Wall-modeled Large Eddy Simulation Research Articles

Improved Delayed Detached-Eddy Simulation of Turbulent Vortex Shedding in Inert Flow over a Triangular Bluff Body

The Improved Delayed Detached-Eddy Simulation (IDDES) is a modification of the original Detached-Eddy Simulation (DES) design to incorporate Wall Modeled Large Eddy Simulation (WMLES) capabilities and to extend the class of flows suitable for this methodology. For thin attached boundary layers, typically seen in external aerodynamic flows, the DES branch of the model is active, whereas with thick boundary layers, typically seen in internal flows and also wake flows, the WMLES branch is active, thus providing a numeric method suited to handling most flow cases automatically. The flow over a triangular bluff body is used to validate the suitability of the IDDES model and compare the results with experimental, DDES, and LES data. The IDDES model is found to be relatively accurate when compared with the experimental results, with recirculation length, streamwise velocity, and Reynolds stresses all showing good agreement with the experimental data. However, when compared with the DDES model, there is a ~4% overprediction of the recirculation length using the same mesh and numerical scheme. The code, with its extra complexity, is also ~3% slower to solve. The IDDES model has also been tested against different meshes, and the results show that even for a coarse mesh, there is still good agreement with the experimental data.

A wall-modeled large-eddy simulation of the unsteady flow in a water-jet pump based on the turbulent length scales

Non-zonal hybrid Reynolds-averaged Navier-Stokes (RANS) and large-eddy simulation (LES) are commonly used for predicting unsteady flows in pumps. However, these hybrid methods often face challenges in the transition between the RANS and LES regions, known as the “grey area” problem. In this study, a pure LES approach, coupled with wall modeling to eliminate this issue, was employed to simulate unsteady flow in a water-jet pump (WJP). A grid generation method, based on turbulent length scales derived from a precursor RANS calculation, was developed to address the complexities of grid design in wall-modeled large-eddy simulations (WMLESs) for complex geometries. Initially, the accuracy of the wall model was validated in the fully developed channel flow. The grid generation method and the accuracy of WMLES in predicting unsteady fluctuations were validated using the flow over a flat strut with an asymmetrically beveled trailing edge. The predicted fluctuation spectra at monitored points showed strong agreement with experimental data. The grid generation method was then applied to WMLES of flow in a WJP, where experimental measurements of the pump head rise and torque were accurately calculated by the numerical simulations. The results from three different grid resolutions were compared with experimental data, revealing significant changes in the predicted mean and transient fields as the grid was refined. The grid based on the turbulent length scales reproduced both the hydrodynamics and transient vortices with high accuracy and detailed resolution. These comparisons demonstrated that pure LES with wall modeling effectively predicts the mean and fluctuating characteristics of high Reynolds number flows with reasonable computational cost. The turbulent length scale-based WMLES enhance the fidelity of computational tools for simulating pump flows.

Turbulent flow and wall forces in staggered square cylinder porous media: An LES Analysis

Abstract The Wall-Modeled-Large Eddy Simulation (WMLES) technique was used to analyze turbulent flow in a porous medium composed of a staggered arrangement of square cylinders. The study focused on a porosity range of 0.3 to 0.8 at a pore Reynolds number of 10×103. The research provides novel information on pressure and shear force distributions around the cylinders and time-averaged values of particle drag and fluctuating lift coefficients. Results indicate that the flow physics are mainly driven by an expansion region in front of the central particle and another in the rear, where the flow is contracted and strongly accelerated. In the first region, velocities, turbulence kinetic energy (k), and its dissipation rate (e) are attenuated by a sudden pressure increase, while in the contraction region, the effect is the opposite. As porosity decreases, flow gradients and the overall levels of k, e, and Reynolds stresses become more significant. Turbulent anisotropy increases as porosity decreases below 0.6. Hydrodynamic stresses in the last interval present relatively uniform levels, which is a unique feature that may be considered in designing dedicated engineering devices with controlled stresses.

The effect of different subgrid-scale models on the flow field in cyclone separator using large-eddy simulations: A benchmark study

Abstract The cyclone separator is extensively utilized across industries to extract solid particles from gas streams. This study is focused on the steady and unsteady simulations of the Stairmand cyclone using large-eddy simulations aiming to assess the performance using different subgrid-scale models viz. standard Smagorinsky (Cs =1), dynamic Smagorinsky, Wall-Adapting Local Eddy-Viscosity (WALE), Wall-Modeled LES (WMLES), and dynamic kinetic energy models. The velocity profiles within the cyclone separator were analyzed under both steady and unsteady conditions, with reference to the Hoekstra experiment for validation and comparison. Velocity profiles inside the cyclone separator were inadequately predicted by the steady-state simulation, whereas the unsteady-state simulation yielded results more aligned with experimental values. The present study suggests that adopting subgrid-scale LES models such as standard Smagorinsky and WMLES offers a better option for analyzing flow patterns.

Analysis of ansys fluent for Wall-Modeled Large-Eddy Simulation of Turbulent Channel Flow

Abstract This study assesses the accuracy of ansysfluent 19.2, a commonly employed general-purpose finite volume solver, in the context of wall-modeled large-eddy simulation for turbulent channel flow at a moderate Reynolds number, Reτ=2000. The sensitivity of the solution to variations in grid resolution, aspect ratio, grid arrangement (collocated versus staggered), and subgrid-scale (SGS) model is analyzed and contrasted to results from a corresponding direct numerical simulation (DNS) and a mixed pseudospectral and finite differences solver. Results indicate good convergence of first- and second-order statistics from the staggered grid setups as the grid is refined, whereas no clear trend is observed in cases with collocated grid setups. Velocity spectra show a lack of an apparent inertial range trend and rapid decay of energy density at high wavenumbers, with a spurious energy pile-up near the cutoff wavenumber indicating the presence of unphysical oscillations in the velocity fields. Grid refinement strengthens such oscillations in collocated grid setups and reduces them in staggered grid setups. Two-point streamwise velocity autocorrelation maps reveal an underprediction of turbulent structure size. In contrast, cross-stream autocorrelations agree with corresponding curves from direct numerical simulation, showing signatures of alternating high- and low-momentum streaks in the logarithmic layer.

Building-block-flow computational model for large-eddy simulation of external aerodynamic applications

Computational fluid dynamics is an essential tool for accelerating the discovery and adoption of transformative designs across multiple engineering disciplines. Despite its many successes, no single approach consistently achieves high accuracy for all flow phenomena of interest, primarily due to limitations in the modeling assumptions. Here, we introduce a closure model for wall-modeled large-eddy simulation to address this challenge. The model, referred to as the Building-block Flow Model (BFM), rests on the premise that a finite collection of simple flows encapsulates the essential missing physics necessary to predict more complex scenarios. The BFM is designed to: (1) predict multiple flow regimes, (2) unify the closure model at solid boundaries and the rest of the flow, (3) ensure consistency with numerical schemes and gridding strategies by accounting for numerical errors, (4) be directly applicable to arbitrary complex geometries, and (5) be scalable to model additional flow physics in the future. The BFM is utilized to predict key quantities in five cases, including an aircraft in landing configuration, demonstrating similar or superior capabilities compared to previous state-of-the-art models. The design of BFM opens up new opportunities for developing closure models that can accurately represent various flow physics across different scenarios.

Wall-Modeled Large-Eddy Simulation Method for Unstructured-Grid Navier–Stokes Solvers

This paper reports on the implementation and assessment of a wall-modeled large-eddy simulation (WMLES) methodology in an unstructured-grid, node-centered flow solver, FUN3D, that is developed and supported at the NASA Langley Research Center. Finite-volume (FV) and finite-element (FE) discretization schemes considered in the study provide formal second-order spatial accuracy. Large-eddy simulations (LES) resolve large-scale turbulent-flow features, and small-scale effects are modeled using the Vreman subgrid-scale model. At solid-wall boundaries, a shear-stress model is employed to provide a proper boundary-flux closure. The nonlinear equations are integrated in time using either an optimized backward difference formula or an implicit multistage Runge–Kutta temporal scheme. The implicit equations at each time step are solved by strong nonlinear iteration schemes. WMLES demonstrations are shown for two high-lift configurations, namely, the McDonnell Douglas 30P30N multi-element airfoil and a NASA High-Lift Common Research Model. Results show that the WMLES approaches implemented in the FV and FE discretization methods produce consistent solutions and are capable of capturing key aerodynamic characteristics and flow structures for high-lift configurations at a wide range of angles of attack, including maximum-lift conditions. In the 30P30N example, correct trends in the variations of integrated aerodynamic forces and moments, surface pressure distributions, and boundary-layer profiles are captured as the Reynolds number is increased.

Numerical Investigation of Aero-Optical Distortions from High-Speed Turbulent Boundary Layers

Wall-modeled large-eddy simulations of turbulent boundary-layer flows over a flat plate at Mach 3.5, 7.87, and 13.64 were carried out, and the aero-optical distortions resulting from density fluctuations were investigated. The conditions for the Mach 3.5 case match those of a direct numerical simulation in the literature. The Mach 7.87 conditions are representative of the Hypersonic Wind Tunnel at Sandia National Laboratories, and the Mach 13.64 conditions match those of the Arnold Engineering Development Complex Hypervelocity Tunnel 9. The wall-modeled large-eddy simulations were validated using available experimental and DNS reference data. The normalized root-mean-square optical path difference for all three cases is in good agreement with respective data obtained from reference direct numerical simulations and experiments (within 1.53% for M∞=3.5, 1.25% for M∞=7.87, and 12% for M∞=13.64, compared to numerical data). Above M∞=5.0, the normalized path difference obtained from the simulations is above the value predicted by a semi-analytical relationship by Notre Dame University. With increasing Mach number, the bulk contribution to the total optical distortion shifts toward the boundary-layer edge. In addition, a proper orthogonal decomposition reveals that the nature of the dominant density fluctuations, which are located near the boundary-layer edge, changes from three-dimensional to two-dimensional. Understanding how the coherent structures contribute to the optical path difference may pave a way toward devising active flow control strategies geared toward a reduction of the optical path difference.

Physics-informed machine-learning solution to log-layer mismatch in wall-modeled large-eddy simulation

This study proposes a physics-informed machine learning to enable using the erroneous flow data at near-wall grid points as the input to the wall model in a wall-modeled large-eddy simulation (LES). The proposed neural network predicts the amount of numerical error in the near-wall grid-point data and inputs the physically correct flow variables into the wall model by correcting the near-wall error. The input and output features of the neural networks are selected based on the physical relations of the turbulent boundary layer for robustness against various Reynolds and Mach number conditions. The proposed neural networks allow the wall model to accurately predict the wall shear stress from the erroneous near-wall information and yields accurate predictions of the turbulence statistics. Additionally, the proposed physics-informed machine-learning approach reproduces the asymmetry in the probability density functions of the predicted wall shear stress observed in direct numerical simulations, while the conventional wall model with input away from the wall does not. The results suggest that using the near-wall information for wall modeling may increase the fidelity of the wall-modeled LES. Published by the American Physical Society 2024

Direct numerical simulation study on wall-modeling of turbulent water channel flows with temperature-dependent viscosity

We discuss wall-modeling of turbulent heat transfer of water channel flows with temperature-dependent viscosity via direct numerical simulations. We considered a top-cooled wall (293[K]) and a bottom-heated wall (353[K]) and varied the friction Reynolds numbers from 300 to 1000. The fluid viscosity varied depending on the local fluid temperature, whereas the other physical properties were assumed to be constant. The results show that semi-local scaling based on the local viscosity and wall friction velocity reasonably accounts for the effects of variable viscosity on turbulent flows, except in the vicinity of the wall, where wall cooling intensifies the turbulent vortical motion, leading to increased semi-locally scaled eddy diffusivities compared with those near the heated wall. In the vicinity of the cooled wall, turbulent transport is enhanced by increased viscous transport, which transfers more turbulent kinetic energy toward the cooled wall. The effectiveness of semi-local scaling for wall-modeling was validated by performing a wall-modeled large-eddy simulation at Reτ=1000, where we incorporated the semi-local viscous length scale into the classical mixing-length model. The modified mixing-length model reasonably reproduced the effects of variable viscosity on turbulent flows.

Reynolds-Number-Dependence of Length Scales Governing Turbulent-Flow Separation in Wall-Modeled Large Eddy Simulation

This paper proposes a Reynolds number Re scaling for the number of grid points Ncv required in wall-modeled Large Eddy Simulation (WMLES) of turbulent boundary layers (TBL) to accurately capture the regions of flow separation. Based on the various time scales in a nonequilibrium TBL, a definition of the near-wall “underequilibrium” scales is proposed (in which “equilibrium” refers to a quasi balance between the viscous and the pressure gradient terms). This length scale is shown to vary with Reynolds number as lp∼Re−2/3. A-priori analysis demonstrates that the resolution (Δ) required to reasonably predict the wall stress in several nonequilibrium flows is at least O(10)lp, irrespective of the Reynolds number and Clauser parameter. Further, a-posteriori studies (on the Boeing speed bump, Song– Eaton diffuser, Notre-Dame Ramp, and the backward-facing step) show that scaling Δ such that Δ/lp is independent of Reynolds number results in accurate predictions of separation for the same “nominal” grid across different Reynolds numbers. Finally, we suggest that near separation and reattachment points, Ncv for WMLES scale as Re4/3, which is more restrictive than the previous estimates (∼Re1) by Choi and Moin (Choi, H., and Moin, P., “Grid-Point Requirements for Large Eddy Simulation: Chapman’s Estimates Revisited,” Physics of Fluids, Vol. 24, No. 1, 2012, Paper 011702) and Yang and Griffin (Yang, X. I. A., and Griffin, K. P., “Grid-Point and Time-Step Requirements for Direct Numerical Simulation and Large-Eddy Simulation,” Physics of Fluids, Vol. 33, No. 1, 2021, Paper 015108).

Wall Modeling of Turbulent Flows with Varying Pressure Gradients Using Multi-Agent Reinforcement Learning

We propose a framework for developing wall models for large-eddy simulation that is able to capture pressure-gradient effects using multi-agent reinforcement learning. Within this framework, the distributed reinforcement learning agents receive off-wall environmental states, including pressure gradient and turbulence strain rate, ensuring adaptability to a wide range of flows characterized by pressure-gradient effects and separations. Based on these states, the agents determine an action to adjust the wall eddy viscosity and, consequently, the wall-shear stress. The model training is in situ with wall-modeled large-eddy simulation grid resolutions and does not rely on the instantaneous velocity fields from high-fidelity simulations. Throughout the training, the agents compute rewards from the relative error in the estimated wall-shear stress, which allows them to refine an optimal control policy that minimizes prediction errors. Employing this framework, wall models are trained for two distinct subgrid-scale models using low-Reynolds-number flow over periodic hills. These models are validated through simulations of flows over periodic hills at higher Reynolds numbers and flows over the Boeing Gaussian bump. The developed wall models successfully capture the acceleration and deceleration of wall-bounded turbulent flows under pressure gradients and outperform the equilibrium wall model in predicting skin friction.

Jet Installation Noise Modelling for Round and Chevron Jets

Wall-Modelled Large Eddy Simulations (LES) are conducted using a high-resolution CABARET method, accelerated on Graphics Processing Units (GPUs), for a canonical configuration that includes a flat plate within the linear hydrodynamic region of a single-stream jet. This configuration was previously investigated through experiments at the University of Bristol. The simulations investigate jets at acoustic Mach numbers of 0.5 and 0.9, focusing on two types of nozzle geometries: round and chevron nozzles. These nozzles are scaled-down versions (3:1 scale) of NASA’s SMC000 and SMC006 nozzles. The parameters from the LES, including flow and noise solutions, are validated by comparison with experimental data. Notably, the mean flow velocity and turbulence distribution are compared with NASA’s PIV measurements. Additionally, the near-field and far-field pressure spectra are evaluated in comparison with data from the Bristol experiments. For far-field noise predictions, a range of techniques are employed, ranging from the Ffowcs Williams–Hawkings (FW–H) method in both permeable and impermeable control surface formulations, to the trailing edge scattering model by Lyu and Dowling, which is based on the Amiet trailing edge noise theory. The permeable control surface FW–H solution, incorporating all jet mixing and installation noise sources, is within 2 dB of the experimental data across most frequencies and observer angles for all considered jet cases. Moreover, the impermeable control surface FW–H solution, accounting for some quadrupole noise contributions, proves adequate for accurate noise spectra predictions across all frequencies at larger observer angles. The implemented edge-scattering model successfully captures the mechanism of low-frequency sound amplification, dominant at low frequencies and high observer angles. Furthermore, this mechanism is shown to be effectively consistent for both M=0.5\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$M=0.5$$\\end{document} and M=0.9\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$M=0.9$$\\end{document}, and for jets from both round and chevron nozzles.

A numerical study of the wall-modeled large-eddy simulations of attached and separated flows with a semi-coupled synthetic turbulence generator

The predictive accuracy of the fluctuations inside turbulent boundary layers directly relies on the upstream turbulence synthesizer in wall-modeled large-eddy simulations (WMLESs). The conventional fully coupled synthetic turbulence generator (STG) strongly depends on the grid topology and simultaneous advancement of the unsteady Reynolds-averaged region. In this study, the two-stage semi-coupled STG, which is tolerant to the grid topology and is cost-effective due to the compatibility with precursor methods, was investigated. First, the semi-coupled STG efficiently generated artificial turbulence based on the existing benchmark data in the calculations of the fully developed channel flow. The adaptation length of the STG was less than ten boundary layer thicknesses by means of the Reynolds stresses and wall shear stresses, while the downstream turbulence was sufficiently “mature” for the predictions of more complex flows. The semi-coupled method with different wall-modeling strategies was validated for the mildly separated flow over a flat strut. The steady two-dimensional (2D) precursor data at the inlet were effectively utilized by the STG to generate turbulence and the monitored pressure fluctuations agreed well with the experimental data. Finally, the calculations of the flow around a wing–body junction showed that the algebraic wall-modeled large-eddy simulation demonstrated good accuracy in predicting the horseshoe vortex at the symmetry plane, and coherent structures rapidly developed from the artificial turbulence generated by the STG. To conclude, the WMLES with the semi-coupled STG can effectively predict the unsteady fluctuations in the attached and separated boundary layers. The compatibility of the semi-coupled STG with precursor methods and the relatively low computational cost of the WMLES can broaden the application areas of the STG method in complex flows at high Reynolds numbers.

Towards Wall-Resolved Large-Eddy Simulation of the High-Lift Common Research Model

In the present study, we performed a sixth-order wall-resolved large-eddy simulation (WRLES) of the high-lift Common Research Model (CRM-HL) on the Leadership Class Computing Cluster Summit. During the 4th High-Lift Prediction Workshop (HLPW-4), wall-modeled LES (WMLES) and hybrid Reynolds-averaged Navier–Stokes (RANS)/LES approaches showed promise in predicting the maximum lift and large flow separations near stall. In those simulations, however, laminar and transition regions were not resolved since the flow was assumed to be fully turbulent. If one wants to resolve these regions, the only viable approach is WRLES. The main purpose of the present study is to demonstrate the feasibility of WRLES for a complex real-world configuration at the wind tunnel Reynolds number. A high-order unstructured mesh LES solver called hpMusic was employed in the study. The simulation at solution polynomial order P=5 has more than 14 billion degrees of freedom per equation. Computational results are compared to experimental data in the form of surface oil flows and pressure coefficient profiles. We highlight lessons learned from attempting a grand-challenge type large-scale simulation: 1) such a simulation is feasible but very expensive, estimated to be at least three orders more expensive than WMLES, 2) oil flows produced with WRLES agree very well with experimental oil flows in fine detail, not observed in those produced with WMLES, and 3) flow visualization is a severe bottleneck, and parallel postprocessing capability is needed.

Large eddy simulation-based modeling of cold-air inhalation from nasal cavities to the distal lung: Insights for athlete health and performance

In cold environments, athletes are frequently susceptible to injuries from inhaling cold and dry air, posing significant health risks. Despite abundant prior research focusing on risk analysis and prevention, the existing body of literature has predominantly focused on heat transfer within lung airways while mainly overlooking the broader respiratory tract. This pioneering study introduces a comprehensive assessment of the entire respiratory system, spanning from the nasal and oral cavities to the larynx, then the trachea, and extending to the 13th generation of lung airways. Employing cutting-edge Computational Fluid Dynamics (CFD) techniques, the investigation operates Large Eddy Simulation (LES) integrated with an algebraic wall-modeled LES subgrid-scale model to simulate heat transfer within the human lung. This approach provides a detailed insight into the complex dynamics of respiratory thermoregulation in cold environments. By offering a comprehensive analysis of the temperature, heat flux, Nusselt number and static pressure profiles throughout the respiratory system, this study fundamentally advances our understanding of the physiological responses of the respiratory system to cold air exposure. These findings have paramount implications for athlete health and performance, shedding light on the complexities of cold-induced respiratory challenges. Moreover, this research lays a solid foundation for developing more effective preventive measures and strategies for optimizing athletic performance in cold weather conditions.

Cause-and-effect chain analysis of combustion cyclic variability in a spark-ignition engine using large-eddy simulation, Part I: From tumble compression to flame initiation

Understanding, modeling, and reducing the cycle-to-cycle variability (CCV) of combustion in internal combustion engines (ICE) is a critical challenge to design engines of high efficiency and low emissions. A high level of CCV may contribute to partial burn, misfire, and knock in extreme engine cycles, which affects engine performance and eventually damages the engine. The origins of CCV have been studied both experimentally and numerically, and the variability of in-cylinder aerodynamics is recognized as one of the most important sources of CCV. However, a detailed and quantitative explanation of how in-cylinder flow CCV is generated is not yet clear. The objective of the present study is to develop a methodology to localize inside the chamber of a spark-ignition engine (SIE) the origins of flow variabilities and to identify some driving mechanisms leading to combustion variabilities. Multi-cycle wall-modeled large-eddy simulations (LES) for the TU Darmstadt optical engine under fired conditions are performed using the CFD solver Converge 3.0. The evolution of organized large-scale structures and the small-scale turbulence of the in-cylinder flow are analyzed using a developed methodology that includes the empirical mode decomposition (EMD) method adapted for 2D and 3D flow fields, and a vortex identification tool Γ3p. The contributions of different parts of the flow to CCV are quantified. In Part I of this work, the LES framework is validated against experimental data, and CCV of large-scale structures is characterized at spark timing. In Part II, the overall flow development during compression and intake strokes are quantitatively analyzed, and links are built between different engine phases to establish the cause-and-effect chain. Other CCV factors, such as spray injection and exhaust gas recirculation, are not included in the current study. However, the developed methodology for in-cylinder flow analysis could be used in studies on other engine configurations to improve the development of engine designs.Novelty and significance statementIn this work, the cycle-to-cycle variability (CCV) of combustion in a spark ignition engine is investigated to give a deeper understanding of CCV generation. The present study focuses on CCV caused by the stochastic nature of internal turbulent flow structures. LES approach is chosen due to its ability to capture CCV. The LES methodology was validated in a motored case in Ding et al. (2023). In the present study, it is validated in a reactive case against experimental in-cylinder pressures and velocity fields.A first novelty is the application of EMD methods combined with topology-based techniques to reactive LES results to characterize flow structures of different scales in the three-dimensional domain and to quantify separately their impacts on combustion.A second novelty and important finding is that a link is established between the combustion speed and the tumble formation and destabilization near BDC.Throughout our analyses in Part I and II, starting from the spark-ignition timing and going back to the early intake phase, a cause-and-effect chain is finally established between the development of in-cylinder flow and the combustion variability.

URANOS-2.0: Improved performance, enhanced portability, and model extension towards exascale computing of high-speed engineering flows

We present URANOS-2.0, the second major release of our massively parallel, GPU-accelerated solver for compressible wall flow applications. This latest version represents a significant leap forward in our initial tool, which was launched in 2023 (De Vanna et al. [1]), and has been specifically optimized to take full advantage of the opportunities offered by the cutting-edge pre-exascale architectures available within the EuroHPC JU. In particular, URANOS-2.0 emphasizes portability and compatibility improvements with the two top-ranked supercomputing architectures in Europe: LUMI and Leonardo. These systems utilize different GPU architectures, AMD and NVIDIA, respectively, which necessitates extensive efforts to ensure seamless usability across their distinct structures. In pursuit of this objective, the current release adheres to the OpenACC standard. This choice not only facilitates efficient utilization of the full potential inherent in these extensive GPU-based architectures but also upholds the principles of vendor neutrality, a distinctive characteristic of URANOS solvers in the CFD solvers' panorama. However, the URANOS-2.0 version goes beyond the goals of improving usability and portability; it introduces performance enhancements and restructures the most demanding computational kernels. This translates into a 2× speedup over the same architecture. In addition to its enhanced single-GPU performance, the present solver release demonstrates very good scalability in multi-GPU environments. URANOS-2.0, in fact, achieves strong scaling efficiencies of over 80% across 64 compute nodes (256 GPUs) for both LUMI and Leonardo. Furthermore, its weak scaling efficiencies reach approximately 95% and 90% on LUMI and Leonardo, respectively, when up to 256 nodes (1024 GPUs) are considered. These significant performance advancements position URANOS-2.0 as a state-of-the-art supercomputing platform tailored for compressible wall turbulence applications, establishing the solver as an integrated tool for various aerospace and energy engineering applications, which can span from direct numerical simulations, wall-resolved large eddy simulations, up to most recent wall-modeled large eddy simulations. Program summaryProgram title: Unsteady Robust All-around Navier-StOkes Solver (URANOS)CPC Library link to program files:https://doi.org/10.17632/pw5hshn9k6.2Developer's repository link:https://github.com/uranos-gpu/uranos-gpu, https://github.com/uranos-gpu/uranos-gpu/tree/v2.0Licensing provisions: BSD License 2.0Programming language: Modern Fortran, OpenACC, MPINature of problem: Solving the compressible Navier-Stokes equations in a three-dimensional Cartesian framework.Solution method: Convective terms are treated with high-resolution shock-capturing schemes. The system dynamics is advanced in time with a three-stage Runge-Kutta method. Parallelization adopts MPI+OpenACC.

Assessment of longitudinal dispersion and flow resistance near floodplains through riparian woodlands

Riparian woodlands prevent bank erosions, recycle minerals, sustain biodiversity, act as flow resistance on floodplains, and filter pollutants. The emergent trees characterize woodlands with different spacing arrangements that dictate flow resistance and longitudinal dispersion of the pollutants in compound channel flow. The single- and multistage compound channels exist in urban and natural watercourses with riparian and transplanted trees on different stages of the floodplain. This study numerically validates the planting of vegetation in lines on single- and multistage floodplains using a wall-modeled large-eddy simulation model. Post-validation, the focus of the study was to assess the hydrodynamic behavior and mixing around the floodplain and main channel section of different tested configurations. The approximation of flow structures for the various configurations of tree plantations shows stronger vortices with significant characteristic length scales for floodplains closer to the main channel. The intensity of the secondary current is higher for denser planted trees at junctions of floodplains. For higher flow events, drag force contributions for staged floodplains with trees on both stages are 45–41%, and trees on the top stage contribute 27-22% to the total frictional force budget. The subsequent investigation shows that the in-line trees geometrical configuration and spacing arrangement on the floodplain dictates flow resistance and longitudinal dispersion of the pollutants and contamination in channel flow. The results show that the overall reduction in discharge for floodplains with tree planting is 19.8–36.2% for single-stage and 10.4–23.6% for multistage compound channels. The longitudinal dispersion coefficients for each multi-zone model predict a 61% and 41% dispersion reduction, respectively, in single- and multistage floodplains with planted trees. Floodplains with denser tree spacing have a maximum zonal discharge reduction of 45% for a single-stage and 27.2% and 28.0% for multistage channels. These findings strongly suggest that the planting parameters of spacing-to-diameter ratio and floodplain geometry play a pivotal role in floodplain management from the perspective of contaminant dispersion and flood risk reduction during high-flow events.

High-Order Wall-Modeled Large-Eddy Simulation of High-Lift Configuration

This paper presents the assessment of several recent enhancements for a high-order wall-modeled large-eddy simulation (WMLES) approach and demonstrates order independence with a fixed data exchange location in the wall model. The two enhancements include the use of isotropic tetrahedral elements to improve accuracy and an explicit subgrid-scale model, the Vreman model, to improve accuracy and robustness. The P-refinement study focused on the high-lift Common Research Model (HL-CRM) at the angle of attack of 19.57 deg, a benchmark problem from the 4th AIAA High-Lift Prediction Workshop. Solution polynomial orders of P=2, 3, 4, and 5 were used in the study. The study demonstrated p independence in integrated forces, pitch moment, velocity profile in the wall-normal direction, and surface flow topology. It also showed that a P order of at least 3 (P3) was needed to correctly predict the external inviscid flow and the surface flow topology. Thereafter, P3 simulations over several other angles of attack demonstrated that the high-order WMLES approach can correctly predict the maximum lift and flow separation regions for HL-CRM with about 40 million degrees of freedom (DOF) compared to at least 250 million DOF required by second-order methods.