Large Eddy Simulation Research Articles

RANS model predictions for desalination discharges implemented with a dynamic turbulent Schmidt number approach

Desalination discharges are commonly in the form of inclined negatively buoyant jets (INBJs). Numerical predictions of INBJs remain a challenge. While accurate large eddy simulations (LES) of INBJs have become available very recently, they are substantially more resource intensive. Reynolds-averaged Navier–Stokes (RANS) modelling is potentially more efficient and can be more readily applied in practice. However, existing RANS simulations show substantial error when compared with experimental measurements. In this study, RANS simulations of 45° INBJs are performed with a dynamic turbulent Schmidt number (DTSN) approach. This new approach involves extracting turbulent Schmidt number (Sct) profiles in the INBJs from recently published LES data that have been validated by experiments. Detailed cross-sectional Sct profiles in INBJs are reported here for the first time. The relationship between Sct and a local mean flow parameter is also determined from the LES data. RANS simulations are then performed—with Sct being allowed to change dynamically during the simulation according to the pre-determined relationship. The results show that the DTSN approach improved the overall predictive capabilities of the RANS model to a limited extent. However, significant issues remain in terms of the models’ ability to predict dilutions in the descending portion of the flow. Importantly, the DTSN simulations demonstrate that the model predictions are sensitive to the determination of the relationship between Sct and the local flow parameter. Further improvements in the DTSN approach are therefore possible with refinement to the characterisation of this relationship. Based on a discussion of the present and recent literature describing RANS simulations of INBJs, the authors encourage a more cautious interpretation of the current predictive capabilities of RANS simulations in the context of INBJs.

Continuous data assimilation closure for modeling statistically steady turbulence in large-eddy simulation

A closure model is presented for large-eddy simulation (LES) based on the three-dimensional variational data assimilation algorithm. The approach aims at reconstructing high-fidelity kinetic energy spectra in coarse numerical simulations by including feedback control to represent unresolved dynamics interactions in the flow as stochastic processes. The forcing uses statistics obtained from offline high-fidelity data and requires only a few parameters compared to the number of degrees of freedom of LES. This modeling strategy is applied to geostrophic turbulence on the sphere and enables simulating indefinitely at reduced cost. The method accurately recovers the energy spectra and the zonal velocity profiles in the coarse model for three generic situations. Published by the American Physical Society 2025

A satellite-based analysis of semi-direct effects of biomass burning aerosols on fog and low-cloud dissipation in the Namib Desert

Abstract. In the Namib Desert, fog is the only regular water input and, thus, is a crucial water source for its fauna and flora. Each year, between June and October, absorbing biomass burning aerosols (BBAs) overlie the stratocumulus clouds in the adjacent Southeast Atlantic. In some synoptic settings, this layer of BBAs reaches Namibia and its desert, where it interacts with coastal fog and low clouds (FLCs). In this study, a novel 15-year data set of geostationary satellite observations of FLC dissipation time in the Namib Desert is used, along with reanalysis data, to better understand the potential semi-direct effects of BBAs on FLC dissipation in the Namib Desert, i.e., through adjustments of atmospheric stability and thermodynamics via the interaction of aerosols with radiation. This is done by investigating both the time of day when FLCs dissolve and the synoptic-scale meteorology depending on BBA loading. It is found that FLC dissipation time is significantly later on high-BBA-loading days. BBAs are transported to the Namib along moist free-tropospheric air by a large-scale anticyclonic recirculation pattern. At the surface, the associated longwave heating strengthens a continental heat low, which modifies the circulation and boundary layer moisture along the coastline, complicating the attribution of BBA effects. During high-BBA days, the vertical profiles of the temporal development of air temperatures highlight contrasting daytime and nighttime processes modifying the local inversion. These processes are thought to be driven by greenhouse warming as a result of the moisture in the BBA plumes and BBA absorption (only during the daytime). A statistical learning framework is used to quantify meteorological and BBA influences on FLC dissipation time. The statistical model is able to reproduce the observed differences in FLC dissipation time between high- and low-BBA days and attributes these differences mainly to differences in circulation, boundary layer moisture and near-surface air temperature along the coastline. However, the model is prone to underfitting and is not able to reproduce the majority of the FLC dissipation variability. While the model does not suggest that BBA patterns are important for FLC dissipation, the findings show how the moist BBA plumes modify local thermodynamics, to which FLC dissipation is shown to be sensitive. The findings highlight the challenges of disentangling meteorological and aerosol effects on cloud development using observations and invite detailed modeling analyses of the underlying processes, for example, with large-eddy simulations.

Large Eddy Simulations of a Medium-Scale Ethanol Pool Fire Using Conditional Source-Term Estimation Including Coupled Soot Radiation Effects

ABSTRACT The objective of this paper is to assess the combined capabilities of Conditional Source-Term Estimation with radiation and soot modeling in large eddy simulations of a medium-scale ethanol pool fire. Tabulated detailed chemistry is implemented including radiative losses. The radiative transfer equation is solved with the weighted sum of gray gas models to determine the gaseous absorption. Two subgrid soot models are considered using the laminar smoke point concept. The first approach calculates the soot formation and oxidation rates corrected to account for turbulent effects. The second determines the soot reaction rates in conditional space using analytical functions and the filtered reaction rates are determined by convolution with the filtered mixture fraction density function. Predictions of the time-averaged and root mean square temperature, species mole fractions and soot mass fraction are compared with experimental measurements. Numerical temperatures agree well with experiments except in the fire plume where some overpredictions are observed. Species concentrations match the measurements with some discrepancies observed in the products farther downstream, partly explained by the experimental uncertainty. The peak soot predicted with the first model is in reasonable agreement with the experiments but is much lower using the second approach. These differences are explained by the differences in the turbulence soot chemistry treatment and calibration of empirical constants. However, here, soot has a limited impact on the temperature, flow and mixing fields due to low soot concentrations produced by ethanol. The radiative heat fluxes are reasonably well predicted. Further validation is needed with additional experimental soot data.

GPU-Accelerated Full-Wheel Large-Eddy Simulations of a Transonic Fan Stage

Abstract A single-stage transonic axial-flow fan is simulated using graphic processing unit (GPU)-accelerated wall-modeled large-eddy simulations. The computational meshes are generated using Voronoi diagram-based approach. Two types of mesh are employed for grid sensitivity study. The first type uses isotropic hexagonal close-packed (HCP) seeding whereas the second combines the background HCP mesh with anisotropic boundary-layer type of mesh around the blade surfaces. The effect of the rotor tip clearance is examined using a rotor-only configuration. The sweep of the performance curve at full rotation speed is carried out for both the rotor and the stage. The computational results are compared against the experimental measurement and excellent agreement is observed when adequate near-wall resolution is employed. The code performance of the GPU-accelerated solver is compared to the CPU-based version. The high throughput of the GPU solver significantly reduces the computational cost. On a mesh with 84 million control volumes, 10 rotor revolutions can be computed within 1 day using 20 GPUs.

Study of a mixing‐fog event using WRF‐LES numerical simulations

AbstractThe prediction of fog using numerical weather forecasting models is a continuing challenge due to the combined influence of processes at different spatial and temporal scales as well as nonlinear interactions between them, especially in coastal regions. The focus of this work is on a specific mixing‐fog event observed during the “Toward Improving Coastal Fog Prediction” field campaign at the Ferryland field site, when a cold‐frontal air mass arriving from the northeast approached the Downs peninsula, Newfoundland, Canada. Simulations with the Weather Research and Forecasting model using a Large Eddy Simulation option (WRF‐LES) were used to study physical processes at different scales contributing to the life cycle of fog. The model was thoroughly evaluated by conducting simulations with a suite of available model options and comparing results with observations, and the best set of options selected were used for simulations of the present field case to reveal the formation, evolution, and dissipation of fog. Our analysis suggests four factors that play a role on the fog formation: (i) synoptic scale – advection of cold moist air over shallow warmer coastal waters creates a shallow marine boundary layer capped by inversion; (ii) mesoscale – low cloud formation strengthens the inversion by releasing latent heat at the top of the cloud, thus generating convective instability and downward mixing in the cloud layer; this further enhances the descent of the lower boundary (base) of the cloud layer; (iii) local scale – near‐surface turbulence induced by the collision of cold denser air mass with an orographic barrier can promote mixing, cooling of the air and fog initiation; and (iv) microscale – mixing of near‐saturated with saturated air and decrease in temperature drive the water vapor condensation. All described processes have significant roles and play together to provide favorable conditions to patchy fog/mist formation for the described case.

High fidelity simulations of contaminant dispersion in an urban environment with comparison to magnetic resonance imaging measurements

The dispersion of a contaminant in an urban environment has the potential to impact a large population of people. In this work, a complex urban canopy flow based on the Oklahoma City downtown business district circa 2003 is studied using Magnetic Resonance Imaging (MRI) and high-fidelity Large Eddy Simulations (LES). MRI is a novel experimental technique that can provide high-resolution measurements in four dimensions (three spatial and temporal) for lab scale models. The experiments and simulations use the same geometry and boundary conditions providing a one-to-one comparison of the two methods. Results are presented on the time-averaged velocity and concentration fields, the temporal dynamics of the concentration plumes for a transient release, and a novel Cloud Identification Algorithm that can separate plumes produced by periodic contaminant releases used for ensemble averaging over many releases. The MRI and LES datasets both include millions of measurement voxels and the comparisons highlight the complex 3D nature of the flow including strong vertical velocities in spanwise street canyons and flow acceleration in streamwise street canyons. The concentration fields are qualitatively similar albeit the LES shows larger dispersion. A quantitative analysis with performance measures compares the datasets pointwise and demonstrates that the two 3D datasets are similar with respect to many measures including a fractional bias of 0.02 (ideal=0.0), correlation coefficient of 0.87 (ideal = 1.0), and the fraction points within a factor of 2 is 0.98 (ideal = 1.0). Plume analysis compares the arrival and residence time of contaminant and is found to vary significantly with location within the urban environment with arrival times between 0 and 1.25 and differences within the contaminant cloud less than 10% at most locations.

Artificial-neural-network-based subgrid-scale models in the strain-rate eigenframe for large-eddy simulation of compressible turbulent channel flow

Artificial-neural-network-based subgrid-scale models in the strain-rate eigenframe for large-eddy simulation of compressible turbulent channel flow

Large-eddy simulation of high-Reynolds-number turbulent channel flow controlled using streamwise travelling wave-like wall deformation for drag reduction

Large-eddy simulation of high-Reynolds-number turbulent channel flow controlled using streamwise travelling wave-like wall deformation for drag reduction

A Data-Driven Approach to Refine the Partially Stirred Reactor Closure for Turbulent Premixed Flames

AbstractAccurately predicting turbulent combustion processes is fundamental for optimizing efficiency, reducing pollutant emissions, and ensuring operational safety in combustion systems. To this purpose, computational fluid dynamics (CFD) simulations are widely employed. In particular, large eddy simulations (LES) balance prediction accuracy with computational efficiency by resolving only the most energy-containing scales of turbulence and rely on modeling the turbulence-chemistry interactions (TCI) occurring at the smallest scales. Among the existing closures, the partially stirred reactor (PaSR) model incorporates finite-rate chemistry and estimates a cell reacting fraction based on the local Damköhler number to account for the subfilter-scale TCI. Although widely validated in CFD computations, the PaSR model was found limited by the way it computes the cell reacting fraction. To tackle this point, our study proposes a machine learning (ML) enhanced partially stirred reactor model for LES. A fully connected neural network is trained on direct numerical simulation (DNS) data of turbulent premixed jet flames to compute a correction coefficient for the cell reacting fraction. Maintaining the original model shape, this ML-enhanced closure aims at bridging the gap between physics-based models and advanced data-driven techniques. The proposed formulation not only improves the prediction accuracy of quantities of interest such as the heat release rate but also features computational feasibility and generalisation capabilities over a large range of LES grid refinement. This demonstrates the significant potential of ML-aided TCI closures in future applications of combustion engineering.

Potential impacts of marine fuel regulations on an Arctic stratocumulus case and its radiative response

Abstract. Increased surface warming over the Arctic triggered by increased greenhouse gas concentrations and feedback processes in the climate system has been causing a steady decline in sea-ice extent and thickness. With the retreating sea ice, shipping activity will likely increase in the future, driven by economic activity and the potential for realizing time and fuel savings from using shorter trade routes. Moreover, over the last decade, the global shipping sector has been subject to regulatory changes that affect the physicochemical properties of exhaust particles. International regulations aiming to reduce SOx and particulate matter (PM) emissions mandate ships to burn fuels with reduced sulfur content or, alternatively, use wet scrubbing as an exhaust aftertreatment when using fuels with sulfur contents exceeding regulatory limits. Compliance measures affect the physicochemical properties of exhaust particles and their cloud condensation nucleus (CCN) activity in different ways, with the potential to have both direct and indirect impacts on atmospheric processes such as the formation and lifetime of clouds. Given the relatively pristine Arctic environment, ship exhaust particle emissions could cause a large perturbation to natural baseline Arctic aerosol concentrations. Low-level stratiform mixed-phase clouds cover large areas of the Arctic region and play an important role in the regional energy budget. Results from laboratory marine engine measurements, which investigated the impact of fuel sulfur content (FSC) reduction and wet scrubbing on exhaust particle properties, motivate the use of large-eddy simulations to further investigate how such particles may influence the micro- and macrophysical properties of a stratiform mixed-phase cloud case observed during the Arctic Summer Cloud Ocean Study campaign. Simulations with diagnostic ice crystal number concentrations revealed that enhancement of ship exhaust particles predominantly affected the liquid-phase properties of the cloud and led to decreased liquid surface precipitation, increased cloud albedo, and increased longwave surface warming. The magnitude of the impact strongly depended on ship exhaust particle concentration, hygroscopicity, and size, where the effect of particle size dominated the impact of hygroscopicity. While low-FSC exhaust particles were mostly observed to affect cloud properties at exhaust particle concentrations of 1000 cm−3, exhaust wet scrubbing already led to significant changes at concentrations of 100 cm−3. Additional simulations with the cloud ice water path increased from ≈ 5.5 to ≈ 9.3 g m−2 show more-muted responses to ship exhaust perturbations but revealed that exhaust perturbations may even lead to a slight radiative cooling effect depending on the microphysical state of the cloud. The regional impact of shipping activity on Arctic cloud properties may, therefore, strongly depend on ship fuel type, whether ships utilize wet scrubbers, and ambient thermodynamic conditions that determine prevailing cloud properties.

CFD study on the effect of the baffles geometry in sedimentation efficiency in wastewater treatments through Large Eddy Simulations

Sedimentation tanks represent one of the most important components of any water and wastewater treatment plants. The lack of knowledge of hydraulics in sedimentation tank leads to unnecessary capital and operating costs as well as water pollution in the form of excessive sludge. Improper and inadequate design cause overloading of filters, and lead to frequent backwashing, which in turn waste a significant percentage of treated water. Sedimentation tanks require a uniform flow field to ensure the correct operating conditions. Unfortunately, the development of circulation zones causes deep deviation from the uniformity, bringing negative effects on the efficiency of the tank. The focus of this study is to apply Computational Fluid Dynamics (CFD) to study and to improve the sedimentation efficiency through the optimization of the hydrodynamics inside settling tanks. In the present analysis, Large Eddy Simulation (LES) is used to simulate three-dimensional turbulent flow and scalar tracer transport in different settlers using a structured finite-volume discretization. The results show how the baffles’ geometry, as well as the inlet design, influences the retention time distribution of the tank, varying the sedimentation efficiency. In particular, the increase of baffles inside the tank reduces the free space and allows a more uniform distribution of velocity vectors. This reduces both short circuits and recirculation zones bringing the flow closer to the ideal condition. On the other hand, the inlet position influences the velocity on the tank’s bottom, with possible particles re-suspension effects.

Turbulent flow pattern and flow resistance characteristics of cross flow over square-arranged tube bundles with different pitch to diameter ratios

Helical tube bundles are used in steam generators and intermediate heat exchangers of high temperature gas-cooled reactors due to their compactness and good thermal expansion adaptation performance. However, the characteristics of cross flow over inline tube bundles are sensitive to pitch to diameter ratios (S/D) and Reynolds numbers (Re), and the influence of S/D and Re variation on the flow patterns (especially wake patterns) and pressure drop coefficients (ξ) remains unclear. In the current investigation, the flow characteristics of tube bundles with S/D = 1.58 and 1.88 with various Re are investigated with the aid of wind tunnel experiments and large eddy simulations (LES). For the tube bundle with S/D = 1.88, the results of LES with periodical geometry align well with wind tunnel experiments, successfully predicting the decreasing recirculation region size as Re increases. In contrast, for the tube bundle with S/D = 1.58, the recirculation region size remains almost constant with varying Re, filling the space between two adjacent tubes even when Re = 36 000. However, the LES with periodical geometry only successfully predicts flow phenomena up to Re = 25 285. The wakes become oblique when Re = 36 000, which differs from experiments. Based on the force balance on the recirculation region, the pressure drop coefficient (ξ) of the cross flow over tube bundles is related to the size of the recirculation region. For the tube bundle with S/D = 1.88, the recirculation region size decreases as Re increases when Re ≥ 18 000, resulting in a larger flow cross section area in the main flow region. The increasing main flow cross section area leads to an increased pressure coefficient along the separation streamlines. Since the Reynolds normal and shear stresses cancel each other out, the increasing pressure coefficients along the recirculation region boundary lead to the increasing surface pressure coefficients in the rear side of the tube and ultimately lead to the ξ decrease from 0.26 to 0.24 when Re increases from 18 000 to 44 571. Conversely, when Re ≤ 10 285, the recirculation area fills the space between two adjacent tubes, so the ξ barely change with Re. For tube bundle with S/D = 1.58, the recirculation area fills the space between tubes even when Re ≥ 18 000, leading to almost the unchanged ξ (≈0.27) with Re. The higher ξ at Re = 10 285 is related to the bounding wall effects on the near wall tubes.

Derivation and Implementation of a Non‐Local Term to Improve the Oceanic Convection Representation Within the k–ɛ Parameterization

AbstractThe representation of turbulent fluxes during oceanic convective events is important to capture the evolution of the oceanic mixed layer. To improve the accuracy of turbulent fluxes, we examine the possibility of adding a non‐local component in their expression in addition to the usual downgradient part. To do so, we extend the – algebraic second‐moment closure by relaxing the assumption on the equilibrium of the temperature variance . With this additional evolution equation for the temperature variance, we obtain a –– model (the “” model) which includes a non‐local term for the temperature flux. We validate this new model against Large Eddy Simulations (LES) in three test cases: free convection (FC), wind‐driven mixing, and diurnal cycle (DC). For wind‐driven mixing, is equivalent to –. However, in the presence of a buoyancy flux (FC and DC), we find that the vertical profile of temperature of the LES is better captured by than –. Particularly, the non‐local term increases the fraction of the mixed layer that is stably stratified. For FC, this fraction is near 50% for both and the LES, whereas the – value is 20%. We show that this improvement is due to a better representation of the temperature variance in the inner part of the mixed layer. This better representation is mainly caused by the diffusion of temperature variance, which is described by and not by –.

Cavitation dynamics and thermodynamic effect of R134a refrigerant in a Venturi tube.

Cavitation plays a crucial role in the reliability of components in refrigeration systems. The properties of refrigerants change significantly with temperature, thereby amplifying the impact of thermodynamic effects. This study, based on the Large Eddy Simulation (LES) method and the Schnerr-Sauer (S-S) cavitation model, investigates the transient cavitating flow characteristics of the R134a refrigerant in a Venturi tube (VT). The bubble number density in the S-S model was improved based on the experimental data of pressure and temperature. Simulation results indicate that there are two shedding modes of cavitation clouds in R134a refrigerant. One is induced by the combined action of reentrant flow and the vortices centrifugal force, while the other is generated by the central jet of the mainstream and the reverse jet produced by the collapsing cavitation bubbles. Furthermore, the thermodynamic effects of the refrigerant exert a certain inhibitory effect on cavitation, revealing the causes of instability in the refrigerant cavitation interface and the shedding characteristics of cavitation clouds. The relationship between local sound speed, flow velocity, and heat conduction rate in the cavitation region was studied, unveiling a time-lag in temperature changes relative to pressure changes in the intensive cavitation region. This study provides insights into the complex cavitation dynamics, especially in R134a refrigerant systems, and provides an approach for accurately predicting and managing cavitation in various industrial applications.

Dissecting inertial clustering and sling dynamics in high-Reynolds number particle-laden turbulence

We advance the understanding of inertial clustering and the role of sling events in high-Reynolds number (Re) particle-laden turbulence. To this end, we perform one-way coupled particle tracking in flow fields obtained from direct numerical simulations (DNS) of forced homogeneous isotropic turbulence. Additionally, we examine the impact of filtering utilized in large eddy simulations by applying a sharp spectral filter to the DNS fields. Our analysis reveals that while instantaneous clustering through the centrifuge mechanism explains clustering at early times, the path history effect—the sampling of fluid flow along particle trajectories—becomes important later on. The filtered fields expose small-scale fractal clustering that cannot be predicted by the instantaneous flow field. We show that there exists a filter-effective Stokes number that governs the degree of fractal clustering and preferential sampling, revealing scale-similarity in the spatial distributions and fractal dimensions. Sling events are prevalent throughout our simulations and impose prominent patterns on the particle fields. In pursuit of investigating the sling dynamics, we compute the relative velocity, averaged over proximal neighboring particles, to identify particles undergoing caustics. As postulated in recent theories, we find that in fully resolved, high-Re turbulence, sling events occur in thin sheets of high strain, situated between turbulent vortices. This behavior is driven by rare, extreme events of compressive straining, manifested by characteristic fluctuations of the flow velocity gradients.

The effects of orifice shape on the dominant jet frequency in crossflow

The jet in crossflow describes a unique flow characteristic, which involves the injection of a fluid jet into a turbulent boundary layer. This flow structure is significant for applications in vibration reduction, noise suppression, and cooling and heat transfer. In this study, a numerical model for jet-in-crossflow was established using Large Eddy Simulation, and the accuracy of simulation results was validated by comparison with experimental data. On the basis of maintaining the same jet exit flow rate, the study investigated the differences in fundamental flow characteristics, wall pressure fluctuations, and flow noise among jet-in-crossflow cases with circular, square, and elliptical orifices. The distribution of sound sources for the three cases was identified using vortex sound theory. The study shows that the elliptical orifice case did not develop a jet blockage effect similar to the other cases. All three orifice cases generated counter-rotating vortex pairs, although the vortex core positions varied. For the circular and square orifices, the root mean square pressure along the lower edge of the orifice exhibited a symmetric distribution, while the elliptical orifice case showed no clear symmetry. In the downstream region, spanning 2–10 orifice diameters, a stable dominant frequency was observed for all three cases, which is attributed to vortex transport. The elliptical orifice demonstrated significant noise reduction performance, with a noise reduction of 3–8 dB, mainly concentrated in the downstream region up to 10 orifice diameters. Using Proper Orthogonal Decomposition and Dynamic Mode Decomposition, the relationship between vortex transport and wall pressure fluctuations for the three cases was explained. The analysis revealed the fundamental reason behind the noise reduction capabilities of the elliptical orifice and the vortex structures responsible for generating the dominant frequency.

Effects of side ratio on wind load characteristics on high-rise building

This study investigates the impact of varying side ratios (SR) on wind loads in high-rise buildings using wind tunnel tests and large eddy simulations. It assesses surface wind load by analyzing static three-component force coefficients and shape factors across different SRs. The results show that the model with D/B = 0.5 exhibits the largest mean and r.m.s drag forces, while the model with square cross section (D/B = 1) experiences the lowest torque. Meanwhile, the model with D/B = 0.5 reveals strong vertical but relatively weak horizontal wind pressure correlation. In addition, models with large SRs exhibit altered wind pressure mechanisms due to the occurrence of flow reattachment and secondary separation, resulting in lower side-surface correlation compared to small SR models.

Numerical study on benefits of curved serrations upon suppressing turbulent boundary layer trailing-edge noise

Turbulent boundary layer trailing-edge noise can be effectively reduced by installing serrations on wind turbine blades. This study designs iron-shaped trailing-edge serrations with Bessel curves and investigates the noise reduction mechanism of three iron-shaped serrations (IS-0.25, IS-0.5, IS-0.75) with different curvatures installed on the NACA0018 airfoil using numerical methods. Large Eddy Simulation and Ffowcs-Williams and Hawkings acoustic analogy integral formula are employed to calculate the flow field and the far-field noise under Reynolds number Re=1.6×105. The results indicate that iron-shaped serrations achieve better aerodynamic performance and noise reduction compared to airfoils without serrations (Baseline) and with triangular serrations. IS-0.75 has the highest lift and lift-to-drag ratio at attack angles of 0∘ to 8∘. For attack angle α=6∘, the fluid near the trailing edge of IS-0.75 adheres well to the airfoil surface, delaying flow separation and suppressing vortex shedding, with maximum low-to-moderate frequency noise reduction of 16.2 dB compared to Baseline.

Analytical modeling of wind-turbine wakes behind an abrupt rough-to-smooth surface roughness transition

Numerous wind farms are planned and built in the coastal or forest-to-grassland transition areas with abrupt rough-to-smooth surface roughness change. Behind the abrupt change, the atmospheric boundary layer (ABL) undergoes a complex transition process which brings big challenges to the canonical wake models of wind turbines. To this end, we employ large eddy simulation (LES) to investigate the development of the ABL and the evolution of wind-turbine wakes at different positions under roughness abruption from rough to smooth, and propose a novel analytical wake model. Due to the abrupt change of surface roughness, pressure gradient forms around the abruption and the internal boundary layer (IBL) develops downstream. The wind turbine near the abruption point is influenced by the pressure gradient, resulting in smaller wake width, while those situated within the IBL are significantly affected by the flow transition, resulting in systematic differences in wake recovery. To explicitly account for the flow transition in the wake model, we introduce an equivalent additional thrust to represent the momentum contribution caused by both background velocity and Reynolds stress. A detailed budget analysis is then conducted around the wind turbine and shows that the equivalent additional thrust is highly correlated with the streamwise turbulence intensity. Finally, a new wake model under roughness abruption is developed and compared with the LES data. Results show that the proposed model demonstrates superior performance over the existing models.