Large Eddy Simulation Simulations Research Articles

A dynamically adaptive Langmuir turbulence parameterization scheme for variable wind wave conditions: Model application

Langmuir circulations and turbulence (LT) are crucial in the upper ocean mixed layer, significantly affecting the air-sea exchange of momentum, heat, and mass. The development of an appropriate LT parameterization scheme is vital for ocean modeling. This study employed the Large-eddy Simulation (LES) and the Physics-informed Neural Network (PINN) to optimize the KC04 Langmuir turbulence scheme by dynamically adjusting E6 as a key parameter determined by winds and waves. The LES simulations under different wind wave states indicated the PINN-inferred values for E6. Modelling results from GOTM in OCSPapa station demonstrated that the optimized scheme outperformed the original KC04 scheme in simulating the vertical eddy diffusivity and temperature, with an ∼6.24% annual reduction in the root mean square error (RMSE) for the temperature and an ∼8.23% reduction in the RMSE during autumn. Furthermore, the optimized scheme resulted in a thicker mixed layer, reaching 4.9 m. This enhanced LT parameterization scheme exhibited the improved robustness for variable spatiotemporal resolutions, significantly improving the modeling accuracy.

Multiscale modeling of cavitation around high-speed object based on Euler-Lagrange model and overset mesh

Abstract Cavitation is a common phenomenon, which usually occurs inside the high-speed liquid or at the liquid-solid interface. The unsteady behaviors of cavitating flow, such as shedding and collapse, can cause intense pressure fluctuations and reduce the stability of devices such as under-water high-speed vehicles. In addition, cavitating flow changes the dynamic characteristics of the liquid and causes vibration of the structure as well, making it extremely difficult in achieving precise control. Using OpenFOAM, the present work employs the large eddy simulation (LES) approach to investigate the characteristics of the unsteady cavitating flow around a high-speed under-water object with using the overset mesh technology. The volume of fluid (VOF) approach jointed with the Lagrangian discreate bubble model (DBM) is used for capturing the multiscale cavitation features. The Schnerr & Sauer model is applied for the mass transfer between water and vapor in macroscale, while the Reynolds-Pel equation is incorporated for the growing and collapsing of microscale bubbles. Due to the difficulty in incorporating the multi-scale method into the problems with mesh motion, the present work employs the overset mesh method. Compared with the published small-scale water tank experiment, the LES simulation results fit well with the experimental phenomena, and the DBM can capture the small bubbles accurately. On the basis of model verification, the mechanisms of cavitation forming and collapsing is investigated and the effect of cavitation shedding on the motion of the object is also studied. Moreover, the nucleation, growth, collapse of bubbles, and the interaction between discrete bubbles and large cavities can be well revealed. Further, the multi-scale Euler-Lagrange model is also applied in the rotating propeller, the generation of tip vortex cavitation which is hard to be captured by traditional models is well presented.

Computational Hemodynamics-Based Growth Prediction for Small Abdominal Aortic Aneurysms: Laminar Simulations Versus Large Eddy Simulations.

Prior studies have shown that computational fluid dynamics (CFD) simulations help assess patient-specific hemodynamics in abdominal aortic aneurysms (AAAs); patient-specific hemodynamic stressors are frequently used to predict an AAA's growth. Previous studies have utilized both laminar and turbulent simulation models to simulate hemodynamics. However, the impact of different CFD simulation models on the predictive modeling of AAA growth remains unknown and is thus the knowledge gap that motivates this study. Specifically, CFD simulations were performed for 70 AAA models derived from 70 patients' computed tomography angiography (CTA) data with known growth status (i.e., fast-growing [> 5mm/yr] or slowly growing [< 5mm/yr]). We used laminar and large eddy simulation (LES) models to obtain hemodynamic parameters to predict AAAs' growth status. Predicting the growth status of AAAs was based on morphological, hemodynamic, and patient health parameters in conjunction with three classical machine learning (ML) classifiers, namely, support vector machine (SVM), K-nearest neighbor (KNN), and generalized linear model (GLM). Our preliminary results estimated aneurysmal flow stability and wall shear stress (WSS) were comparable in both laminar and LES flow simulations. Moreover, computed WSS and velocity-related hemodynamic variables obtained from the laminar and LES simulations showed comparable abilities in differentiating the growth status of AAAs. More importantly, the predictive modeling performance of the three ML classifiers mentioned above was similar, with less than a 2% difference observed (p-value>0.05). In closing, our findings suggest that two different flow simulations investigated did not significantly affect outcomes of computational hemodynamics and predictive modeling of AAAs' growth status, given the data investigated.

Investigating crossflow interactions in multi-perforation cooling systems: Experimental and numerical insights

This study investigates the effects of employing a multi-perforation cooling system on crossflow interactions, utilizing both numerical simulations and experimental methods. A 30° inclined multi-perforation cooling system is applied on a heated flat plate as part of the experimental setup. Large Eddy Simulation (LES) is utilized for Computational Fluid Dynamics (CFD) calculations to analyze the impact of multi-perforation on heat transfer dynamics. Validation is conducted by comparing the results with experimental investigations. The study encompasses both aerodynamic and thermal considerations, employing Particle Image Velocimetry (PIV) and infrared techniques for analysis, while wall heat flux is measured using electrical discharge. Experimental data on film cooling are collected through these methods, focusing on the impact of blowing ratio (M) and the number of open jet rows (R). The LES-based CFD simulations accurately predict the trajectory of the cooling film. Notably, the influence of flow through the multi-perforation on the primary flow is observable across both configurations of open jet rows (4R and 8R near the wall). The outcomes substantiate the formation of a cooling film emanating from the jet’s fourth row (4R configuration), thereby validating the LES simulations. Visualization of wall temperatures illustrates the formation of a cooling film, discernible through the visible heat distribution from row 4R. However, discrepancies arise in predicting the adiabatic cooling efficiency towards the exit of the 4R region and the commencement of the 8R region, potentially attributed to the alterations induced by the additional multi-perforated injection. The novelty and the main objective of this study is to evaluate the impact of the variation of geometric parameters between the jets and the main flow on the dispersion of the jets themselves. A novel function, tailored to the temperature evolution of the cooling gas, is employed for data analysis. Two geometry configurations, featuring varying open hole areas, are evaluated. The film-cooled heat transfer coefficient, depicted by the Nusselt number, and the adiabatic film cooling efficiency results, serve to appraise the film cooling efficacy of the configurations.

Aerodynamic analysis of vertical axis wind turbines at various turbulent levels: Insights from 3D LES simulations

This study provides novel insights into the aerodynamic performance of vertical axis wind turbines (VAWTs) in diverse turbulent environments using 3D large eddy simulations (LES). The research aims to understand how turbulence affects VAWT aerodynamics across different operational conditions, including varying wind speeds, tip speed ratios (TSRs), and turbulence intensities. Validation against wind tunnel test data from literature enhances the reliability of the findings. The study utilizes the consistent discrete random flow generation (CDRFG) technique to create homogeneous turbulence in the approaching flow. Through a detailed examination of the rotor aerodynamics and flow fields, critical insights are gained into the impact of turbulence on VAWT performance. The results highlight that local wind speed fluctuations influence the onset of dynamic stall, with turbulence significantly affecting lift forces, while having negligible effects on drag. Notably, fluctuations in the one-cycle power coefficient CP,sgl are primarily attributed to variations in lift. Furthermore, under turbulent conditions, substantial improvements in power performance are observed as wind speed increases from 5 m/s to 10 m/s, with minimal further enhancements at higher wind speeds. These findings contribute valuable insights for optimizing turbine design and operation, particularly in regions characterized by varying wind speeds and turbulence.

Usage of high-fidelity large eddy simulation to improve the turbulence modeling of Reynolds averaged navier stokes simulation in film cooling applications via a neural network

In this study, high-Fidelity Large eddy simulation (LES) data was used to create a surrogate turbulence model to enhance the estimation of turbulent heat flux in a Reynolds averaged Navier Stokes (RANS) solver for film cooling applications. The LES simulation (A flat plate film cooling application with a Reynolds number of 17,382, a blowing ratio of 1 and a density ratio of 2) was validated by comparison with experimental data. A correlation analysis was performed to identify the most influential parameters, and temperature gradient, velocity gradient, turbulent dissipation rate, shear strain rate, and turbulent viscosity ratio were selected as the most effective parameters. A second model was developed to create a Galilean-invariant model that remains unaffected by changes in the coordinate system. Neural network was applied to the LES training data to propose a modified surrogate dynamic turbulent Prandtl number to be applied to the k − ε realizable RANS simulation. The first surrogate model was implemented to two different geometries, one geometry was a flat plate film cooling similar to the training data but with different flow conditions, and another one was a more complex geometry with pressure gradient. The second model was only implemented on the second geometry and produced similar results. The surrogate models predicted a more accurate thermal field near the cooling wall (up-to 58 % error reduction) with a computational time complexity similar to the base RANS solver.

Multi-fidelity actuator-line modelling of FOWT wakes

Large Eddy Simulations (LES) are considered the proper tool for predicting the physics of a wind turbine wake, thereby establishing a solid foundation for investigating the interaction among floating turbines within wind farms. In this work the Actuator Line Model, implemented in the OpenFoam environment, is combined with both U-RANS and LES simulations to underline the differences in accuracy when reproducing the near and far wake of a single turbine. Both a fixed-bottom and a surge motion case are tested to highlight the wake phenomena strictly generated by the platform motion. The use of LES simulation becomes fundamental by virtue of its ability to accurately simulate turbulence and mixing with free-stream flow, hence, this research aims at advancing the knowledge of wake dynamics from multiple perspectives while ensuring reliability thanks to the use of the experimental wake data from the UNAFLOW test campaign on the scaled laboratory model of the DTU 10 MW. In the near wake, limited flow unsteadiness and similar mean velocity are predicted by the two models. In the far wake, instead, the LES approach estimates a strong rise of flow unsteadiness which, in case of surge motion, affects the mean velocity value making evident the difference between LES and RANS estimation.

LES and RANS Spray Combustion Analysis of OME3-5 and n-Dodecane

Clean-burning oxygenated and synthetic fuels derived from renewable power, so-called e-fuels, are a promising pathway to decarbonize compression–ignition engines. Polyoxymethylene dimethyl ethers (PODEs or OMEs) are one candidate of such fuels with good prospects. Their lack of carbon-to-carbon bonds and high concentration of chemically bound oxygen effectively negate the emergence of polycyclic aromatic hydrocarbons (PAHs) and even their precursors like acetylene (C2H2), enabling soot-free combustion without the soot-NOx trade-off common for diesel engines. The differences in the spray combustion process for OMEs and diesel-like reference fuels like n-dodecane and their potential implications on engine applications include discrepancies in the observed ignition delay, the stabilized flame lift-off location, and significant deviations in high-temperature flame morphology. For CFD simulations, the accurate modeling and prediction of these differences between OMEs and n-dodecane proved challenging. This study investigates the spray combustion process of an OME3 − 5 mixture and n-dodecane with advanced optical diagnostics, Reynolds-Averaged Navier–Stokes (RANS), and Large-Eddy Simulations (LESs) within a constant-volume vessel. Cool-flame and high-temperature combustion were measured simultaneously via high-speed (50 kHz) imaging with formaldehyde (CH2O) planar laser-induced fluorescence (PLIF) representing the former and line-of-sight OH* chemiluminescence the latter. Both RANS and LES simulations accurately describe the cool-flame development process with the formation of CH2O. However, CH2O consumption and the onset of high-temperature reactions, signaled by the rise of OH* levels, show significant deviations between RANS, LES, and experiments as well as between n-dodecane and OME. A focus is set on the quality of the simulated results compared to the experimentally observed spatial distribution of OH*, especially in OME fuel-rich regions. The influence of the turbulence modeling is investigated for the two distinct ambient temperatures of 900 K and 1200 K within the Engine Combustion Network Spray A setup. The capabilities and limitations of the RANS simulations are demonstrated with the initial cool-flame propagation and periodic oscillations of CH2O formation/consumption during the quasi-steady combustion period captured by the LES.

On the feasibility of overnight industrial high-fidelity simulations of CSP technologies on modern HPC systems

In the last decades, computational fluid dynamics (CFD) has become a standard design tool in many fields, such as the automotive, aeronautical, and renewable energy industries. The driving force behind this is the development of numerical techniques in conjunction with the progress of high-performance computing (HPC) systems. However, simulation time remains the most limiting factor for large-eddy simulations (LES) to be adopted in the industry. A consensus exists that, to be feasible, LES simulations should be completed overnight In this context, this work assesses the feasibility of overnight LES simulations on GPU-accelerated supercomputers with TFA, our novel in-house code, which relies on a symmetry-preserving discretisation for unstructured collocated grids that, apart from being virtually free of artificial dissipation, is shown to be unconditionally stable. The study cases will be taken from central receivers used in concentrated solar power (CSP) plants, and a comparison with open-source CFD codes will be made.

LES investigations of turbulent heat transfer structures with exponential power escalation

The BORAX-type accident is a key scenario in the safety design of pool-type experimental nuclear reactors. It considers a reactivity insertion large enough to initiate an exponential power escalation with a period as small as tens of milliseconds, necessitating effective heat removal by the coolant system. This study presents a computational analysis of single-phase transient heat transfer under thermal-hydraulic conditions relevant to such reactors, focusing on turbulent channel flow between planar fuel plates with highly subcooled water. Our investigation uses Large Eddy Simulation (LES) performed with TrioCFD, the open-source CFD code developed by the French Atomic Energy Commission (CEA). Several modeling options are tested: incompressible flow with temperature as a passive scalar, incompressible flow with varying viscosity, and quasicompressible flow with temperature-dependent viscosity and mass density. To evaluate the accuracy of our physical models, all simulations were performed under uniform conditions, using the same experimental parameters, mesh, and numerical strategies. The specific examined scenario involves a highly subcooled turbulent channel flow at moderate pressure, experiencing an exponential power increase. We ensure detailed turbulence resolution at the Batchelor scale in the wall normal direction close to the heating wall. This communication presents a comparative study of LES simulations of the single-phase flow under exponential power excursion at the wall. Subsequent analyses focused on the impact of different velocity-temperature couplings on the prediction of wall heat transfer, incorporating comparisons with experimental infrared thermometry measurements. Early in the transient phase, temperature peaks are confined within turbulent streaks, as reported in the existing literature. However, as the exponential power transient unfolds, the viscous layer and streak structures destabilize, leading to a more dispersed distribution of hot spots. Preliminary findings suggest a transition in heat transfer modes from turbulence-driven to conduction during the final stages of the single-phase transient.

Large eddy simulation of a turbulent channel flow using dynamic Smagorinsky subgrid scale model and differential equation wall model

A large eddy simulation (LES) is conducted in a plane channel flow which is turbulent. For understanding the mechanism of the turbulent motion more efficiently, the present study is an attempt to conduct the LES using a Dynamic Smagorinsky Model (DSM) and a Differential Equation Wall Model (DEWM). DSM is a subgrid-scale model and DEWM is for approximating the near wall layer. The simulation is performed in a domain of 2 π δ × 2 δ × π δwhich is discretized by 32 × 20 × 32grid points where δ is the channel half width. The discretization techniques have been used in the simulation, are the 3rd order low storage R-K method in time and 2nd order finite difference formulation in space. To assess the performance of the LES with DSM and DEWM, the simulation results are compared with direct numerical simulation (DNS) data and LES data using Standard Smagorinsky Model (SSM). Comparing the results in the essential turbulence statistical field it has been found that DSM performs better than SSM in most of the cases and shows better agreement with the DNS results. Flow structures in the turbulent flow field are compared in isosurfaces and contour plots, and found that tube-like vortical structures are randomly distributed over the entire flow field, and the number of the vortical structures are more for the DSM case than that of SSM.

Evaluation of wind farm parameterizations in the WRF model under different atmospheric stability conditions with high-resolution wake simulations

Abstract. Wind farm parameterizations (WFPs) are used in mesoscale models for predicting wind farm power production and its impact on wind resources while considering the variability of the regional wind climate. However, the performance of WFPs is influenced by various factors including atmospheric stability. In this study, we compared two widely used WFPs in the Weather Research and Forecasting (WRF) model to large-eddy simulations (LES) of turbine wakes performed with the same model. The Fitch WFP and the explicit wake parameterization were evaluated for their ability to represent wind speed and turbulent kinetic energy (TKE) in a two-turbine wind farm layout under neutral, unstable, and stable atmospheric stability conditions. To ensure a fair comparison, the inflow conditions were kept as close as possible between the LES and mesoscale simulations for each type of stability condition, and the LES results were spatially aggregated to align with the mesoscale grid spacing. Our findings indicate that the performance of WFPs varies depending on the specific variable (wind speed or TKE) and the area of interest downwind of the turbine when compared to the LES reference. The WFPs can accurately depict the vertical profiles of the wind speed deficit for either the grid cell containing the wind turbines or the grid cells in the far wake, but not both simultaneously. The WFPs with an explicit source of TKE overestimate TKE values at the first grid cell containing the wind turbine; however, for downwind grid cells, agreement improves. On the other hand, WFPs without a TKE source underestimate TKE in all downwind grid cells. These agreement patterns between the WFPs and the LES reference are consistent under the three atmospheric stability conditions. However, the WFPs resemble less the wind speed and TKE from the LES reference under stable conditions than that under neutral or unstable conditions.

Turbulent Particle Flow in Spent Nuclear Fuel Storage Systems

Deposition models are being developed with the commercial computational fluid dynamics software STAR-CCM+ to evaluate particulate deposition on spent nuclear fuel (SNF) canisters. The primary particulate of concern is chloride salts, which are dispersed in the atmosphere and then deposited onto the canisters. During dry storage, the primary degradation process is likely to be chloride-induced stress corrosion cracking (CISCC) at the heat-affected zones of the canister welds. It is known that stainless steel canisters are susceptible to CISCC; however, the rate of chloride deposition onto the canisters is poorly known, based on sparse field data from a small number of sites. This paper describes work looking at various approaches to modeling turbulence, such as Reynolds-averaged Navier Stokes (RANS) and large eddy simulation (LES), and its impact on particle flow and deposition within a ventilated SNF storage system. The deposition rate is determined for a vertical canister system and a horizontal canister system. LES has the potential to simulate turbulent flows more accurately versus RANS, but is much more computationally expensive. A k-omega version of the RANS turbulence model was used for this study. The computational efficient RANS steady-state model predicted a similar canister deposition result as the LES simulation for a vertical canister storage system. For a horizontal storage system, the RANS steady-state model predicted more particles depositing on the canister than the LES simulation, providing a conservative estimation for particle deposition. A wall correction factor was added to the RANS model to dampen the turbulence fluctuation normal to a surface that left undamped, leads to the RANS model overpredicting deposition along a surface for smaller particles. This work was done to further development of deposition models that could be used to plan and inform SNF canister aging management programs with predictive models for the timing and occurrence of canister CISCC. This work is part of a larger effort tasked with understanding the likelihood of canister degradation due to CISCC. These models are still under development, and testing is needed for validation. However, these models are being presented now to demonstrate to canister vendors, utilities, regulators, and stakeholders the value of this type of modeling.

Turbulent mixed convection in a horizontal cylindrical cavity with the off-lattice Boltzmann method

Large-eddy simulations (LES) of turbulent mixed convection in a horizontal concentric cylindrical cavity when cylinders are subjected to rotations are investigated in the present study. A characteristic-based finite-difference off-lattice Boltzmann method solver is employed to investigate whether rotation enhances heat transfer in a horizontal concentric cylindrical cavity configuration where buoyancy acts perpendicular to the cylinder axis. The study focuses on assessing heat transfer characteristics for different rotation intensities in both counter-rotating-cylinders (CRC) and outer-rotating-cylinder (ORC) configurations. The LES simulations are performed for Rayleigh number, Ra=106, and Reynolds numbers, Re=0,500,1000, and 5000 for air (Pr=0.71), employing a classical Smagorinsky sub-grid-scale (SGS) model. The numerical solver is verified using two benchmark problems, namely (i) Buoyancy-driven flow in a differentially heated air-filled cubic enclosure and (ii) turbulent Taylor-Couette flow. The CRC and ORC configurations are chosen for the three-dimensional simulations in this study, prompted by the notable improvement in heat transfer observed in their respective two-dimensional simulations. A thorough comparison between two- and three-dimensional mixed convection results reveals substantial influence from secondary flow in the axial direction. While three-dimensional CRC simulations exhibit a modest increase in heat transfer at Re=500, the ORC configuration experiences a decrease in heat transfer rate as the Reynolds number increases, contrasting with two-dimensional simulation trends. The CRC configuration enhances the axial motion of the flow with Reynolds number, and its magnitude is larger than that of the ORC configuration and natural convection. A significant difference between two-dimensional and three-dimensional mixed convection simulation results is observed because of considerable secondary flow. Furthermore, the flow and thermal characteristics of turbulent mixed convection are investigated using streamlines, isotherms, Q-criterion, Nusselt number variation along the cylinders, anisotropy analysis, turbulent kinetic energy (TKE), dissipation, contours of radial and axial components of velocity.

Role of turbulence in ozone chemistry: Segregation effect implicated from multiscale modeling over Hong Kong

By influencing the mixing of reactive species in the atmosphere, turbulence affects the rates at which chemical species react, specifically in the planetary boundary layer. To analyze the turbulent segregation effect on the atmospheric ozone photochemistry, coupled meso-to micro-scale simulations are performed over Hong Kong, a polluted megacity. The comparison of the ozone production rates between the mesoscale model and the large-eddy simulations (LES) indicates that the resolved turbulent processes inhibit the mixing of the reactants, and thereby slow down the reaction rate between NO and O3, resulting in a smaller net O3 production when represented by a LES simulation. The calculated segregation intensities show clear correlations with the emission distribution, revealing that the segregation effect is significant in urban areas with inhomogeneous pollution sources, including traffic emissions. The evolution of the eddy structure plays a significant role in the diurnal variation of the segregation intensity. Applying the obtained segregation intensities to the mesoscale output, the NO–O3 reaction rate decreases with results closer to those provided by the LES model. This confirms the importance of the segregation effect on fast chemical reactions and provides insights into the parameterization of the segregation effect in mesoscale models, which do not resolve turbulent eddies.

Energetic and dynamic characterization of pollutant dispersion in varied building layouts through an augmented analysis procedure

This work presents a post-data analysis procedure, namely, proper orthogonal decomposition (POD)–dynamic mode decomposition (DMD)–discrete Fourier transform analysis, for evaluating the dominant features of the flow fields from both energetic and dynamic perspectives. The large-eddy simulation (LES) was first employed to reproduce the flow field surrounding three types of building layouts. Subsequently, both POD and DMD were conducted according to LES simulation results. The extracted modes were classified into three types based on the POD and DMD: Type-1 mode: energetically and dynamically significant mode, Type-2 mode: energetically significant and dynamically insignificant mode, and Type-3 mode: energetically insignificant and dynamically significant mode. The findings indicate that Type-1 mode governs the primary velocity field and the predominant vortex patterns observed at the rear of the building arrays, as the reduction of inter-building widths leads to a shorter flow separation region. Type-2 mode is characterized by the presence of small-scale vortices and the high turbulent kinetic energy region, which periodically triggers pollutant increase in the vicinity of structures. Type-3 mode demonstrates a minimal energetic influence on the flow field; nevertheless, it significantly contributes to the consistent build-up of pollutants within the far-wake region. The present study also investigates the predominant coherent structures of flow fields concerning various building layouts and highlights the influence of passage widths on the efficiency of pollutant removal. This comprehensive analysis enables a systematic exploration of flow patterns within various building layouts, offering potential solutions for pollutant dispersion challenges in metropolitan areas.

Impact of Momentum Perturbation on Convective Boundary Layer Turbulence

AbstractMesoscale‐to‐microscale coupling is an important tool for conducting turbulence‐resolving multiscale simulations of realistic atmospheric flows, which are crucial for applications ranging from wind energy to wildfire spread studies. Different techniques are used to facilitate the development of realistic turbulence in the large‐eddy simulation (LES) domain while minimizing computational cost. Here, we explore the impact of a simple and computationally efficient Stochastic Cell Perturbation method using momentum perturbation (SCPM‐M) to accelerate turbulence generation in boundary‐coupled LES simulations using the Weather Research and Forecasting model. We simulate a convective boundary layer (CBL) to characterize the production and dissipation of turbulent kinetic energy (TKE) and the variation of TKE budget terms. Furthermore, we evaluate the impact of applying momentum perturbations of three magnitudes below, up to, and above the CBL on the TKE budget terms. Momentum perturbations greatly reduce the fetch associated with turbulence generation. When applied to half the vertical extent of the boundary layer, momentum perturbations produce an adequate amount of turbulence. However, when applied above the CBL, additional structures are generated at the top of the CBL, near the inversion layer. The magnitudes of the TKE budgets produced by SCPM‐M when applied at varying heights and with different perturbation amplitudes are always higher near the surface and inversion layer than those produced by No‐SCPM, as are their contributions to the TKE. This study provides a better understanding of how SCPM‐M reduces computational costs and how different budget terms contribute to TKE in a boundary‐coupled LES simulation.

Large-Eddy Simulation Study of Injector Geometry and Parcel Injection Location on Spray Simulation of the Engine Combustion Network Spray G Injector

Abstract Recent improvements in computing power and numerical techniques have enabled us resolve minute details of spray plume behavior and its wall boundary interactions, and made detailed spray simulations using large-eddy simulation (LES) turbulence models available to many more engineers. However, guidelines for parcel-based spray simulation boundary and initial conditions are still based on results from lower-resolution and Reynolds averaged Navier–Stokes (RANS) simulations. Hence, it is necessary to critically examine those assumptions and compare their impact with results using a RANS turbulence model. Three different parameters, including whether a simulation includes a detailed injector tip geometry or a flat surface, whether parcels are initialized at the counterbore exit, which is more common, or at the nozzle exit, and whether to use an experimentally derived rate of injection or one-way coupling with a separate internal nozzle volume of fluid simulation, were examined with an LES turbulence model. Both local data close to the injector and global penetration results were used to compare simulations. Local data, such as the local liquid volume fraction, showed greater variation between the conditions, which may have an impact on mixing and combustion predictions in engine applications. Spray penetration and other global measures demonstrated limited sensitivity to the boundary conditions/initialization procedure. Results were also compared with prior results that used a RANS turbulence model. RANS simulations had overall smoother responses to the changes, as would be expected, but LES simulations showed similar trends in the effects for the measured variables.

High-resolution CFD modelling of Lillgrund Wind farm

We report on a fully dynamic simulation of Vattenfall’s Lillgrund offshore Wind Farm, with a focus on the wake effects of turbines on the performance of individual turbines, and of the farm as a whole. The model uses a dynamic representation of a wind turbine to simulate interaction between the wind and the turbine rotors, calculating the instantaneous power output and forces on the air; this was embedded in a finite element, large eddy simulation (LES) computational fluid dynamics code. This model was applied to the wind farm for a selection of key wind speeds and directions, to investigate cases where a row of turbines would be fully aligned with the wind or at specific angles to the wind. The simulation results were then compared to actual performance measurements from the wind farm spanning several years’ of operation. These results demonstrate that time-resolving LES simulations are able to reproduce realistic wake structures, including wake meandering and wake recovery, as well as the effect of wakes on turbine performance.

A subgrid-scale model to account for thermo-diffusive effects in artificially thickened LES models for lean turbulent premixed ammonia/hydrogen flames

With the introduction of carbon-free fuels and their rapid implementation, accurate combustion models are needed to design decarbonized engines, gas turbines or burners. Recent experimental and numerical work have highlighted the high burning rate of lean hydrogen and hydrogen/ammonia flames and their deviation from flamelet assumptions, pointing out the need to revise classical combustion models for Reynolds Averaged Navier–Stokes (RANS) or Large-Eddy Simulations (LES). In this work, a novel subgrid-scale model accounting for stretch effects for lean ammonia/hydrogen (NH3/H2) flames in the Thickened-Flame LES framework (TFLES) is proposed as an extension to the standard Charlette model Charlette et al. (2002). This model, called ESE−NH3, is based on 1-D premixed strained flames and validated a priori with Direct Numerical Simulations (DNS) and used to perform LES simulation of a turbulent slot burner configuration. To assess the performance of the novel subgrid model, LES predictions are compared a posteriori to the DNS and to LES employing the standard Charlette model. The comparison shows that the LES computation with the novel subgrid-scale model accounting for stretch effects predicts flame lengths closer to the DNS. This shows that thermo-diffusive effects can be integrated simply in the TFLES framework. Moreover, results show that these effects are significant in all lean NH3/H2 flames even at low H2 contents.