Subgrid-scale Model Research Articles

Evaluation of subgrid scale models in turbulent large eddy simulations of pumpjet propulsor

To assess the effectiveness of subgrid scale (SGS) models on the prediction results of unsteady loads and turbulent fluctuation of pumpjet propulsors equipped with both front and rear stators, a pumpjet propulsor computational model with attached parts at the model scale is developed using a fully structured mesh, and large eddy simulations are conducted. The computational results of the different SGS models are compared based on five aspects: open water characteristics, turbulence parameters, incoming turbulence spectrum, vortex structure, and fluctuating pressure. Their results are also compared with the experimental values, and the correlation between the internal flow characteristics of the pumpjet propulsor and the turbulent fluctuation is analyzed. According to the results, as regards the prediction of the open water performance of the pumpjet propulsor containing both front and rear stators, the overall trend obtained by the three subgrid models is similar, and the error between the values predicted by the SL model and the experimental ones is the smallest. At the same mesh level, the turbulent fluctuating scale obtained by the SL model is larger than that obtained by the WALE and DSL models, and the turbulent time scale obtained by the DSL model has the smallest fluctuation in the circumferential direction. Among the three SGS models, the turbulent fluctuating scale of the SL model is larger than those of the WALE and DSL models. The SL model exhibits the largest energy dissipation among the three SGS models, followed by the DSL model, while that of the WALE model is the smallest. In the WALE model, the leakage vortex at the top of the blade is the longest, followed by the DSL model, while it is the shortest in the SL model. In the WALE and DSL models, the fluctuating load fluctuates more in the transition region from the middle section to the trailing edge of the blade.

Application of a subgrid-scale urban inundation model for a storm surge simulation: Case study of typhoon Haiyan

This study evaluated the individual drag force model (iDFM), a subgrid-scale model for simulating tsunami inundation in coastal urban areas. The iDFM was then applied to characterize Typhoon Haiyan-induced storm surge inundations in 2013. Using a post-typhoon survey dataset containing inundation depths at different survey points with inundation limits, the performance of iDFM was validated, and the results confirmed that iDFM accurately estimates the storm surge inundation depths but overestimates the limit of inundation. In addition, the results revealed that the iDFM flow velocity was a dominant factor, and the inclusion of buildings in the simulated affected the arrival of the leading edge of inundation. Furthermore, the reduction in flow velocity was sensitive to the subgrid-scale parameters, and the spatial distribution pattern of buildings located in the inundated area affected the relative difference in the maximum flow velocity with the regional roughness model. The inundation characteristics of the Typhoon Haiyan storm surge models were compared with a historical tsunami event. The inundation characteristics were similar and model differences were observed mainly in the fluid velocity and momentum flux rather than the inundation depth. However, the magnitudes of relative differences observed in Tacloban were larger for fluid velocity and momentum flux, respectively, than in the tsunami event. The effect of building drag on advection was also substantial in Tacloban due to the differences in the inflow mass and momentum fluxes.

Large eddy simulation-bivariate sectional model for non-spherical TiO2 nanoparticle synthesis in flame

Numerical simulation of nanoparticle synthesis in flame necessitates a high level of fidelity for turbulent flame, as well as delivers more detail insight into the evolution of structure and size distribution of particles undergoing various dynamic events. In the present work, a new simulation approach coupling large-eddy simulation (LES) and bivariate sectional model is proposed to explore the synthesis of nanoparticles in turbulent flame. More specifically, the nonlinear LES-partially stirred reactor model (NLES-PaSR) is utilized to simulate the turbulent flame, wherein the gradient-type structural subgrid-scale (SGS) model for turbulent flow and partially stirred reactor (PaSR) model for turbulent combustion are considered. In addition, the volume-based bivariate sectional model is thoroughly coupled with the LES model for the first time to describe the spatiotemporally resolved formation and growth of nanoparticles using particle number concentration and surface area concentration as two sets of variables. Compared directly with the LES-monodisperse (LES-Mono) and LES-univariate sectional (LES-UniSe) models, the LES-bivariate sectional (LES-BiSe) model has significant advantages in its ability to analyze and predict the size, morphology, as well as polydispersed particle size distribution (PSD) evolution of nanoparticles at a moderate computational cost simultaneously. In the LES framework, the proposed model successfully simulates the spatiotemporally resolved formation and growth of non-spherical TiO2 nanoparticle in turbulent diffusion burner. The predicted results derived from the LES-BiSe model are in good agreement with the experimental measurements. Also, the aggregate and primary particle size distribution shows highly temporal fluctuation, which mainly results from the continuous variations of particle path induced by the unsteady turbulent combustion. Furthermore, the present work demonstrates the profound dependence of particle morphological on both spatiotemporal evolution and their intrinsic size distribution. In particular, the large aggregates in the higher sections are commonly found as irregular structure with fractal-like dimensions.

Evaluating anisotropic minimum dissipation, sigma and modulated gradient subgrid-scale models in large-eddy simulation of compressible mixing layers

We evaluate three subgrid-scale (SGS) models in large eddy simulations (LES) of compressible mixing layers up to convective Mach number ( M c ) 2.0. The initial momentum-thickness based Reynolds number is 1000 to match recent high-resolution simulations of the same configuration. The simulations employ the Localised Artificial Diffusivity (LAD) shock-capturing scheme and evaluate constant-coefficient and dynamic versions of Anisotropic Minimum Dissipation (AMD), Sigma, and Modulated Gradient (MGM) SGS models. The results show that the LAD scheme is crucial for stability at higher convective Mach numbers, for M c > 1.2 . The SGS models improve the accuracy of the LES predictions, particularly for dissipation and Reynolds stresses. Dynamic versions of all three SGS models give accurate results. The AMD kernel is found to be most sensitive to the flow conditions since the dynamically obtained model coefficient varies the least with M c . Dynamic versions of the SGS models enhance the agreement with reference results compared to the constant-coefficient versions, particularly for the eddy-viscosity AMD and Sigma models, and to a lesser extent for the MGM model. The results also emphasise the importance of retaining a non-zero artificial-shear-viscosity term, even in the presence of explicit SGS models.

Development of a subgrid-scale model for Burgers turbulence using statistical mechanics-based methods

Turbulent flows can be simulated using direct numerical simulations (DNS), but DNS is computationally expensive. Reduced-order models implemented into Reynolds-averaged Navier–Stokes and large eddy simulations (LES) can reduce the computational cost, but need to account for subgrid-scale (SGS) turbulence through closure relations. Turbulence modeling has presented a significant challenge due to the non-linearities in the flow and multi-scale behavior. Well-established features of the turbulent energy cascade can be leveraged through statistical mechanics to provide a characterization of turbulence. This paper presents a physics-based data-driven SGS model for LES using the concepts of statistical mechanics. The SGS model is implemented and tested using the stochastic Burgers equation. DNS data are used to calculate Kramers–Moyal (KM) coefficients, which are then implemented as an SGS closure model. The presented data-driven KM method outperforms traditional methods in capturing the multi-scale behavior of Burgers turbulence.

Numerical investigation on tornado-like flows and immersed bodies using vortex models

A numerical investigation to evaluate tornado flows with immersed bodies is presented in this work, where vortex profile models are adopted to generate the flow field based on time-dependent boundary conditions. In order to reproduce flow conditions obtained from field data and experimental analyses, a parametric study is performed considering the main model parameters influencing the tornado flow characteristics. A Taylor–Galerkin finite element model is used for flow simulation, where eight-node hexahedral elements with one-point integration are adopted. Vortex flow fields are generated numerically using the Modified Rankine Combined Vortex Method (MRCVM) and a fully three-dimensional approach is utilized for tornado-like flows considering the Vastistas vortex model. Turbulence is analyzed using Large Eddy Simulation (LES) with Smagorinsky's sub-grid scale modeling. The vortex formulations are verified considering a circular cylinder submitted to vortex flows, where aerodynamic force coefficients are obtained. A tornado flow field generated experimentally is reproduced utilizing the vortex models proposed here and a cubic building subject to different tornado flow conditions is also analyzed. Results demonstrate that velocity profile models are able to reproduce tornado flow fields and aerodynamic forces on immersed bodies satisfactorily since the boundary conditions and vortex model parameters are calibrated properly.

Invariance embedded physics-infused deep neural network-based sub-grid scale models for turbulent flows

In this paper, we present two novel physics-infused neural network (NN) architectures that satisfy various invariance conditions for constructing efficient and robust Deep Learning (DL)-based sub-grid scale (SGS) turbulence models for use in Large Eddy Simulation (LES) procedures widely used in various fluid engineering applications. The first architecture, called tensor basis neural networks (TBNN), recently proposed in the context of Reynolds-averaged Navier–Stokes (RANS) modeling, and introduced herein for SGS modeling of wall-bounded turbulence, embeds the analytical expansion of the SGS turbulence stresses into integrity basis tensors composed of the symmetric and anti-symmetric parts of the resolved velocity gradient tensor, thus incorporating the Galilean, rotational and reflectional invariances. In our second approach, a relatively simple yet powerful architecture, called Galilean Invariance embedded Neural Network (GINN) incorporates the Galilean invariance, and takes in as inputs the independent components of the integrity basis tensors in addition to the invariant inputs in a single input layer. Explicit filtering of data from direct simulations of the canonical channel flow at two friction Reynolds numbers Reτ≈395 and 590 provided accurate data for training and testing these models. Both sets of models are used to predict the SGS stresses for feature datasets generated with different filter widths, and at different Reynolds numbers. The GINN model yields less prediction error on test datasets (mean squared error ∼0.4) compared to the TBNN model (mean squared error ∼0.5). Upon comparison, it is revealed that GINN has better feature extraction capacity owing to its ability to establish relations between and extract information from cross-components of the integrity basis tensors and the SGS stresses. Based on their predictive performance, both models proposed herein have shown great promise for use in a posteriori actual LESs. The present work illustrates the significance of physics infusion as well as invariance embedding into NN architecture for constructing efficient and robust DL-based SGS turbulent models in achieving superior predictive efficacy.

Influence of wall shear stress on the secondary flow in square ducts

We investigate turbulent duct flows with a square cross section using well-resolved large-eddy simulations (LES). A physically consistent subgrid-scale turbulence model based on the Adaptive Local Deconvolution Method (ALDM) for implicit LES is used. The wall shear stress is artificially modified at one of the four walls to analyse the influence on the secondary flow. A direct numerical simulation (DNS) of a symmetrical duct flow is used as reference to assess the influence of a modified wall shear stress. The modification results in an asymmetrical distribution of the secondary flow source terms, affecting the momentum distribution. Further, the anisotropy of the Reynolds stress tensor, which induces the secondary flow vortices is considerably affected by the wall shear stress modulation.

The multi-objective optimisation design of outlet guide vanes of diagonal flow fan based on sobol sensitivity analysis

Diagonal flow fans offer substantial energy-saving potential and find broad application across various sectors. Their performance relies heavily on factors like outlet guide vanes and spacing relative to moving blades. However, research into enhancing fan performance through optimized guide vanes and spacing remains limited. In this study, we focus on improving the accuracy of predicting the internal flow field of diagonal flow fans. This paper incorporate rotation and curvature effects using the Large Eddy Simulation (LES) model and introduce stress terms with helicity constraints to create a non-linear subgrid-scale model. This refined model enables more precise numerical simulations. By employing accurate simulations, we optimize the outlet guide vane configuration and conduct sensitivity analysis. We utilize a Radial Basis Function (RBF) model coupled with the Sobol method for this purpose. The optimized guide vane design exhibits enhanced resistance to airflow separation compared to the original, resulting in notable reductions in flow losses within the grille channel. Experimental tests are performed on the diagonal flow fan both before and after optimization. At the specified operating point, the second guide vane optimization leads to a 1.28 m3/min increase in fan flow, a 4.33% rise in total pressure efficiency, and a 2.2 dB noise reduction. These findings underscore the accuracy of the helicity correction model in predicting diagonal flow fan behavior. The multi-objective optimization approach, combining the RBF proxy model with the Sobol method, proves highly reliable. It offers valuable design insights for similar fans and establishes a credible design methodology.

High-Order Implicit Large Eddy Simulation using Entropically Damped Artificial Compressibility

Performing industrial scale incompressible Large Eddy Simulation (LES) remains particularly challenging due to computational cost limitations. Recently, the Entropically Damped Artificial Compressibility (EDAC) method was introduced, which does not require coupled global solves or pseudo-time stepping. Parallel to this, high-order unstructured methods, such as the Flux Reconstruction (FR) approach, have been proposed for Implicit LES (ILES) of compressible turbulent flows. This work presents EDAC with FR as an ILES framework for incompressible flows. Results from a Taylor–Green vortex, turbulent channel flow, and transitional and turbulent flow over an SD7003 airfoil demonstrate the approach is accurate and stable for solutions polynomials of degree ps≤4, while some instabilities were observed beyond this. Higher-order solutions were found to be significantly more accurate than their lower-order counterparts compared to reference direct numerical simulation, and had lower divergence error even with less strict incompressibility factors. These results demonstrate that combining EDAC with FR provides a simple, accurate, efficient, and stable framework for performing ILES of incompressible flows. Additionally, this fully explicit framework does not require coupled solvers, pseudo-time stepping, or explicit subgrid scale models.

Multiscale numerical modeling of a complete spray evolution including breakup of liquid jet injection in gaseous cross flow

A direct coupling of the Volume of Fluid method (VOF) and the Lagrangian Particle Tracking (LPT) technique within a Large Eddy Simulation (LES) framework is revisited and assessed by numerically investigating a liquid jet injection into a cross-flowing air (JICF). To close the subgrid scale (SGS) terms appropriate SGS models are considered. In particular, an interfacial SGS term is included into the VOF scalar transport equation in order to achieve a suitable LES and to describe properly the liquid column and the break-up processes (primary and secondary). The dilute spray region including the droplets resulting from the secondary breakup is solved using the LPT approach. Since the latter allows the cell size to be multiple times larger than the droplet diameter, this reduces the computational expenses significantly making it possible to handle the simulation of the whole spray evolution including the complete liquid atomization without complex tunable atomization models. For this purpose, two operating conditions of a JICF existing in the literature are considered. The achieved results are first presented in terms of mesh sensitivity, required computational costs and impact of the interfacial SGS term. Next, comparisons between pure VOF/LES and VOF/LPT/LES for both qualitative features and quantitative properties are provided and discussed. In overall, a good agreement with experiments for the quantitative properties is reported. It is especially found that both the Rosin–Rammler and Gaussian distributions offer nearly a more accurate fit to the particle size distribution except for the range from 0 to 10 μm. Together with the detailed characteristics of vortices evolving and an extended breakup regime map, the spray characteristics including the spray structure are well captured. Finally, even though the interfacial SGS term has an evident influence on the jet and atomization dynamics, its impact on quantitative properties is not so prominent under these operating conditions.

Effect of turbulence and viscosity models on wall shear stress derived biomarkers for aorta simulations

Ascending aorta simulations provide insight into patient-specific hemodynamic conditions. Numerous studies have assessed fluid biomarkers which show a potential to aid clinicians in the diagnosis process. Unfortunately, there exists a large disparity in the computational methodology used to model turbulence and viscosity. Recognizing this disparity, some authors focused on analysing the influence of either the turbulence or viscosity models on the biomarkers in order to quantify the importance of these model choices. However, no analysis has yet been done on their combined effect. In order to fully understand and quantify the effect of the computational methodology, an assessment of the combined effect of turbulence and viscosity model choice was performed. Our results show that (1) non-Newtonian viscosity has greater impact (2.9–5.0%) on wall shear stress than Large Eddy Simulation turbulence modelling (0.1–1.4%), (2) the contribution of non-Newtonian viscosity is amplified when combined with a subgrid-scale turbulence model, (3) wall shear stress is underestimated when considering Newtonian viscosity by 2.9–5.0% and (4) cycle-to-cycle variability can impact the results as much as the numerical model if insufficient cycles are performed. These results demonstrate that, when assessing the effect of computational methodologies, the resultant combined effect of the different modelling assumptions differs from the aggregated effect of the isolated modifications. Accurate aortic flow modelling requires non-Newtonian viscosity and Large Eddy Simulation turbulence modelling.

Simulation of the flow past a circular cylinder from sub-critical to super-critical Reynolds numbers using an intermittency-based hybrid model

In this work, we investigate the prediction of the flow around a circular cylinder from sub-critical to super-critical Reynolds numbers using a hybrid approach which combines a dynamic variational multiscale (DVMS) large-eddy simulation (LES) model and a transitional RANS model. In the proposed hybrid approach, the variational multiscale model, aiming to limit the effects of the subgrid-scale (SGS) model to the smallest resolved scales, is combined with the dynamic procedure which provides a tuning of the SGS dissipation in space and time. For representing laminar to turbulent boundary layer transition, the equations of the RANS part of the hybrid approach are completed with a transition model based on an intermittency transport equation. Results are compared to those of other numerical simulations in the literature and with experimental data. They highlight the overall good prediction capabilities of the proposed hybrid strategy for the simulation of such massively separated flows, even with the use of coarse meshes. In particular, the intermittency-based hybrid model was found to be able to predict the drag crisis of a circular cylinder, as well as the sharp increase in vortex shedding frequency, unlike the equivalent hybrid approach when no laminar-turbulent transition model is introduced.

Numerical Simulation of Turbulent Structures Inside Internal Combustion Engines Using Large Eddy Simulation Method

<div>Using two subgrid-scale models of Smagorinsky and its dynamic version, large eddy simulation (LES) approach is applied to develop a 3D computer code simulating the in-cylinder flow during intake and compression strokes in an engine geometry consisting of a pancake-shaped piston with a fixed valve. The results are compared with corresponding experimental data and a standard K-Ɛ turbulence model. LES results generally show better agreement with available experimental data suggesting that LES with dynamic subgrid-scale model is more effective method for accurately predicting the in-cylinder flow field. Representative Fiat engine equipped with moving valve and piston bowl is analyzed as the second case to assess the capability of the method to handle complex geometries and impacts of geometrical parameters such as shape and position of piston bowl together with swirling intake flow pattern on both turbulent structure of in-cylinder flow and engine performance using dynamic version of LES approach over a curvilinear computational meshed geometry. Results indicate that presence of piston bowl leads to eye-catching increment in both turbulent kinematic energy and tumble ratio amounts at the end of compression stroke by around 29% and 33%, respectively. The optimum swirl ratio found to be 4, leading to 67.9% increment in pre-injection turbulent kinetic energy in comparison with non-swirl pattern, whereas 20% eccentricity of cylinder bowl just led to 2% improvement in the pre-injection turbulent kinetic energy, which is not recommended due to small impact compared to noticeable manufacturing expenditures.</div>

Large-Scale Cluster Parallel Strategy for Regularized Lattice Boltzmann Method with Sub-Grid Scale Model in Large Eddy Simulation

As an improved method of the lattice Boltzmann method (LBM), the regularized lattice Boltzmann method (RLBM) has been widely used to simulate fluid flow. For solving high Reynolds number problems, large eddy simulation (LES) and RLBM can be combined. The computation of fluid flow problems often requires a large number of computational grids and large-scale parallel clusters. Therefore, the high scalability parallel algorithm of RLBM with LES on a large-scale cluster has been proposed in this paper. The proposed parallel algorithm can solve complex flow problems with large-scale Cartesian grids and high Reynolds numbers. In order to achieve computational load balancing, the domain decomposition method (DDM) has been used in large-scale mesh generation. Three mesh generation strategies are adopted, namely 1D, 2D and 3D. Then, the buffer on the grid interface is introduced and the corresponding 1D, 2D and 3D parallel data exchange strategies are proposed. For the 3D lid-driven cavity flow and incompressible flow around a sphere under a high Reynolds number, the given parallel algorithm is analyzed in detail. Experimental results show that the proposed parallel algorithm has a high scalability and accuracy on hundreds of thousands of cores.

Subgrid-Scale Models for Predicting Premixed Methane–Air Flame Propagating in a Chamber with a Rectangular Obstacle

Subgrid-Scale Models for Predicting Premixed Methane–Air Flame Propagating in a Chamber with a Rectangular Obstacle

A small-eddy-dissipation mechanism for turbulence modeling and application to wall-bounded flows

A small-eddy-dissipation (SED) mechanism is proposed in the present study for the development of turbulence models. According to the SED mechanism, a turbulence model introduces artificial dissipation to filter out small eddies so that a lower resolution mesh can be used in the simulation. In addition, the artificial dissipation should be applied outside the energy-containing range so that the large-scale motions are not affected. A small-eddy-dissipation mixing length (SED-ML) model is developed based on the SED mechanism to calculate wall-bounded flows. A local Reynolds number ys+=|det(∇u)|1/3/s is introduced in the SED-ML model to distinguish laminar flows from turbulent flows. Therefore, in addition to fully turbulent flows, the SED-ML model can also be used to calculate weakly turbulent or laminar flows. To demonstrate the performance of the SED-ML model, turbulent channel flows with the Reynolds numbers Reτ up to 4200 are simulated. The numerical results are extensively compared with the large eddy simulation (LES) results using the classical subgrid-scale models. The numerical results show that the SED-ML model predicts the statistical results with a good accuracy, while requiring a lower mesh resolution than the classical LES models. The accuracy of the calculated statistical results can be further improved by the parameter extension. The friction coefficient f for channel flows can be extended directly from the reference solution according to the relation ∂f/∂ϕ/f=−9, where ϕ is a dissipative strength coefficient. The energy and dissipation spectra confirm that the SED-ML model introduces significant dissipation at high wavenumbers. This feature is beneficial in maintaining the high accuracy of the simulation results and reducing the computational cost. The numerical study also shows that a sharp filtering of the turbulent kinetic energy in the wavenumber space is essential for the development of the turbulence model with high performance.

Large-eddy simulations of compressible Rayleigh–Taylor turbulence with miscible fluids using spatial gradient model

Large-eddy simulations (LES) and implicit LES (ILES) of three-dimensional compressible Rayleigh–Taylor turbulence with miscible fluids are performed and compared with direct numerical simulation (DNS) at the Atwood number At=0.5 and stratification parameters Sr = 1.0 and 4.0. Three sub-grid-scale (SGS) models including constant-coefficient spatial gradient model (CSGM), dynamic Smagorinsky model (DSM), and dynamic mixed model (DMM) are considered. The CSGM model achieves a high accuracy by using the velocity gradients at the neighboring LES grids. The a priori tests show that the CSGM model has significantly higher correlation coefficients and lower relative errors than traditional SGS models. In the a posteriori tests, the probability density functions of SGS terms predicted by the CSGM model are consistent with the filtered DNS results. The CSGM model can accurately predict the small bubble and spike structures, resulting in good predictions of mixing heights and concentration fields. The instantaneous structures, spectra, and statistics of velocity and vorticity fields are also examined, showing the excellent performance of the CSGM model compared to the ILES, DSM, and DMM models. Moreover, the predictions of the temperature and pressure fields by the CSGM model are significantly better than the traditional SGS models and ILES.

Wind Tunnel and Grid Resolution Effects in Large-Eddy Simulations of the High-Lift Common Research Model

This paper describes the application of a compressible large-eddy simulation (LES) solver to the flow over the High-Lift Common Research Model (CRM-HL) in landing configuration, a complex external aerodynamic flow configuration with deployed slats, flaps, a flow-through nacelle, and the associated brackets/fairings on the high-lift devices. The bulk Mach number is (0.2) and the mean-aerodynamic-chord-based Reynolds number is typical of a wind tunnel experiment (5.49E6). A key development in these simulations relative to previous work is that this work serves to establish robustness of LES methods to Reynolds number and aircraft configuration. Previous studies focused on the Japan Aerospace Exploration Agency Standard Model, which featured a nearly 3× lower Reynolds number than the present CRM-HL investigation and less aggressive wing/slat leading-edge curvature than the CRM-HL geometry, which led to lower leading-edge pressure suction peak magnitudes, both of which led to less stringent grid resolution requirements. In these LES simulations, an algebraic equilibrium wall modeling approach is employed along with a dynamic implementation of the Smagorinsky subgrid-scale model. The calculations are carried out in both a free air setting and one that includes the wind tunnel facility at seven angles of attack at five grid resolution levels, ranging from ≈10 to 1500 million control volumes. In free air, the solutions show decreasing sensitivity to the grid with each successive refinement level and systematically approach the experimental lift coefficient data as the grid is refined, with the 1.5 billion control volume case showing excellent agreement with the corrected experimental data. The simulations in both free air and in the wind tunnel predict a stall mechanism featuring a large inboard juncture stall and a nose-down break in the pitching moment curve, both of which agree with the experimental observations. The accuracy of the simulations is assessed via comparisons of integrated forces/moments, surface pressures, and surface skin friction visualizations. Graphics processing unit (GPU) acceleration of the charLES solver results in tractable turnaround times that make LES a useful tool in the aerospace industry design cycle. Recent GPU acceleration of the flow solver has made LES solutions that are highly accurate in lift/drag/moment for relevant high-lift aircraft flows achievable within about 5 h of wall time on 600 GPU cores.

Pressure-based large-eddy simulation of under-expanded hydrogen jets for engine applications

An assessment of Large-Eddy Simulations (LES) of non-reactive under-expanded hydrogen jets by using a pressure-based algorithm is presented. Such jets feature strong compressible discontinuities often considered to be best dealt with by a density-based solver. The crucial contribution of this work is to evaluate the suitability of the pressure-based solver to correctly describe the flow field of gaseous hydrogen jets for engine applications, despite the presence of shock waves in the under-expanded near-orifice region. Inherently, the paper aims at providing guidance on the corresponding numerical aspects to simulate these flows. Hydrogen jets in an argon atmosphere at three different injection pressures are simulated and the results are compared to experiments in literature. Jet tip penetration and cone angle are the main investigated parameters. A good match is found, confirming the solidity of the proposed model. Different LES sub-grid scale models and discretisation schemes are then investigated in order to find the best approach in terms of accuracy and required computational cost. In particular, it is found that the WALE model coupled with a 4th-order cubic scheme for the convective terms yields the most suitable configuration.