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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Unsteady CFD Simulations of a Compression Corner Geometry Using Wall-Modeled LES Methods in Loci/CHEM

Several wall-modeled large eddy simulation (WMLES) methods are tested by simulating an unsteady Mach 2.0 compression corner geometry in Mississippi State’s Loci/CHEM solver. This study is conducted to evaluate the usage and requirements of these WMLES methods for applications regarding fluctuating pressure environments on launch vehicles with computational fluid dynamics (CFD). Two hybrid Reynolds-averaged Navier-Stokes (RANS)-large eddy simulation (LES) methods, Dynamic Hybrid RANS-LES (DHRL) and Improved Delayed Detached Eddy Simulation (IDDES), and one wall-stress-model, the Algebraic Wall Model for Wall-Modeled LES (AWMLES), are tested on varying grid and timestep refinement levels. These grid and timestep sizes are chosen to test the minimum requirements for successfully running these WMLES methods. The simulations are evaluated based on turbulent boundary layer properties in the developed boundary layer as well as unsteady quantities relating to fluctuating pressure environments in the region of the compression corner. The DHRL method shows good agreement with the comparison wind tunnel data and shows good grid and timestep convergence. The results from the IDDES and WMLES simulations show good agreement for several quantities with some discrepancies regarding others. The results presented in this paper will be used to inform further studies in predicting unsteady environments on higher-complexity geometries.

Bryson Frank↗
NASA NTRSDate not supplied

HLPW-4/GMGW-3: Wall-Modeled LES and Lattice-Boltzmann Technology Focus Group Workshop Summary

A summary of the nine submissions to the Wall-Modeled LES and Lattice-Boltzmann(WMLESLB) Technical Focus Group (TFG) at the 4th High lift Prediction Workshop is provided. The focus of this TFG was to assess the current capabilities of WMLES and Lattice-Boltzmann methods on a complex high-lift configuration across a wide range of angles of attack. Preliminary analysis of the submitted data suggests that>250𝑀spatial degrees of freedom are needed to accurately predict pitching moments at high angles of attack due to large pressure gradients present on the outboard slat and main element for𝛼 >17◦(corrected for free-air).While some scatter is reported in pitching moments at the low-angles of attack (𝛼 <11◦) - likely caused by differences in flap separation possibly due to low Reynolds number effects - excellent agreement is observed between the submissions near the𝐶𝐿,max state. Objective superiority over steady state RANS can be seen in terms of lack of excess outboard separation; a majority of the good quality WMLES and LB submissions predict wedge-shaped separation patterns consistent with the experimental oil flow. Differences in the onset of stall mechanism in the free-air configuration for𝛼 >20◦is reported with two distinct topologies observed. Topology A is characterized by the onset of corner-flow separation which progressively grows to produce a pitch break in free-air with an angle of attack increase from𝛼=20.55◦to𝛼=21.47◦+𝜖where𝜖is a small perturbation (varying between submissions and likely to be within±0.3◦). Topology Bis characterized by boundary layer weakness emanating from the inboard side of the wing-pylon juncture substantially larger than any weakness in the wing-body juncture (due to corner-flow);submissions in this category do not show any tendency for occurrence of a pitch break for the free-air configuration within the vicinity of𝛼=21.47◦. The in-tunnel simulations submitted by3 participants using different discretizations, grids and closure models show excellent agreement with the experiment in terms of a) integrated loads, b) surface flow-topology, and c) mechanism for the onset of inboard stall. Further evidence is provided to demonstrate both qualitative and quantitative superiority of all 3 WMLES submissions over a single steady state RANS submission to the workshop.

TTT↗
NASA NTRS2023

HLPW-4: Wall-Modeled LES and Lattice-Boltzmann Technology Focus Group Workshop Summary

A summary of the nine submissions to the Wall-Modeled LES and Lattice-Boltzmann(WMLESLB) Technical Focus Group (TFG) at the 4th High lift Prediction Workshop is provided. The focus of this TFG was to assess the current capabilities of WMLES and LB methods on a complex high-lift configuration across a wide range of angles-of-attack. Analysis of the submitted data suggests that>250𝑀spatial degrees of freedom are needed to accurately predict pitching moments at high angles-of-attack due to large pressure gradients present on the outboard slat and main element for 𝛼 >17◦(corrected for free-air). While some scatter is reported in pitching moment coefficient at the low-angles of attack (𝛼 <11◦) - excellent agreement is observed between submissions near the 𝐶𝐿,max state. Objective superiority of WMLES methods over RANS can be seen in terms of lack of excess outboard separation; a majority of the WMLES and LB submissions predict wedge-shaped separation patterns consistent with the experimental oil flow. The in-tunnel simulations show excellent agreement with the experiment in terms of a) integrated loads, b) surface flow-topology, and c) mechanism for the onset of inboard stall. Further evidence is provided to demonstrate both qualitative and quantitative superiority of the WMLES submissions over RANS.

TTT↗
NASA NTRSDate not supplied

Unsteady CFD Simulations of a Compression Corner Geometry Using Wall-Modeled LES Methods in Loci/CHEM

As computing technology continues to improve, simulating unsteady aerodynamic environments on launch vehicle geometries becomes more viable. For NASA’s Space Launch System, the flowfield is characterized by large regions of unsteady turbulent wall-bounded flow. Simulating these unsteady wall-bounded environments is of interest to the SLS Aerodynamics team. Wall-modeled LES methods are currently the best approach for simulating these environments in engineering applications. Less-expensive computationally than fully-resolved methods while maintaining many of the benefits in simulating unsteady environments. Before applying these methods blindly to large geometries, best practices can first be applied and understood on smaller canonical problems.

Bryson Frank↗
NASA NTRSDate not supplied

Wall-modeled LES of the NASA Juncture Flow Experiment

We perform wall-modeled large eddy simulation (WMLES) of the NASA Juncture Flow experiment (Kegerise & Neuhart, NASA/TM–2019–20286) using an equilibrium wall model and unstructured finite volume solver, to assess its predictive ability for complex geometries. The flow condition simulated corresponds to 5 degrees angle of attack with a freestream Mach number of 0.189, and a Reynolds number based on the mean crank chord of 2.4 million. All simulations neglect the effects of wind tunnel walls, sting and mast present in the experiment. To assess the performance of WMLES on simpler flows with very coarse grids, we simulate flow in a turbulent channel at a friction Reynolds number, Reτ≈2000, and flow through a square duct at anReτ≈1000. The duct flow results using the equilibrium wall model indicate that the skin friction is inaccurate near the corner for grid topologies and resolutions typically used in WMLES, having implications for more complicated flows such as the juncture flow. For the juncture flow simulation, two different approaches are investigated. The first approach consists of a truncated-domain simulation wherein the inflow plane of the computational domain is placed at≈0.2chord length of the wing, and we prescribe the mean flow from a separate Reynolds-averaged Navier-Stokes (RANS) solution along with synthetic turbulence to initiate realistic unsteadiness in the domain. The second approach involves simulating the entire geometry with trips to trigger transition to turbulence. The truncated- and full-domain simulations contain about 62 and 90 million cells, respectively; with 8-10 points per boundary layer thickness in the wall-parallel directions, 14-20 points in the wall-normal direction and a near-wall viscous spacing (∆n+1) of≈100. Preliminary results are encouraging overall in terms of the prediction of wall pressure, wall skin friction, velocity and stresses; but indicate that further work is required to improve the predictions in the separation bubble and wing-fuselage corner regions. The grid resolution used in this study is still fairly coarse, and the results should be interpreted as work in progress.

Prahladh S Iyer↗
NASA NTRSDate not supplied

Wall-modeled LES of Flow Over a Gaussian Bump

We perform wall-modeled large eddy simulations (WMLES) of turbulent flow over a Gaussian-shaped bump geometry, to assess its performance in the accelerating and separation regions of the flow. The flow conditions are based on the ongoing CFD validation experiments of Slotnick [NATO STO-MP-AVT-307, 2019]. The oncoming flow Mach number is 0.176, and two Reynolds numbers are simulated that are about 10000 and 36000 based on boundary layer thickness upstream of the bump. Preliminary Reynolds-averaged Navier-Stokes simulations are first performed to assess the effects of Mach number, Reynolds number, tunnel top and sidewall effects. Finally, WMLES results with an equilibrium wall model will be presented at two Reynolds numbers to assess their performance for this flow by making detailed comparisons with available experimental and higher-fidelity numerical data.

turbulence, wall model, large eddy simulation↗
NASA NTRSDate not supplied

Wall-modeled LES of Flow Over a Gaussian Bump

We perform wall-modeled large eddy simulations (WMLES) of turbulent flow over a Gaussian-shaped bump geometry, to assess its performance in the acceleration and separation regions of the flow. An unstructured finite-volume solver is used along with an equilibrium wall model. The Mach number of the oncoming flow selected for the simulation is 0.176, and two Reynolds numbers (Re) are simulated that are about 10000 and 36000 based on boundary layer thickness upstream of the bump. Spanwise periodic results for the lower Re case are compared with the available DNS data, while the full three-dimensional simulation results for the higher Re case are compared to available experimental data. Sensitivity of WMLES results are assessed for a number of factors including grid resolution, wall model exchange location, type of wall model, and unstructured grid topology. The WMLES results for the lower Re case agree well with available DNS data in terms of the wall pressure variation, velocity and turbulent stress profile comparisons. The skin-friction predictions show a reduced tendency to separate. This appears to be accentuated for the higher Re case, for the medium resolution grid used in this study, where WMLES does not predict any flow separation in the mean, which is in contrast to the large separation bubble observed in the experiments.

turbulence↗
NASA NTRSDate not supplied

Evaluation of Wall-Modeled Les for Flow Over A Multi-Element Airfoil

We perform wall-modeled large-eddy simulations (WMLES) of turbulent flow over a 30P30N multielement airfoil at various angles of attack to assess its ability to accurately predict lift using an unstructured node-based finite-volume methodology. The flow conditions are based on the experiments reported in Klausmeyer & Lin [NASA /TM-112858]. The oncoming flow Mach number is 0.2, and the stowed chord-based Reynolds number (𝑅𝑒𝑐) is 9 million. The angle of attack (𝛼) is varied between 8◦ and 23◦ with the expected stall angle of around 21◦. The simulated geometry is periodic in the span, thus any three-dimensional effects present in the experiment are ignored. We first analyze the predictions with baseline isotropic and anisotropic grids containing over 16 grid points per boundary-layer thickness. The near-wall streamwise/nominal spacing ratio is 0.4 at the leading/trailing edges of the slat, main element and flap, and 1 elsewhere, and the first wall-normal/nominal spacing ratio is 0.375 over most of the airfoil for the anisotropic grid, while these are unity for the isotropic grid. It is found that the predicted lift and wall pressures, near-wall velocity profiles, and the location of onset of resolved turbulence are sensitive to the near-wall grid anisotropy. Further sensitivities were explored at lower angles of attack by independently varying the streamwise and wall-normal grid anisotropies. The effects of both off-wall and near-wall grid refinement were also quantified. For the grid resolutions used here, our results suggest that the first wall-normal spacing, which coincides with the WMLES exchange location, has a dominant effect on the predictions for this flow configuration.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Wall-Modeled LES of a Swept Wing with Leading-Edge Ice Using LAVA Curvilinear, Unstructured, and Cartesian Solvers

Wall-modeled large-eddy simulation (LES) of a swept wing with leading-edge ice build up is performed using three mesh paradigms and associated flow solvers and compared to experimental results. The study focuses on an 8.9% scale model of the CRM65 swept wing featuring both high-fidelity and smooth leading-edge ice shapes. The assessment is conducted using the Launch, Ascent, and Vehicle Aerodynamics (LAVA) framework using the three actively supported meshing paradigms in LAVA: structured curvilinear overset, unstructured, andCartesian. For the iced configurations, these paradigms use hybrid body-fitted/source-term immersed-boundary, body-fitted, and ghost-cell immersed-boundary strategies, respectively.The unstructured and Cartesian mesh paradigms are particularly attractive for complex ice shapes as they avoid the manual mesh generation effort associated with the curvilinear approach. For the high-fidelity ice shape, good agreement with the experiment can be obtained with all three strategies; however, the curvilinear method is particularly sensitive to the source-term immersed-boundary timescale and span wise mesh resolution, and the Cartesian implementation is sensitive to the choice of numerical flux. For the smooth ice, larger discrepancies are observed across all methods. However, a mesh refinement study guided by flow visualizations leads to an improved comparison with the experiment that is particularly pronounced for the unstructured mesh paradigm.

TTT↗
NASA NTRSDate not supplied

Wall-modeled LES of Turbulent Flow Over a Two-dimensional Gaussian Bump

We perform wall-modeled large eddy simulations (WMLES) of turbulent flow over a nominally two-dimensional Gaussian-shaped bump geometry to assess its performance in the accelerating and separation regions of the flow. The flow conditions are based on high-fidelity numerical simulation of Uzun & Malik (AIAA Journal 2022). The oncoming flow Mach number is 0.2, with the bump length-based Reynolds number (ReL) of 2 million. In our previous study, while WMLES with the constant coefficient Vreman subgrid scale model and equilibrium wall model performed satisfactorily at lower ReL = 1 million, it failed to predict flow separation at the higher Re, contrary to the experimental observations. We investigate the sensitivity of WMLES to different subgrid scale models, wall models, and grid resolution and topology on flow separation by comparing with available data.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Wall-modeled LES of the Three-dimensional Speed Bump Experiment

We evaluate the performance of wall-modeled large eddy simulation (WMLES) in predicting smooth-body turbulent flow separation for a three-dimensional Gaussian-shaped speed bump geometry. The Reynolds number based on the bump length is 2 million, and an unstructured compressible finite-volume solver is used with an equilibrium wall model and dynamic subgrid scale model. Spanwise periodic simulations of the centerline two-dimensional bump were used to assess grid resolution requirements, and resolving the thin internal layer in the accelerating region was found to be necessary to correctly capture the downstream separated flow region. Based on these insights, an optimized grid that was smaller by a factor of two provided comparable accuracy to a finer grid that has been used by us and other researchers in past studies. Using insights gained from the spanwise periodic simulation, an unstructured polyhderal grid with about 250 million cells was used for the three-dimensional (3D) configuration with inviscid tunnel side and top walls. Detailed comparisons of wall skin-friction coefficient, wall pressure, velocity and turbulent stresses with available experimental data indicated excellent agreement. While the low-Reynolds Number Spalart-Allmaras RANS model with rotation/curvature correction gave qualitatively good agreement with experiments, WMLES showed significantly more accurate quantitative predictions of the flowfield. The 3D WMLES showed good agreement with experiments in the separated region, and the centerplane results indicated a different separation topology compared to the spanwise periodic simulation.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

A Wall-Modeled LES Perspective for the High Lift Common Research Model Using LAVA

A new immersed boundary Wall-Modelled Large Eddy Simulation (WMLES) formulation is developed to study high-lift aerodynamics on the NASA High-Lift Common Research Model (HL-CRM). A sequence of Cartesian Octree grids with sizes ranging from 100 Million through 2.02 Billion grid points is utilized to systematically assess grid-sensitivity and convergence for the in-tunnel (QinetiQ) configuration of the model, and remarkable agreement between the immersed boundary and the curvilinear body-aligned WMLES formulations is reported on grids with comparable resolutions. In the free-air configuration of the model, consistent predictions between the Curvilinear Overset and the Cartesian Octree formulations are reported for angles of attack up to C(L,max) at a=19.57. However, some differences in the onset of stall are seen between the two methods for a>20°: while the curvilinear WMLES experiences wing-root separation with increasing angle of attack (Topology A), the Cartesian Octree formulation shows a different flow topology characterized by boundary layer weakness on the main element, emanating from the pylon-wing attachment (Topology B). In order to obtain further insight into the two-distinct topologies, carefully designed numerical experiments to isolate effects of the model standoff and the tunnel wall-boundary layers are conducted using the immersed boundary WMLES formulation. The increased incidence angle-of-attack on the inboard portion of the wing due to the standoff is shown to be sufficient for triggering a switch from Topology B to Topology A in Cartesian WMLES. The role of the floor boundary layer is further examined in detail by identification of additional corner-flow vorticity generated by the viscous juncture flow interactions between the floor boundary layer and the standoff leading to formation of a strong coherent and persistent vortex on the belly-side of the fuselage. The intensity of this vortex is shown to increase with the thickness of the floor boundary layer. A further increase in the incidence angle of attack near the leading-edge strake caused by the presence of this belly-side vortex is quantified for two-distinct floor boundary layers. Both of the floor boundary layers considered result in the onset of large scale wing-root separation at a=21.47in non-confined (free-air) configurations.

TTT↗
DOE OSTI2024

An Investigation of LES Wall Modeling for Rayleigh–Bénard Convection via Interpretable and Physics-Aware Feedforward Neural Networks with DNS

Abstract The traditional approach of using the Monin–Obukhov similarity theory (MOST) to model near-surface processes in large-eddy simulations (LESs) can lead to significant errors in natural convection. In this study, we propose an alternative approach based on feedforward neural networks (FNNs) trained on output from direct numerical simulation (DNS). To evaluate the performance, we conduct both a priori and a posteriori tests. In the a priori (offline) tests, we compare the statistics of the surface shear stress and heat flux, computed from filtered DNS input variables, to the stress and flux obtained from the filtered DNS. Additionally, we investigate the importance of various input features using the Shapley additive explanations value and the conditional average of the filter grid cells. In the a posteriori (online) tests, we implement the trained models in the System for Atmospheric Modeling (SAM) LES and compare the LES-generated surface shear stress and heat flux with those in the DNS. Our findings reveal that vertical velocity, a traditionally overlooked flow quantity, is one of the most important input features for determining the wall fluxes. Increasing the number of input features improves the a priori test results but does not always improve the model performance in the a posteriori tests because of the differences in input variables between the LES and DNS. Last, we show that physics-aware FNN models trained with logarithmic and scaled parameters can well extrapolate to more intense convection scenarios than in the training dataset, whereas those trained with primitive flow quantities cannot. Significance Statement The traditional near-surface turbulence model, based on a shear-dominated boundary layer flow, does not represent near-surface turbulence in natural convection. Using a feedforward neural network (FNN), we can construct a more accurate model that better represents the near-surface turbulence in various flows and reveals previously overlooked controlling factors and process interactions. Our study shows that the FNN-generated models outperform the traditional model and highlight the importance of the near-surface vertical velocity. Furthermore, the physics-aware FNN models exhibit the potential to extrapolate to convective flows of various intensities beyond the range of the training dataset, suggesting their broader applicability for more accurate modeling of near-surface turbulence.

54 ENVIRONMENTAL SCIENCES↗