Large Eddy Simulation Predictions Research Articles

Sensitivity analysis of wall-modeled large-eddy simulation for separated turbulent flow

In this study, we conduct a parametric analysis to evaluate the sensitivities of wall-modeled large-eddy simulation (LES) with respect to subgrid-scale (SGS) models, mesh resolution, wall boundary conditions and mesh anisotropy. While such investigations have been conducted for attached/flat-plate flow configurations, systematic studies specifically targeting turbulent flows with separation are notably sparse. To bridge this gap, our study focuses on the flow over a two-dimensional Gaussian-shaped bump at a moderately high Reynolds number, which involves smooth-body separation of a turbulent boundary layer under pressure-gradient and surface-curvature effects. In the simulations, the no-slip condition at the wall is replaced by three different forms of boundary condition based on the thin boundary layer equations and the mean wall-shear stress from high-fidelity numerical simulation to avoid the additional complexity of modeling the wall-shear stress. Various statistics, including the mean separation bubble size, mean velocity profile, and dissipation from SGS model, are compared and analyzed. The results reveal that capturing the separation bubble strongly depends on the choice of SGS model. While simulations approach grid convergence with resolutions nearing those of wall-resolved LES meshes, above this limit, the LES predictions exhibit intricate sensitivities to mesh resolution. Furthermore, both wall boundary conditions and the anisotropy of mesh cells exert discernible impacts on the turbulent flow predictions, yet the magnitudes of these impacts vary based on the specific SGS model chosen for the simulation.

LES Modeling of the DLR Generic Single-Cup Spray Combustor: Validation and the Impact of Combustion Chemistry

AbstractTurbulent spray combustion in a generic kerosene-fueled single-cup combustor at typical idle and cruise conditions of an aeroengine are studied with Large Eddy Simulations (LES) using Lagrangian spray and finite-rate chemistry combustion modeling. Three reaction mechanisms of varying complexity are used to model the combustion chemistry. The choice of turbulence-chemistry interaction model is shown to affect the results significantly. The impact of the choice of chemical reaction mechanism and the difference in operating conditions are gauged in terms of time-averaged flow, spray, and combustion characteristics as well as unsteady behavior. Good agreement between LES predictions and experimental results are generally observed but with a notable dependence on the choice of chemical reaction mechanism. The mechanism specifically targeting Jet A displays the best agreement. The choice of reaction mechanism is further demonstrated to influence the flow and thermoacoustics in the combustor, resulting in different thermoacoustic modes dominating. The spray cone is found to be too narrow and thin, an inaccuracy which could be remedied by either making the injection method more empirical or by introducing additional models.

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.

Large Eddy Simulation of cavity stabilized ramjet combustion

In this study we use finite rate chemistry Large Eddy Simulation (LES) to examine flow, injection, mixing, self-ignition and turbulent combustion in a dual-mode ramjet combustor with a cavity flameholder. The target case is the dual-mode ramjet combustor studied experimentally by Micka & Driscoll in a series of publications under different operating conditions characterized by varying air stagnation temperatures, T0, and fueled with hydrogen or hydrogen-ethylene blends. Here, only hydrogen fuel is considered. Three skeletal and comprehensive chemical reaction mechanisms are used to evaluate the influence of the reaction mechanism. Based on comparisons with ignition, laminar flame, and dual-mode ramjet combustor experiments the Z22 mechanism is found superior to the D7 and J20 mechanisms, which is then used throughout this study. For the ramjet experiments, two stabilization modes were reported: cavity-stabilized combustion at low T0 and jet-wake-stabilized combustion at high T0. For in-between values of T0, combustion oscillates between these modes. The LES results using the Z22 reaction mechanism are in good agreement with the experimental data: cavity-stabilized combustion is observed for low T0, and for this case combustion anchors at the leading-edge of the cavity. For high T0 jet-wake-stabilized combustion occurs in the near-wake of the fuel-plume. Between these two modes, combustion oscillates between modes that can be roughly identified as jet-wake and cavity stabilized. The LES predictions also reveal details about high-frequency oscillations (∼1 kHz) that are observed in particular for low and intermediate T0. The H2-air mixture appears to burn as an auto-ignition assisted premixed flame in the cavity-stabilized case, and as a diffusion-flame in the jet-wake stabilized case, whereas for the in-between cases, the burning modes changes accordingly.

Deep learning closure models for large-eddy simulation of flows around bluff bodies

Near-wall flow simulation remains a central challenge in aerodynamics modelling: Reynolds-averaged Navier–Stokes predictions of separated flows are often inaccurate, and large-eddy simulation (LES) can require prohibitively small near-wall mesh sizes. A deep learning (DL) closure model for LES is developed by introducing untrained neural networks into the governing equations and training in situ for incompressible flows around rectangular prisms at moderate Reynolds numbers. The DL-LES models are trained using adjoint partial differential equation (PDE) optimization methods to match, as closely as possible, direct numerical simulation (DNS) data. They are then evaluated out-of-sample – for aspect ratios, Reynolds numbers and bluff-body geometries not included in the training data – and compared with standard LES models. The DL-LES models outperform these models and are able to achieve accurate LES predictions on a relatively coarse mesh (downsampled from the DNS mesh by factors of four or eight in each Cartesian direction). We study the accuracy of the DL-LES model for predicting the drag coefficient, near-wall and far-field mean flow, and resolved Reynolds stress. A crucial challenge is that the LES quantities of interest are the steady-state flow statistics; for example, a time-averaged velocity component $\langle {u}_i\rangle (x) = \lim _{t \rightarrow \infty } ({1}/{t}) \int _0^t u_i(s,x)\, {\rm d}s$ . Calculating the steady-state flow statistics therefore requires simulating the DL-LES equations over a large number of flow times through the domain. It is a non-trivial question whether an unsteady PDE model with a functional form defined by a deep neural network can remain stable and accurate on $t \in [0, \infty )$ , especially when trained over comparatively short time intervals. Our results demonstrate that the DL-LES models are accurate and stable over long time horizons, which enables the estimation of the steady-state mean velocity, fluctuations and drag coefficient of turbulent flows around bluff bodies relevant to aerodynamics applications.

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.

Validating Confined Flame Noise Simulation Using External Sensor.

Advancements in lean premixed combustion have increased the efficiency and reduced the amount of greenhouse gas emissions, but they have led to increased noise emissions due to higher turbulence and mixing fluctuations. This study used an external sensor (microphone) to validate the simulation of the combustion noise of a confined space. An experimental facility with a laboratory-scale furnace was used to carry out the measurement, and the simulation of the confined flame noise was conducted in OpenFOAM. The simulation utilized the Partially Stirred Reactor (PaSR) and a hybrid computational aeroacoustics (CAA) approach using the large eddy simulation (LES)/the Ffwocs Williams–Hawkings (FWH) method. Additionally, unsteady Reynolds-averaged Navier–Stokes (URANS)/the FWH method was tested for a comparison with the LES prediction. A sensor which was placed outside the enclosure for ease of access was then used to validate the results of the numerical model. The sensor data agreed with the LES/FWH results including the amplitude and frequency of the primary combustion peak and the overall sound pressure level (OASPL). This suggested that a sensor which was placed outside the enclosure could serve as a validation tool for the simulation of the confined flames despite the sound reflections from the walls.

Sensitivity Analysis of Wind and Turbulence Predictions With Mesoscale‐Coupled Large Eddy Simulations Using Ensemble Machine Learning

AbstractCoupling between mesoscale models and large‐eddy simulation (LES) models is increasingly used to more realistically represent the wide range of scales of atmospheric motions affecting boundary layer winds and turbulence that need to be simulated accurately for applications such as wind energy. However, such mesoscale‐to‐microscale coupled modeling frameworks are potentially affected by a large number of uncertain closure parameters. Here, we investigate the sensitivity associated with six closure parameters related to a 1.5‐order subgrid‐scale turbulence closure for an ensemble of mesoscale‐coupled LES. The simulations are performed using the Weather Research and Forecasting model nested from horizontal resolutions of greater than a kilometer down to tens of meters. Closure parameters are varied to generate perturbed parameter ensembles for two case studies of highly sheared, convective boundary layers observed in the Columbia Basin of Oregon and Washington during the Second Wind Forecast Improvement Project. Machine learning algorithms are used to explore the sensitivity of LES predictions, considering the effects of the perturbed physical parameters alongside categorical factors such as the case study identity, measurement location, and LES resolution. For the conditions we examine, a single parameter, the eddy viscosity coefficient, is the dominant source of parametric sensitivity and its importance is comparable to the categorical factors for several of the simulation response variables we examine.

How trees affect urban air quality: It depends on the source

Large-eddy simulation (LES) is used to systematically analyse the impacts of trees on air quality in idealised street canyons. The LES tree model includes radiation, transpiration, drag and deposition effects. The superposition of background concentrations and local emissions is used to construct realistic urban scenarios for fine particulate matter (PM2.5) and nitrogen oxides (NOx). Both neutral and convective atmospheric conditions are considered to assess the importance of buoyancy effects and the role of tree shading and transpiration. Tree impact on local air quality is shown to be driven by the balance between the rate at which they actively remove pollutants from the air (deposition) and the way in which they alter the transport of pollutants within and out of the street canyon (dispersion). For pollutant species or street types where the concentration field is dominated by background levels (such as PM2.5), deposition will generally dominate and thus local air quality will improve. For pollutants and street types where local emission sources dominate (e.g. NOx on a busy road), the dispersion effects of trees become more prominent and can lead to elevated concentrations where mixing or exchange is significantly inhibited. Mixing in the convective simulation is more vigorous than in the neutral simulation which results in substantial differences in in-canyon flow fields and exchange velocities, highlighting the importance of incorporating thermal effects when studying urban trees. Increased residency times, and thus deposition, under neutral conditions suggest that trees can have amplified effects under conditions conducive of poor air quality. For the cases considered, trees largely act to improve air quality with the exception of localised hotspots. The competing effects of trees — specifically deposition versus altered exchange with the atmosphere — are also incorporated in a simple integral model that predicts whether or not the air quality will improve. The model matches well with LES predictions for both PM2.5 and NOx and can serve as a simple tool for urban design purposes.

LES predictions of confinement effect on swirling flow generated by single helical axial swirler

PurposeFor higher swirling flows (swirl > 0.5), flow confinement significantly impacts fluid flow, flame stability, flame length and heat transfer, especially when the confinement ratio is less than 9. Past numerical studies on helical axial swirler type systems are limited to non-reacting or reacting flows type Reynolds averaged Navier Stokes closure models, mostly are non-parametric studies. Effects of parametric studies like swirl angle and confinement on the unsteady flow field, either numerical or experimental, are very minimal. The purpose of this paper is to document modeling practices for a large eddy simulation (LES) type grid, predict the confinement effects of a single swirler lean direct injection (LDI) system and validate with literature data.Design/methodology/approachThe first part of the paper discusses the approach followed for numerical modelling of LES with the minimum number of cells required across critical sections to capture the spectrum of turbulent energy with good accuracy. The numerical model includes all flow developing sections of the LDI swirler, right from the axial setting chamber to the exit of the flame tube, and its length is effectively modelled to match the experimental data. The computational model predicts unsteady features like vortex breakdown bubble, represented by a strong recirculation zone anchored downstream of the fuel nozzle. It is interesting to note that the LES is effective in predicting the secondary recirculation zones in the divergent section as well as at the corners of the tube wall.FindingsThe predictions of a single helical axial swirler with a vane tip angle of 60°, with a duct size of 2 × 2 square inches, are compared with the experimental data at several axial locations as well as with centerline data. Both mean and unsteady turbulent quantities obtained through the numerical simulations are validated with the experimental data (Cai et al., 2005). The methodology is extended to the confinements effect on mean flow characteristics. The time scale and length scale are useful parameters to get the desired results. The results show that with an increase in the confinement ratio, the recirculation length increases proportionally. A sample of three cases has been documented in this paper.Originality/valueThe novelty of the paper is the modelling practices (grid/unsteady models) for a parametric study of LDI are established, and the mean confinement effects are validated with experimental data. The spectrum of turbulent energies is well captured by LES, and trends are aligned with experimental data. The methodology can be extended to reacting flows also to study the effect of swirl angle, fuel injection on aerodynamics, droplet characteristics and emissions.

Effect of MDI Actuation Timing on Inhalation Dosimetry in a Human Respiratory Tract Model.

Accurate knowledge of the delivery of locally acting drug products, such as metered-dose inhaler (MDI) formulations, to large and small airways is essential to develop reliable in vitro/in vivo correlations (IVIVCs). However, challenges exist in modeling MDI delivery, due to the highly transient multiscale spray formation, the large variability in actuation–inhalation coordination, and the complex lung networks. The objective of this study was to develop/validate a computational MDI-releasing-delivery model and to evaluate the device actuation effects on the dose distribution with the newly developed model. An integrated MDI–mouth–lung (G9) geometry was developed. An albuterol MDI with the chlorofluorocarbon propellant was simulated with polydisperse aerosol size distribution measured by laser light scatter and aerosol discharge velocity derived from measurements taken while using a phase Doppler anemometry. The highly transient, multiscale airflow and droplet dynamics were simulated by using large eddy simulation (LES) and Lagrangian tracking with sufficiently fine computation mesh. A high-speed camera imaging of the MDI plume formation was conducted and compared with LES predictions. The aerosol discharge velocity at the MDI orifice was reversely determined to be 40 m/s based on the phase Doppler anemometry (PDA) measurements at two different locations from the mouthpiece. The LES-predicted instantaneous vortex structures and corresponding spray clouds resembled each other. There are three phases of the MDI plume evolution (discharging, dispersion, and dispensing), each with distinct features regardless of the actuation time. Good agreement was achieved between the predicted and measured doses in both the device, mouth–throat, and lung. Concerning the device–patient coordination, delayed MDI actuation increased drug deposition in the mouth and reduced drug delivery to the lung. Firing MDI before inhalation was found to increase drug loss in the device; however, it also reduced mouth–throat loss and increased lung doses in both the central and peripheral regions.

Large Eddy Simulations of Turbulent and Buoyant Flows in Urban and Complex Terrain Areas Using the Aeolus Model

Fast and accurate predictions of the flow and transport of materials in urban and complex terrain areas are challenging because of the heterogeneity of buildings and land features of different shapes and sizes connected by canyons and channels, which results in complex patterns of turbulence that can enhance material concentrations in certain regions. To address this challenge, we have developed an efficient three-dimensional computational fluid dynamics (CFD) code called Aeolus that is based on first principles for predicting transport and dispersion of materials in complex terrain and urban areas. The model can be run in a very efficient Reynolds average Navier–Stokes (RANS) mode or a detailed large eddy simulation (LES) mode. The RANS version of Aeolus was previously validated against field data for tracer gas and radiological dispersal releases. As a part of this work, we have validated the Aeolus model in LES mode against two different sets of data: (1) turbulence quantities measured in complex terrain at Askervein Hill; and (2) wind and tracer data from the Joint Urban 2003 field campaign for urban topography. As a third set-up, we have applied Aeolus to simulate cloud rise dynamics for buoyant plumes from high-temperature explosions. For all three cases, Aeolus LES predictions compare well to observations and other models. These results indicate that Aeolus LES can be used to accurately simulate turbulent flow and transport for a wide range of applications and scales.

Investigation of the three-dimensional flow past a flatback wind turbine airfoil at high angles of attack

Flatback airfoils are airfoils with a blunt trailing edge. They are currently commonly used in the inboard part of large wind turbine blades, as they offer a number of aerodynamic, structural, and aeroelastic benefits. However, the flow past them at high angles of attack (AoA) has received relatively little attention until now. This is important because they usually operate at high AoA at the inboard part of Wind Turbine blades. The present investigation uses Reynolds averaged Navier–Stokes (RANS) and hybrid RANS + large eddy simulation predictions to analyze the flow in question. The numerical results are validated against previously published wind tunnel experiments. The analysis reveals that to successfully simulate this flow, the spanwise extent of the computational domain is crucial, more so than the selection of the modeling approach. Additionally, a low-drag regime observed at angles of attack before stall is identified and analyzed in detail. Finally, the complex interaction between the three-dimensional separated flow beyond maximum lift (stall cells) with the vortex shedding from the blunt trailing edge is revealed.

Analysis of flow field and turbulence predictions in a lung model applying RANS and implications for particle deposition

Airflow and aerosol deposition in the human airways are important aspects for applications such as pulmonary drug delivery and human exposure to aerosol pollutants. Numerical simulations are widely used nowadays to shed light in airflow features and particle deposition patterns inside the airways. For that purpose, the Euler/Lagrange approach is adopted for predicting flow field and particle deposition through point-particle tracking. Steady-state RANS (Reynolds-averaged Navier-Stokes) computations of flow evolution in an extended lung model applying different turbulence models were conducted and compared to measurements as well as high resolution LES (large-eddy simulations) for several flow rates. In addition, various inlet boundary conditions were considered and their influence on the predicted flow field was analysed. The results showed that the mean velocity field was simulated reasonably well, however, turbulence intensity was completely under-predicted by two-equation turbulence models. Only a Reynolds-stress model (RSM) was able predicting a turbulence level comparable to the measurements and the high resolution LES. Remarkable reductions in wall deposition were observed when wall effects were accounted for in the drag and lift force expressions. Naturally, turbulence is an essential contribution to particle deposition and it is well known that two-equation turbulence models considerably over-predict deposition due to the spurious drift effect. A full correction of this error is only possible in connection with a Reynolds-stress turbulence model whereby the predicted deposition in dependence of particle diameter yielded better agreement to the LES predictions. Specifically, with the RSM larger deposition is predicted for smaller particles and lower deposition fraction for larger particles compared to LES. The local deposition fraction along the lung model was numerically predicted with the same trend as found from the measurements, however the values in the middle region of the lung model were found to be somewhat larger.

Liquid mixing intensification by adding swirling flow in the transverse jet mixer

AbstractIn this study, effect of swirling addition on the liquid mixing behavior of multiorifice‐impinging transverse jet mixer has been investigated by planar laser‐induced fluorescence as well as large eddy simulation (LES). In the case of swirling addition into the jet flow, there exists an optimized swirling jet angle or optimized jet‐to‐cross velocity ratio for the fixed mixer configuration. A larger swirling jet angle will make the flow dominated by the swirling, resulting in a slower mixing process. Interaction of swirling crossflow with no‐swirling‐injected streams, or with swirling‐injected streams in the opposite direction is beneficial for the mixing. LES predictions show that many small vortices are produced homogenously due to intensified impingement in the case of opposite swirling directions, leading to a relative fast mixing process in few milliseconds. Whereas the mixing is restrained when the swirling directions of two flows are the same.

Static mesh adaptation for reliable large eddy simulation of turbulent reacting flows

The design challenge of reliable lean combustors needed to decrease pollutant emissions has clearly progressed with the common use of experiments as well as large eddy simulation (LES) because of its ability to predict the interactions between turbulent flows, sprays, acoustics, and flames. However, the accuracy of such numerical predictions depends very often on the user's experience to choose the most appropriate flow modeling and, more importantly, the proper spatial discretization for a given computational domain. The present work focuses on the last issue and proposes a static mesh refinement strategy based on flow physical quantities. To do so, a combination of sensors based on the dissipation and production of kinetic energy coupled to the flame-position probability is proposed to detect the regions of interest where flow physics happens and grid adaptation is recommended for good LES predictions. Thanks to such measures, a local mesh resolution can be achieved in these zones improving the LES overall accuracy while, eventually, coarsening everywhere else in the domain to reduce the computational cost. The proposed mesh refinement strategy is detailed and validated on two reacting-flow problems: a fully premixed bluff-body stabilized flame, i.e., the VOLVO test case, and a partially premixed swirled flame, i.e., the PRECCINSTA burner, which is closer to industrial configurations. For both cases, comparisons of the results with experimental data underline the fact that the predictions of the flame stabilization, and hence the computed velocity and temperature fields, are strongly influenced by the mesh quality and significant improvement can be obtained by applying the proposed strategy.

Turbulent thermal convection driven by free-surface evaporation in cuboidal domains of different aspect ratios

In this paper, we present simulations of turbulent thermal convection driven by free-surface evaporation above and by a heated wall below. A novel algorithm is proposed for predicting evaporation rates at a free surface, which we then validate against experimental data. At the top of a cuboidal domain, a shear-free boundary condition acts as an approximation of the free surface. We first focus on a domain of aspect ratio Γ = 1, where a fully resolved direct numerical simulation is carried out at a moderate Rayleigh number, Ra = 1.2 × 107, and we compare flow statistics with a Large-Eddy Simulation (LES) on a coarse grid. Both the fully resolved simulation and the LES predict well the time- and area-averaged evaporation rate and free surface temperature when compared with the experimental data. Next, we carry out a series of LES with an increasing lower wall temperature and, consequently, Ra. We then validate the evaporation model by comparing LES predictions of the time- and area-averaged mass flux and temperature at the upper boundary against the experimental measurements. The aspect ratio of the domain is then reduced, and we show, for the first time, the transition to a dual-roll state of the large-scale circulation (LSC) at the aspect ratio of Γ = 1/4 in a cuboidal domain. The temperature and velocity distributions at the free surface are impacted by the state of the LSC. However, we find that the water-side turbulence and aspect ratio play a negligible role on the evaporation rate above, in accordance with experimental observations.

Application of Actuator Line Model for Large Eddy Simulation of Rotor Noise Control

A hybrid Large Eddy Simulation (LES)/Actuator Line Model (ALM) computational approach is employed to simulate the turbulent wake of a two-bladed rotor in hover. Validations are performed for the Knight and Hefner two-bladed rotor case with comparisons to previous LES predictions using the immersed boundary method, as well as hybrid RANS-LES using the Helios code. The Ffowcs-Williams Hawkings (FWH) acoustic analogy is then used for predicting rotor noise. Predictions from the combined LES/ALM/FWH model are next validated against recent PIV wake flow and acoustic measurements for a two-bladed rotor. Finally, the LES/ALM/FWH approach is exploited to demonstrate a novel way to explore active flow control strategies to reduce rotor noise by delaying flow separation and enabling a lower rate of rotation, resulting in lower noise while maintaining thrust.

Large Eddy Simulation of Film Cooling with Bulk Flow Pulsation: Comparative Study of LES and RANS

The effects of bulk flow pulsations on film cooling in gas turbine blades were investigated by conducting large eddy simulation (LES) and Reynolds-averaged Navier–Stokes simulation (RANS). The film cooling flow fields under 32 Hz pulsation in the mainstream from a cylindrical hole inclined 35° to a flat plate at the average blowing ratio of M = 0.5 were numerically simulated. The LES results were compared to the experimental data of Seo, Lee, and Ligrani (1998) and Jung, Lee, and Ligrani (2001). The credibility of the LES results relative to the experimental data was demonstrated through a comparison of the time-averaged adiabatic film cooling effectiveness, time- and phase-averaged temperature contours, Q-criterion contours, time-averaged velocity profiles, and time- and phase-averaged Urms profiles with the corresponding RANS results. The adiabatic film cooling effectiveness predicted using LES agreed well with the experimental data, whereas RANS highly overpredicted the centerline effectiveness. RANS could not properly predict the injectant topology change in the streamwise normal plane, but LES reproduced it properly. In the case of the injectant trajectory, which greatly influences film cooling effectiveness, RANS could not properly predict the changes in the streamwise velocity peak due to flow pulsation, but they were predicted well with LES. RANS greatly underpredicted the streamwise velocity fluctuations, which determine the mixing of main flow and injectant, whereas LES prediction was close to the experimental data.

High-fidelity simulations and field measurements for characterizing wind fields in a utility-scale wind farm

Characterizing wind farm flow fields at high temporal and spatial resolutions is critical prerequisite for the optimal design and operation of utility-scale wind farms and for reducing the levelized cost of energy. However, due to the large disparity of underlying scales, measurements or simulations alone cannot provide high resolution wind fields, which are informed by and account for the effect of both large scale (i.e. hour, day, month and year) and small scale (i.e. second and minute) site-specific variations in the atmosphere. We explore the feasibility of integrating field measurements and high-fidelity large-eddy simulation (LES) to characterize the wind field in a utility-scale wind farm while accounting for flow phenomena across multiple temporal scales. Specifically, we employ field measurements to characterize the monthly wind speed and wind direction distributions and investigate the wind characteristics in turbine wakes. It was found that the probability density function (PDF) of the wind speed in turbine wakes can be reasonably represented using the Weibull distribution but with shape factors smaller than those not in the wake. LES of the wind farm under statistically steady inflow is subsequently carried out for one wind direction. The LES predictions are compared with the measured data conditionally averaged based on the wind speed, wind direction and the root-mean-square of wind speed fluctuations over time intervals of 30 min. Good agreement is obtained for both mean wind speed and turbulence intensity. The present work shows the possibility of integrating field measurements and high-fidelity simulations for improved characterization of the site-specific wind fields in utility-scale wind farms.