simultaneously encodes the definition of the manifold variables, the nonlinear mapping, and the subfilter closure for LES. This allows all three of these aspects of the model to be co-optimized, generating a model from any source of combustion thermochemical state data. The manifold parameterizing variables are constrained to be linear combinations of species, as in FGM and PCA-based models, to aid in interpretability and implementation. For LES, subfilter variances of the manifold variables are also included as inputs. Two types of a priori analysis are performed to evaluate the new approach. In the first, the model is trained on data from one-dimensional premixed flames. In this case, the approach recovers the behavior of flamelet-based manifold approaches, and in fact slightly improves performance by identifying an optimized progress variable. The approach is also applied to data from direct numerical simulations of spherical ignition kernels in isotropic turbulence. For any specified manifold dimensionality, the new approach provides substantially lower prediction errors than a PCA-based model developed from the same data set. Additionally, the LES formulation of the new approach can provide accurate predictions for filtered reaction rates across a variety of filter widths.

97 MATHEMATICS AND COMPUTING↗

Study of incompressible turbulent channel flow by large eddy simulation

Incompressible turbulent channel flow is investigated by large eddy simulation using improved numerical methods and boundary conditions. In downstream and spanwise directions, cyclic boundary conditions are imposed for velocity and pressure, and two types of boundary conditions near the wall are used and compared. One type is based on the logarithmic law of the mean velocity near the wall and has a slip boundary condition where the molecular-viscous term is neglected. The other type is based on a no-slip boundary condition, where fine mesh spacing near the wall is used to take account of the molecular viscosity. Although the present study employs a coarse mesh (16 x 16 x 21), its results are in good agreement with those of Moin and Kim (1981).

Horiuti, K.↗

On the application of large-eddy simulation to transitional wall-bounded flows

Large-eddy simulations of transition on a flat-plate boundary layer have been carried out. Standard residual stress models of the Smagorinsky type are excessively dissipative, but rescaling the model constant improves the prediction of the total (integrated) subgrid scale dissipation, leading to results that compare favorably with those of a direct simulation, at a small fraction of the computational effort.

Piomelli, Ugo↗

Unstructured-grid large-eddy simulation of flow over an airfoil

Historically, large-eddy simulations (LES) have been restricted to simple geometries where spectral or finite difference methods have dominated due to their efficient use of structured grids. Structured grids, however, not only difficulty representing complex domains and adapting to complicated flow features, but also are rather inefficient for simulating flows at high Reynolds numbers. The lack of efficiency stems from the need to resolve the viscous sublayer, which requires very fine resolution in all three directions near the wall. Structured grids make use of a stretching to reduce the normal grid spacing but must carry the fine resolution in the streamwise and spanwise directions throughout the domain. The unnecessarily fine grid for much of the domain leads to disturbingly high grid estimates. Chapman (1979), and later Moin & Jimenez (1993), pointed out that, in order to advance the technology to airfoils at flight Reynolds numbers, structured grids must be abandoned in lieu of what are known as nested or unstructured grids. The finite element method can efficiently solve the Navier-Stokes equations on unstructured grids. Although the CPU cost per time step per element is somewhat higher than structured grid methods, this effect is more than offset by the reduction in the number of elements. The use of unstructured grids, coupled with the advances in dynamic subgrid-scale modeling such as those made by Germano et al. (1991) and Ghosal et al. (1994), make LES of an airfoil tractable. We have chosen the NACA 4412 airfoil at maximum lift as the first simulation since this flow has not been successfully simulated with the Reynolds-averaged Navier-Stokes equations.

Jansen, Kenneth↗

Large-Eddy Simulation of Turbulent Wall-Pressure Fluctuations

Large-eddy simulations of a turbulent boundary layer with Reynolds number based on displacement thickness equal to 3500 were performed with two grid resolutions. The computations were continued for sufficient time to obtain frequency spectra with resolved frequencies that correspond to the most important structural frequencies on an aircraft fuselage. The turbulent stresses were adequately resolved with both resolutions. Detailed quantitative analysis of a variety of statistical quantities associated with the wall-pressure fluctuations revealed similar behavior for both simulations. The primary differences were associated with the lack of resolution of the high-frequency data in the coarse-grid calculation and the increased jitter (due to the lack of multiple realizations for averaging purposes) in the fine-grid calculation. A new curve fit was introduced to represent the spanwise coherence of the cross-spectral density.

Singer, Bart A.↗

Large-Eddy Simulations of Convection Initiation over Heterogeneous, Low Terrain

Abstract Large-eddy simulations are conducted to investigate and physically interpret the impacts of heterogeneous, low terrain on deep-convection initiation (CI). The simulations are based on a case of shallow-to-deep convective transition over the Amazon River basin, and use idealized terrains with varying levels of ruggedness. The terrain is designed by specifying its power-spectral shape in wavenumber space, inverting to physical space assuming random phases for all wave modes, and scaling the terrain to have a peak height of 200 m. For the case in question, these modest terrain fields expedite CI by up to 2–3 h, largely due to the impacts of the terrain on the size of, and subcloud support for, incipient cumuli. Terrain-induced circulations enhance subcloud kinetic energy on the mesoscale, which is realized as wider and longer-lived subcloud circulations. When the updraft branches of these circulations breach the level of free convection, they initiate wider and more persistent cumuli that subsequently undergo less entrainment-induced cloud dilution and detrainment-induced mass loss. As a result, the clouds become more vigorous and penetrate deeper into the troposphere. Larger-scale terrains are more effective than smaller-scale terrains in promoting CI because they induce larger enhancements in both the width and the persistence of subcloud updrafts.

54 ENVIRONMENTAL SCIENCES↗

Toward Verification of RANS Simulations of the T-Tube Modular Divertor Using Large Eddy Simulations of Impinging Turbulent Plane Jets

Turbulent impinging jets have been proposed to cool high heat flux plasma-facing components such as the solid tungsten target plates of the divertor in long-pulse magnetic fusion energy reactors. In particular, the T-tube modular divertor, originally developed by the ARIES Team, consists of two concentric cylindrical tubes where helium flows through a slot in the inner tube, forming an approximately planar jet that impinges upon and cools the inner surface of the pressure boundary (namely, the outer tube) and the ~15-cm 2 plasma-facing W target. The objective of this work is to demonstrate that large eddy simulations (LESs) accurately simulate the thermal transport in canonical flows that comprise the cooling flow in the T-tube, as well as validate temperatures from LES with experimental measurements in a simplified T-tube geometry. Wall‑resolved LESs, validated by experimental data and verified by direct numerical simulations (DNSs), provide benchmark data for two canonical flows in the T‑tube, namely, planar impinging and wall jets, for Reynolds numbers Re B = 4 × 10 3 to 2 × 10 4 . Our LES results are within 4% to 12% root-mean-square error (RMSE) of surface Nusselt number distributions (Nu) from experiments and DNSs. The validated LES results are then used as the ground truth to evaluate four Reynolds‑averaged Navier-Stokes (RANS) turbulence closures, namely, the k‑ω SST, realizable k‑ε, GEKO, and γ‑SST models. The k‑ω SST model has the best overall performance in terms of heat transfer, giving surface Nu within 12% RMSE of the LES results for high‑ReB impinging jets and reduced overprediction in the wall‑jet region. The GEKO model with default constants has the next best performance, providing slightly better Nu predictions for low ReB impinging jets (versus k-ω SST) but worse overall performance over the full range of ReB studied here. The realizable k‑ε turbulence model significantly overestimates turbulence near the stagnation point, while the γ‑SST model suppresses near‑wall production, biasing the simulations toward simulating laminar surface heat transfer. Simulations of the simplified T‑tube show that LES and RANS simulations with the k‑ω SST model give nearly identical average heat transfer coefficients (HTCs) over the impingement surface. The realizable k‑ε model predicts significantly lower wall temperatures due to overestimation of HTC in the outlet flow.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Numerical Study of Self-Similarity in a Turbulent Plane Wake Using Large-Eddy Simulation

Turbulent wakes are known to develop self-similarly sufficiently far downstream from obstacles that generate them. It has long been assumed that the spreading rate of the wake in the self-similar regime is independent of the details of the body generating the wake, being dependent only on the total drag (or momentum deficit). This assumption seems to be in contradiction with some recent experiments. In this study we attempt to complement these experimental investigations through a numerical study of a time-developing wake. A numerical study has the advantage of eliminating many of the uncontrolled factors present in experiments and allowing precise control of initial conditions. Large-eddy simulations employing the recently developed dynamic localization model are used to extend previous results from direct numerical simulations. The large-eddy simulation results are compared to the direct numerical simulation database, wherever such comparisons are feasible, as a check of the method. Like the experiments, the large-eddy simulations suggest that non-unique self-similar states, characterized by different spreading rates and turbulent statistics, are possible and that they can be maintained for significant time periods. The study also demonstrates the predictive capability of the dynamic localization subgrid model.

Ghosal, Sandip↗

A Large-Eddy Simulation Of Turbulent Flow Over A Backward Facing Step

Large-eddy simulation (LES) was used to study the turbulent flow over a backward facing step. The simulations examine the details of the turbulent flow's separated and reattaching regions created by the step geometry. An explicit high-order of accuracy/high resolution finite-difference computational fluid dynamics solver was used for both LES and Reynolds-averaged Navier-Stokes (RANS) simulations. The experimental data from the backward facing step experiment of Driver and Seegmiller was used for comparison. Data presented are derived from a RANS simulation using the Spalart-Allmaras turbulence model and LES simulations using the implict LES assumption on three different grids of varying resolution. The RANS solution agrees with past work. It does an adequate job of predicting the flowfield and reattachment point, but misses details such as the strength of the recirculating region and magnitudes of the Reynolds stresses. The synthetic eddy method was used to provide a turbulent inflow to the quasi-2D LES domains. For the LES, the coarse grid was of insufficient resolution and under-predicted the skin friction coefficient and over-predicted the normal stresses. The finer grid LES results accurately predict the skin friction coefficient and provide more accurate Reynolds stresses. Triple product velocity correlations are also computed from the LES and the finer grid results did a good job predicting the magnitudes of the curves and the shapes were reasonably represented. It is recommended that future work include investigating the turbulent inflow domain length, width of the quasi-2D domain, and additional grid refinement.

turbulence↗

A Large-Eddy Simulation Of Turbulent Flow Over A Backward Facing Step

Large-eddy simulation (LES) was used to study the turbulent flow over a backward facing step. The simulations examine the details of the turbulent flow’s separated and reattaching regions created by the step geometry. An explicit high-order of accuracy/high resolution finite-difference computational fluid dynamics solver was used for both LES and Reynolds-averaged Navier-Stokes (RANS) simulations. The experimental data from the backward facing step experiment of Driver and Seegmiller was used for comparison. Data presented are derived from a RANS simulation using the Spalart-Allmaras turbulence model and LES simulations using the implicit LES assumption on three different grids of varying resolution. The RANS solution agrees with past work. It does an adequate job of predicting the flowfield and reattachment point, but misses details such as the strength of the recirculating region and magnitudes of the Reynolds stresses. The synthetic eddy method was used to provide a turbulent inflow to the quasi-2D LES domains. For the LES, the coarse grid was of insufficient resolution and under-predicted the skin friction coefficient and over-predicted the normal stresses. The finer grid LES results accurately predict the skin friction coefficient and provide more accurate Reynolds stresses. Triple product velocity correlations are also computed from the LES and the finer grid results did a good job predicting the magnitudes of the curves and the shapes were reasonably represented. It is recommended that future work include investigating the turbulent inflow domain length, width of the quasi-2D domain, and additional grid refinement

turbulence↗

Study of Near-Surface Models in Large-Eddy Simulations of a Neutrally Stratified Atmospheric Boundary Layer

Large-eddy simulation (LES) is a widely used technique in armospheric modeling research. In LES, large, unsteady, three dimensional structures are resolved and small structures that are not resolved on the computational grid are modeled. A filtering operation is applied to distinguish between resolved and unresolved scales. We present two near-surface models that have found use in atmospheric modeling. We also suggest a simpler eddy viscosity model that adopts Prandtl's mixing length model (Prandtl 1925) in the vicinity of the surface and blends with the dynamic Smagotinsky model (Germano et al, 1991) away from the surface. We evaluate the performance of these surface models by simulating a neutraly stratified atmospheric boundary layer.

Senocak, I.↗

Toward the large-eddy simulations of compressible turbulent flows

New subgrid-scale models for the large-eddy simulation of compressible turbulent flows are developed based on the Favre-filtered equations of motion for an ideal gas. A compressible generalization of the linear combination of the Smagorinsky model and scale-similarity model (in terms of Favre-filtered fields) is obtained for the subgrid-scale stress tensor. An analogous thermal linear combination model is also developed for the subgrid-scale heat flux vector. The three dimensionless constants associated with these subgrid-scale models are obtained by correlating with the results of direct numerical simulations of compressible isotropic turbulence performed on a 96 to the third power grid using Fourier collocation methods. Extensive comparisons between the direct and modeled subgrid-scale fields are provided in order to validate the models. Future applications of these compressible subgrid-scale models to the large-eddy simulation of supersonic aerodynamic flows are discussed briefly.

Erlebacher, G.↗

Temporal Large-Eddy Simulation

In 1999, Stolz and Adams unveiled a subgrid-scale model for LES based upon approximately inverting (defiltering) the spatial grid-filter operator and termed .the approximate deconvolution model (ADM). Subsequently, the utility and accuracy of the ADM were demonstrated in a posteriori analyses of flows as diverse as incompressible plane-channel flow and supersonic compression-ramp flow. In a prelude to the current paper, a parameterized temporal ADM (TADM) was developed and demonstrated in both a priori and a posteriori analyses for forced, viscous Burger's flow. The development of a time-filtered variant of the ADM was motivated-primarily by the desire for a unifying theoretical and computational context to encompass direct numerical simulation (DNS), large-eddy simulation (LES), and Reynolds averaged Navier-Stokes simulation (RANS). The resultant methodology was termed temporal LES (TLES). To permit exploration of the parameter space, however, previous analyses of the TADM were restricted to Burger's flow, and it has remained to demonstrate the TADM and TLES methodology for three-dimensional flow. For several reasons, plane-channel flow presents an ideal test case for the TADM. Among these reasons, channel flow is anisotropic, yet it lends itself to highly efficient and accurate spectral numerical methods. Moreover, channel-flow has been investigated extensively by DNS, and a highly accurate data base of Moser et.al. exists. In the present paper, we develop a fully anisotropic TADM model and demonstrate its utility in simulating incompressible plane-channel flow at nominal values of Re(sub tau) = 180 and Re(sub tau) = 590 by the TLES method. The TADM model is shown to perform nearly as well as the ADM at equivalent resolution, thereby establishing TLES as a viable alternative to LES. Moreover, as the current model is suboptimal is some respects, there is considerable room to improve TLES.

Pruett, C. D.↗

A Dynamic Nonlinear Subgrid-Scale Model for Large-Eddy Simulation of Complex Turbulent Flows

We present a new dynamic nonlinear subgrid-scale (SGS) model for large-eddy simulations (LES) and apply it to compute a flow involving pressure gradients, surface curvature and separation, for which data from a direct numerical simulation are available for comparison. The model, inspired by the triple model idea of Bardina et al. (“Improved Turbulence Models Based on Large Eddy Simulation of Homogeneous, Incompressible, Turbulent Flows,” Report No. TF-19, Thermosciences Division, Department of Mechanical Engineering, Stanford University, 1983), includes a Galilean-invariant term called the modified Leonard stress tensor, and two nonlinear terms comprised of the products of the strain-rate and rotation-rate tensors for an improved representation of the subgrid-scale dissipation, backscatter and anisotropy effects. The model does not employ any ad hoc averaging or clipping procedures, and does not require the specification of a characteristic length scale; hence, it naturally avoids the ambiguities associated with defining a proper length scale for anisotropic grids. Results from the wall-resolved LES of flow past a Gaussian bump using the new model demonstrate improved prediction of skin-friction, flow separation, mean flow profiles and turbulent quantities when compared to implicit LES as well as explicit LES using the Vreman SGS model on the same grid.

Turbulence↗

Developments and applications of dynamic models for large eddy simulation of complex flows

The dynamic modeling procedure for large eddy simulation of turbulent flows is reviewed and recent developments in the theoretical aspects and applications are described. Methods for inclusion of backscatter of energy from small to large scale motions are presented. New formulations of the dynamic procedure are proposed which are optimized based on the subgrid scale flux vector or the energy dissipation rate instead of the subgrid scale stress tensor. Recent results from application of the model to forced isotropic turbulence with an inertial subrange, flow over a backward facing step at Reynolds number of 28000, and flow over a concave curved surface are presented.

Moin, P.↗

Code for the manuscript "Lagrangian Large Eddy Simulations vis Physics-informed Machine Learning"

We would like to disclose a code based on Python/Pytorch, in which we implement the data-driven physics-informed machine learning of Lagrangian large eddy simulation that is described in the manuscript "Lagrangian Large Eddy Simulations via Physics-Informed Machine Learning ". High-Reynolds number Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as Large Eddy Simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about the effects of sub-grid scales on the resolved scales. Here, we take an alternative approach and design novel LES heuristics stated in terms of Lagrangian particles moving with the flow. Our \emph{Lagrangian LES}, thus L-LES, is described by equations generalizing the weakly compressible Smoothed Particle Hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from Direct Numerical Simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The sub-grid scale contributions are modeled separately with physical constraints to account for the effects from un-resolved scales. We build the resulting model under the Differentiable Programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our Lagrangian LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

Tian, Yifeng↗

Large-eddy simulation of flow past a circular cylinder

Some of the most challenging applications of large-eddy simulation are those in complex geometries where spectral methods are of limited use. For such applications more conventional methods such as finite difference or finite element have to be used. However, it has become clear in recent years that dissipative numerical schemes which are routinely used in viscous flow simulations are not good candidates for use in LES of turbulent flows. Except in cases where the flow is extremely well resolved, it has been found that upwind schemes tend to damp out a significant portion of the small scales that can be resolved on the grid. Furthermore, it has been found that even specially designed higher-order upwind schemes that have been used successfully in the direct numerical simulation of turbulent flows produce too much dissipation when used in conjunction with large-eddy simulation. The objective of the current study is to perform a LES of incompressible flow past a circular cylinder at a Reynolds number of 3900 using a solver which employs an energy-conservative second-order central difference scheme for spatial discretization and compare the results obtained with those of Beaudan & Moin (1994) and with the experiments in order to assess the performance of the central scheme for this relatively complex geometry.

Mittal, R.↗