Use Of Large Eddy Simulation Research Articles

Standardized Daily High‐Resolution Large‐Eddy Simulations of the Arctic Boundary Layer and Clouds During the Complete MOSAiC Drift

AbstractThis study utilizes the wealth of observational data collected during the recent Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) drift experiment to constrain and evaluate close to two‐hundred daily Large‐Eddy Simulations (LES) of Arctic boundary layers and clouds at high resolutions. A standardized approach is adopted to tightly integrate field measurements into the experimental configuration. Covering the full drift represents a step forward from single‐case LES studies, and allows for a robust assessment of model performance against independent data under a range of atmospheric conditions. A homogeneously forced domain is simulated in a Lagrangian frame of reference, initialized with radiosonde and value‐added cloud profiles. Prescribed boundary conditions include various measured surface characteristics. Time‐constant composite forcing is applied, primarily consisting of subsidence rates sampled from reanalysis data. The simulations run for 3 hours, allowing turbulence and clouds to spin up while still facilitating direct comparison to MOSAiC data. Key aspects such as the vertical thermodynamic structure, cloud properties, and surface energy fluxes are well reproduced and maintained. The model captures the bimodal distribution of atmospheric states that is typical of Arctic climate. Selected days are investigated more closely to assess the model's skill in maintaining the observed boundary layer structure. The sensitivity to various aspects of the experimental configuration and model physics is tested. The model input and output are available to the scientific community, supplementing the MOSAiC data archive. The close agreement with observed meteorology justifies the use of LES for gaining further insight into Arctic boundary layer processes and their role in Arctic climate change.

CFD Simulation of Stirling Engines: A Review

Stirling engines (SEs) have long attracted the attention of renewable energy researchers due to their external combustion design and flexibility in operating with various heat sources. The mathematical analysis of these devices is conducted by using a broad range of models ranging from basic zero-order to highly detailed fourth-order models, which are implemented through Computational Fluid Dynamics (CFD) simulations. The unique features of this last approach, combined with the increase in computing power, have promoted the use of CFD as a tool for analyzing SEs in recent years, significantly reducing the costs associated with prototype construction. However, Stirling CFD simulations are sophisticated due to the variety of physical phenomena involved, such as volume change, conjugated heat transfer, turbulent compressible fluid dynamics, and flow through porous media in the regenerator. Furthermore, there is currently no comprehensive review of CFD simulations of SEs in the literature; therefore, this contribution aims to fill that gap. Emphasis has been placed on identifying the type of engine, the physical phenomena modeled, the simplifying assumptions, and specific numerical aspects, such as mesh type, spatial and temporal discretization, and the order of the numerical schemes used. As a result, it has been found that in many cases, CFD numerical reports lack sufficient detail to ensure the reproducibility of the simulations. This work proposes guidelines for reporting CFD studies on Stirling engines to address this issue. Additionally, the need for a sufficiently detailed experimental benchmark database to validate future CFD studies is stressed. Finally, the use of Large Eddy Simulations on coupled key engine components—such as compression and expansion spaces, pistons, displacer, and regenerator—is suggested to provide further insights into the specific flow and heat transfer characteristics in Stirling engines.

Forced air flow through a rectangular channel with 3D turbulence enhancers: fluid-dynamics and thermal analysis by Large Eddy Simulations

Many newer engineering applications, like the cooling of automotive batteries and high-performance CPUs, require heat exchangers (HEs) with large contact areas and very small heights. Performances of this type of HEs can be significantly improved by using surfaces enhanced with optimized 3D structures. The project Mood4hex aims at designing new geometries with optimized morphology, starting from a large database of experimental data on ribbed surfaces. In order to perform an optimization algorithm on such surfaces, analyses are carried out on CFD models with increasing complexity and computational time, to find a fast-running code that preserves the physical meaning. Until recently we used RANS models, and now we began to investigate the use of Large Eddy Simulations (LES) as a higher order validation tool for simpler models. In this paper, we present the results of LES along with experimental data of a forced air flow inside a streamwise periodic rectangular channel of high aspect ratio, i.e., 1:10, equipped with standard transverse ribs (α = 90°). More specifically, the ribs are placed only on the lower wall that is operated at constant heat flux, while air flowing at Re 500 or 1000. Comparison of experimental data vs LES results shows weaknesses and strengths of the model.

Autonomous large-eddy simulations of turbulence using eddy viscosity derived from the subgrid-scale similarity stress tensor

A previously developed method for large-eddy simulations (LES), based on spectral eddy-viscosity models, is generalised to the physical space representation. The method estimates the subgrid-scale (SGS) energy transfer using a similarity-type model expression for the SGS tensor obtained using Gaussian filtering of velocity fields advanced in the simulations. Following steps for the spectral space representation, the SGS transfer in the physical space is used to obtain a spatially varying eddy viscosity at each time step in LES. The computed eddy viscosity is employed to model the SGS stress tensor in the familiar Boussinesq form for use in LES. The method is tested in LES of isotropic turbulence at high Reynolds numbers where the inertial range dynamics is expected and for lower Reynolds number decaying turbulence under conditions of the classical Comte-Bellot and Corrsin experiments. In both cases the agreement with reference data is very good and the SGS transfer computed for the proposed eddy-viscosity model is highly correlated with the transfer computed for the similarity-type stress tensor.

Parametric study of large-eddy simulation to capture scaling laws of velocity fluctuations in neutral atmospheric boundary layers

The development of digital twins for wind farms often involves the use of large-eddy simulation (LES) to model atmospheric boundary layers. Existing LES solvers primarily focus on accurately capturing streamwise fluctuations. They, however, overlook the less energetic cross-stream fluctuations, which play a crucial role in wind turbine wake evolution. In this study, we conduct a systematic parametric study and incorporate changes in an open-source LES solver. The improved solver is able to predict all three components of velocity fluctuations in alignment with the scaling laws derived from the attached-eddy hypothesis. In particular, we examine the impact of (i) the subgrid-scale model, (ii) the wall model, (iii) the von Kármán constant, and (iv) the grid-cell aspect ratio. We find that although all these factors influence the prediction of velocity fluctuations, the grid-cell aspect ratio has the greatest effect on the spanwise and vertical velocity components. Notably, utilizing nearly isotropic grid cells leads to the best alignment of all three velocity component fluctuations with the scaling laws. Spectral analysis further demonstrates that the present LES solver accurately predicts the characteristic length scales for all velocity fluctuation components, making it a reliable tool for obtaining turbulent inflow conditions for wind farm modeling.

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.

A Review of Large-Eddy Simulation Cell Size Requirements for Indoor Flows

Nowadays computational fluid dynamics now assists ventilation system designers and architects in understanding the induced flow behaviour in the indoor environment. The use of large-eddy simulation is a novel methodology for these types of assessments. The method requires that the computational domain be adequately discretized in order to resolve the majority of the flow. The last five years of publications of Elsevier, SAGE, and Multidisciplinary Digital Publishing Institute were screened. Indoor flow categories were utilized to assess the differences. Based on the papers reviewed, the cell size requirement was considered as a key factor of computational demand. Specifications were made for each type of indoor flow simulation.

Toward the use of LES for industrial complex geometries. Part II: Reduce the time-to-solution by using a linearised implicit time advancement

The strong increase in computational power observed during the last few years has allowed to use Large Eddy Simulation (LES) for industrial configurations. Nevertheless, the time-to-solution is still too large for a daily use in the design phases. The objective of this work is to develop a new time integration method to reduce the time-to-solution of LES of incompressible flows by allowing the use of larger time step. The projection method, probably the most commonly used method in the context of LES of incompressible flow, is generally applied using explicit time advancement which constrains the time-step value for stability reasons (CFL and Fourier constraints). The time step can then be small with respect to the physical characteristic times of the studied flow. In this case, an implicit time advancement method, which is unconditionally stable, can be used. However, this leads to non-linear resolution of momentum equation which can strongly increase time-to-solution because of non-linear iterations inside a physical iteration. To relax the stability constraints while minimising the computational cost of an iteration, a linearised implicit time advancement based on Backward Differentiation Formula (BDF) scheme is proposed in this work. The linearisation is performed using an extrapolated velocity field based on the previous fields. This time integration is first evaluated on a turbulent pipe test case. It is observed a time-to-solution up to five times lower than the explicit time integration while keeping the same accuracy in terms of mean and fluctuating velocity fields. To incorporate this new time advancement method in the automatic mesh convergence developed in Part I, a time-step control method based on the local truncation error is used. The resulting automatic time-step and mesh procedure is evaluated on a turbulent round jet case and on PRECCINSTA configuration, a swirl burner which is a representative case of an industrial aeronautical injection system. This new procedure leads to a time-to-solution up to three times lower than the previous procedure, presented in Part I.

Toward the use of LES for industrial complex geometries. Part I: automatic mesh definition

With the constant increase of computational power for the past years, Computational Fluid Dynamics (CFD) has become an essential part of the design in complex industrial processes. In this context, among the scale resolving numerical methods, Large-Eddy Simulation (LES) has become a valuable tool for the simulation of complex unsteady flows. To generalise the industrial use of LES, two main limitations are identified. First, the generation of a proper mesh can be a difficult task, which often relies on user-experience. Secondly, the ‘time-to-solution’ associated with the LES approach can be prohibitive in an industrial context. In this work, these two challenges are addressed in two parts. In this Part I, an automatic procedure for mesh definition is proposed, whereas the Part II is devoted to numerical technique to reduce the LES ‘time-to-solution’. The main goal of these works is then to develop an accurate LES strategy at an optimised computational cost. Concerning the mesh definition, because LES is based on separation between resolved and modelled subgrid-scales, the quality of the computed solution is then directly linked to the quality of the mesh. However, the definition of an adequate mesh is still an issue when LES is used to predict the flow in an industrial complex geometry without a priori knowledge of the flow dynamics. This first part presents a user-independent approach for both the generation of an initial mesh and the convergence of the mesh in the LES framework. An automatic mesh convergence strategy is proposed to ensure LES accuracy. This strategy is built to guarantee a mesh-independent mean field kinetic energy budget. The mean field kinetic energy is indeed expected to be mesh independent since only turbulent scales should be unresolved in LES. The approach is validated on canonical cases, a turbulent round jet and a turbulent pipe flow. Finally, the PRECCINSTA swirl burner is considered as a representative case of complex geometry. First, an algorithm for the generation of an unstructured mesh from a STL file is proposed to generate a coarse initial mesh, before applying the mesh convergence procedure. The overall strategy including automatic first mesh generation and its automatic adaptation paves the way to use LES approach as a decision support tool for various applications, provided that the ‘time-to-solution’ is compatible with the applications constraint. A second paper, referred as Part II, is devoted to the reduction of this time.

How Fast is Fast Enough? Industry Perspectives on the Use of Large-eddy Simulation in Wind Energy

The use of graphics processing units (GPUs) has facilitated unprecedented performance gains for computational fluids dynamics in recent years. In many industries this has enabled the integration of large-eddy simulation (LES) in the engineering practice. Flow modelling in the wind industry though still primarily relies on models with significantly lower fidelity. This paper seeks to investigate the reasons why wind energy applications of LES are still an exception in the industrial practice. On that account, we present a survey among industry experts on the matter. The survey shows that the large runtimes and computational costs of LES are still seen as a main obstacle. However, other reasons such as a lack of expertise and user experience, the need for more validation, and lacking trust in the potential benefits of LES reveal that computational efficiency is not the only concern. Lastly, we present an exemplary simulation of a generic offshore wind farm using a GPU-resident Lattice Boltzmann LES framework. The example shows that the runtime requirements stated by a large part of the respondents can already now be fulfilled with reasonable hardware effort.

Analysis of Upstream Turbulence Impact on Wall Heat Transfer in an Acoustic Liner with Large-Eddy Simulations

Acoustic liners of aircraft fan ducts generate synthetic jets that interact with the boundary layer of the incident grazing flow. Such an interaction leads to complex wall heat transfer, which has been scarcely studied. The objective of the present work is to evaluate the flow dynamics and the heat transfer mechanisms that occur in acoustic liners by the use of Large-Eddy Simulations. To do so, two configurations, linked by a principle of similarity, are considered: a lab-scale one, for which dimensions have been multiplied by a factor of 6.25 to ease measurements, and an engine-scale configuration. The lab-scale configuration is used to validate the numerical methodology and, although some limitations are pointed out, the similitude is validated. As a main outcome of these detailed simulations, synthetic jets are found to completely drive the flow dynamics in the jet wakes. Upstream turbulence is also shown to impact the development of the first jet rows as well as the wall heat transfer between jets.

Random Errors in the Stable Boundary Layer: Implications for Modern Observational Techniques

Abstract For decades, stable boundary layer (SBL) turbulence has proven challenging to measure, parameterize, simulate, and interpret. Uncrewed aircraft systems (UAS) are becoming a reliable method to sample the atmospheric boundary layer, offering new perspectives for understanding the SBL. Moreover, continual computational advances have enabled the use of large-eddy simulations (LES) to simulate the atmosphere at ever-smaller scales. LES is therefore a powerful tool in establishing a baseline framework to understand the extent to which vertical profiles from UAS can represent larger-scale SBL flows. To quantify the representativeness of observations from UAS profiles and eddy-covariance observations within the SBL, we performed a random error analysis using a suite of six large-eddy simulations for a wide range of stabilities. We combine these random error estimates with emulated observations of a UAS and eddy-covariance systems to better inform future observational studies. For each experiment, we estimate relative random errors using the so-called relaxed filtering method for first- and second-order moments as functions of height and averaging time. We show that the random errors can be on the same order of magnitude as other instrument-based errors due to bias or dynamic response. Unlike instrument errors, however, random errors decrease with averaging time. For these reasons, we recommend coupling UAS observations with other ground-based instruments as well as dynamically adjusting the UAS vertical ascent rate to account for how errors change with height and stability. Significance Statement Weather-sensing uncrewed aircraft systems are rapidly being realized as effective tools to collect valuable observations within the atmospheric boundary layer. To fully capitalize on this novel observational technique, it is necessary to develop an understanding of how well their observations can represent the surrounding atmosphere across various spatial and temporal scales. In this study we quantify the representativeness of atmospheric observations in the stable boundary layer by evaluating the random errors for parameters such as temperature, wind speed, and fluxes as estimated from a suite of large-eddy simulations. Our results can better inform future studies utilizing uncrewed aircraft systems by highlighting how random errors in their observations relate to vertical ascent rate, atmospheric stability, and measurement height.

LES prediction of transitional flows in LP turbine cascades: effects of blade loading, flow phenomena and numerical setup

This paper presents detailed validations of a Large Eddy Simulation (LES) methodology for various transitional phenomena in low pressure turbines. The results are discussed to identify key phenomena to be resolved accurately toward future industrial use of LES. Detailed comparisons between experimental and CFD results are made on three different 2D cascades with different blade loading. One is low-lift and fully laminar design, while the others are moderate- and high-lift designs with boundary layer transition. The experimental data are obtained in a low speed linear cascade at Iwate University. All computations are conducted by a carefully-designed overset LES code. For the high-load design with a distinct laminar separation on the suction side, the LES result shows satisfactory agreement with the test. However, although the peak of total pressure loss distribution is predicted quite accurately, integrated cascade losses are over-predicted in the other two cases. For the laminar blade, the LES result implies some differences can exist in the state of wake, while the transitional blade shows delay of transition in the boundary layer. The effects of inflow turbulence intensity, length scale, and stream tube contraction are discussed in detail to improve LES prediction.

LES-CHT for a Rotating Cavity With Axial Throughflow

Abstract The flow and heat transfer within rotating cavities is often discussed as a conjugate problem; the temperature distribution within the cavity disks drives the large-scale flow structure within the cavity, and the cavity aerodynamics influence the heat transfer to the disks. However, most simulations of rotating cavities only consider the fluid domain in isolation. This is particularly true for turbulence resolving approaches such as large eddy simulation (LES). The large time-scale disparity between the fluid time-steps used in LES and the characteristic solid time-scale complicates the use of LES with conjugate heat transfer (CHT). A further issue is that an under-resolved solid mesh artificially amplifies higher frequency temperature fluctuations from the fluid. This paper addresses these challenges with a new method for LES-CHT where the low frequency temperature fluctuation caused by the large-scale flow structure is accounted for using a multi-scale frequency domain approach. We investigate two cases: axially heated disks made of a low conductivity material, and disks made from a higher conductivity material with a temperature set by radial conduction from the shroud. The formation of small-scale flow structures on both the disk and shroud is dependent on the heating configuration of the cavity—indicating that high-fidelity thermal boundary conditions should be used when simulating rotating cavities. The formation of heating induced vortical flow structures near the disk is particularly interesting, as this is unexpected from the laminar Ekman layer modeling argument usually used to consider this region.

Grain-scale computations of barchan dunes

Barchans are crescent-shaped dunes commonly found in diverse environments and scales: from the 10-cm-long barchans found under water to the 1-km-long barchans on Mars, passing by the 100-m-long dunes on Earth's deserts. Although ubiquitous in nature, there is a lack of grain-scale computations of the growth and evolution of those bedforms. In this paper, we investigate the values of grain properties (coefficients of sliding friction, rolling friction, and restitution) necessary to carry out numerical simulations of subaqueous barchans with CFD–DEM (computational fluid dynamics–discrete element method), and how the values of those coefficients change the barchan dynamics. We made use of LES (large eddy simulation) for the fluid, varied the coefficients of sliding friction, rolling friction, and restitution in the DEM, and compared the outputs with experiments. We show (i) for the case of glass spheres, the values of coefficients for correctly obtaining the dune morphology, timescales, trajectories of individual grains, and forces experienced by grains; (ii) the LES meshes allowing computations of bedload while capturing the main disturbances of the fluid flow; (iii) how different values of coefficients affect the morphology of barchans; and (iv) that spheres with higher coefficients of rolling friction can be used for simulating barchans consisting of angular grains. Our results represent a significant step for performing simulations that capture, at the same time, details of the fluid flow (large eddies) and grains' motion (individual particles).

Large-Eddy Simulation of Hydrodynamic Structure in a Strongly Curved Bank

Advances in computer technology have facilitated the use of large-eddy simulation (LES) as a numerical simulation method in fluid mechanics. In this study, LES was used for the numerical simulation of curved water flow with a large curvature. The simulation results show that water separation occurs near the convex bank of the bend transverse section while the separation area increases and then decreases along the water depth direction, where the peak is at half-depth. As the water surface is affected by air shear stress, the velocity decreases. However, as the gradient increases, the vorticity is larger and the vorticity distribution is more even. Reflux occurs in the inlet and outlet sections of the bend but does not occur on the surfaces of z/H = 0.5 and z/H = 0.2, where the vorticity distribution is uneven. In the narrow corridor of the concave and convex banks, notably near the curved top, vorticity distribution is concentrated with a high intensity. At the center of the curve, the vorticity intensity is weak but 10 times higher at the concave and convex banks. A strong correlation exists between circulation structure and vorticity distribution: the vorticity is large where the circulation is intense and the structure is complex.

Use of large-eddy simulations to design an adaptive sampling strategy to assess cumulus cloud heterogeneities by remotely piloted aircraft

Abstract. Trade wind cumulus clouds have a significant impact on the Earth's radiative balance due to their ubiquitous presence and significant coverage in subtropical regions. Many numerical studies and field campaigns have focused on better understanding the thermodynamic, microphysical, and macroscopic properties of cumulus clouds with ground-based and satellite remote sensing as well as in situ observations. Aircraft flights have provided a significant contribution, but their resolution remains limited by rectilinear transects and fragmented temporal data for individual clouds. To provide a higher spatial and temporal resolution, remotely piloted aircraft (RPA) can now be employed for direct observations using numerous technological advances to map the microphysical cloud structure and to study entrainment mixing. In fact, the numerical representation of mixing processes between a cloud and the surrounding air has been a key issue in model parameterizations for decades. To better study these mixing processes as well as their impacts on cloud microphysical properties, the paper aims to improve exploration strategies that can be implemented by a fleet of RPA. Here, we use a large-eddy simulation (LES) of shallow maritime cumulus clouds to design adaptive sampling strategies. An implementation of the RPA flight simulator within high-frequency LES outputs (every 5 s) allows tracking individual clouds. A rosette sampling strategy is used to explore clouds of different sizes that are static in time and space. The adaptive sampling carried out by these explorations is optimized using one or two RPA and with or without Gaussian process regression (GPR) mapping by comparing the results obtained with those of a reference simulation, in particular the total liquid water content (LWC) and the LWC distribution in a horizontal cross section. Also, a sensitivity test of length scale for GPR mapping is performed. The results of exploring a static cloud are then extended to a dynamic case of a cloud evolving with time to assess the application of this exploration strategy to study the evolution of cloud heterogeneities. While a single RPA coupled to GPR mapping remains insufficient to accurately reconstruct individual clouds, two RPA with GPR mapping adequately characterize cloud heterogeneities on scales small enough to quantify the variability of important parameters such as total LWC.

Numerical characterization of a novel test bench featuring secondary reactions of methane

Recently, a novel test bench was developed at the Bundeswehr University of Munich in order to study secondary near-wall reactions caused by cold injection of methane into an oxygen-rich hot crossflow. The available measurements of the experiment, namely Laser Induced Fluorescence (LIF) of OH allowed to locate the reaction zone and to estimate the autoignition length, while the heat load prediction at the wall was calculated from the thermocouple readings using the inverse heat transfer method. A numerical investigation of this test bench is presented in this work. In the first part, non-reactive Large Eddy Simulations (LES) are used to evaluate the turbulent boundary conditions of the reactive test rig. The use of LES provides an insight in the distribution of velocity, turbulence intensity, temperature and species within the hot flow generator (burner), the fuel injection nozzles and the inlet of the reactive test rig. In the second part, reactive LES computations are used for comparison of the autoignition length and the wall heat fluxes with the experimental data, based on the boundary conditions provided by the non-reactive LES. The results show that in this configuration the autoignition length is more strongly affected by the hot gas inlet temperature than by the turbulent fluctuations of the crossflow. The qualitative comparison with the autoignition length assessed from the experiment is satisfactory and a wall heat flux distribution similar to the experimental distribution is obtained downstream the fuel injection nozzles.

Synthetic near-wall small-scale turbulence and its application in wall-modeled large-eddy simulation

A suitable representation of the universal near-wall small-scale motions helps the understanding of physical mechanisms as well as the development of simulation techniques of wall turbulence. Minimum flow unit (MFU) as a reduced-order model of wall turbulence serves the purpose, but requires non-trivial computational cost. Motivated by improving the MFU-based near-wall turbulence prediction model [Yin et al., “Prediction of near-wall turbulence using minimal flow unit,” J. Fluid Mech. 841, 654–673 (2018)] for better use in large-eddy simulations (LES), the present study seeks to supply near-wall small-scale turbulence fluctuations with synthetic flow fields generated from universal model of MFU, thus avoiding the auxiliary simulation and lowering the computational cost. We first obtain MFU data ranging from Reτ=2000 to 8000 using direct numerical simulations and reconstruct 3-dimensional space–time spectra of MFU using the generalized local modulated wave method. The space–time spectra serve as the universal model of near-wall small-scale turbulence. We then propose a method to generate turbulent flow fields from space–time spectra, based on the synthetic random Fourier method. The generated flow is statistically consistent with and structurally similar to the authentic MFU. At last, the generated flow fields at different Reynolds numbers are applied to LES of off-wall channels, and the reasonable results obtained suggest that our synthetic near-wall small-scale turbulence is as effective as authentic MFU in constructing off-wall boundary conditions.

Numerical Simulation of a Three-Dimensional Axisymmetric Hill: Performance Evaluation of Hybrid RANS–LES Models

Abstract Computational fluid dynamics (CFD) simulation of flow over a three-dimensional (3D) axisymmetric hill presents a unique set of challenges for turbulence modeling. The flow past the crest of the hill is characterized by boundary layer separation, complex vortical structures, and unsteady wake flow. As a result, traditional eddy-viscosity Reynolds-averaged Navier–Stokes (RANS) models have been found to perform poorly for this benchmark test case. Recent studies have focused on the use of large eddy simulation (LES) and hybrid RANS–LES (HRL) methods to improve accuracy. In this study, several different HRL models are investigated, and results from the different models are evaluated relative to each other, to an eddy-viscosity RANS model, and to previously documented high-fidelity LESs and experimental data. Results obtained from the simulations in terms of mean flow statistics, surface pressure distribution, and turbulence characteristics are presented and discussed in detail. Results indicate that eddy-viscosity based HRL models can improve predictions over comparable eddy-viscosity based RANS models such as the shear stress transport (SST) k–ω model used in this study, but only when the development of turbulent velocity fluctuations in the separated shear layer and recirculation region are well resolved.