Turbulent Boundary Layer Flow Research Articles

A Comparative Study of Structured and Cut-Cell Grids Applied to an Oil-Injected Screw Compressor

Abstract Discretized Partial Differential Equations (PDEs) for numerical modeling of fluid mechanics systems require the use of various iterative linear solvers. In this study, two different CFD solvers, Ansys CFX and Converge, were employed to develop a transient 3D CFD model of an oil-injected screw compressor. Each solver utilized distinct meshing techniques—Ansys with a structured grid and Converge with a cut-cell grid. The numerical models have been validated utilizing experimental measurements. Presence of turbulent boundary layer and shear flow topology in the rotating fluid domains required implementing k-ω Shear Stress Transport (SST) turbulence model along with the physics needed to capture multifluid interfaces. In CONVERGE CFD, Semi Implicit Pressure Linked Equation (SIMPLE) algorithm was used for initial model development and pressure-velocity coupling in a collocated grid model, eliminating checkerboard numerical oscillations with the Rhie-Chow interpolation scheme. Ansys CFX handles pressure-velocity interactions through its solver framework, which operates without requiring a separately defined pressure-velocity coupling algorithm. These model parameters and pressure velocity coupling algorithms are kept unchanged while comparing preconditioned Successive Over Relaxation (SOR) and Incomplete Lower and Upper triangular (ILU) decomposition. These two solvers yielded to different numerical instabilities and rate of convergence, affecting the simulation clock time.

Experimental characterization and similarity scaling of smooth-body flow separation and reattachment on a two-dimensional ramp geometry

The results of an experimental investigation of smooth-body adverse pressure gradient (APG) turbulent boundary layer flow separation and reattachment over a two-dimensional ramp are presented. These results are part of a larger archival smooth-body flow separation data set acquired in partnership with NASA Langley Research Center and archived on the NASA Turbulence Modeling Resource website. The experimental geometry provides initial canonical turbulent boundary layer growth under nominally zero pressure gradient conditions prior to encountering a smooth, two-dimensional, backward facing ramp geometry onto which a streamwise APG that is fully adjustable is imposed. Detailed surface and off-surface flow field measurements are used to fully characterize the smooth-body APG turbulent boundary layer separation and reattachment at multiple spanwise locations over the ramp geometry. Unsteady aspects of the flow separation are characterized. It is shown that the first and second spatial derivatives of the streamwise static surface pressure profile are sufficient to determine key detachment and reattachment locations. The imposed streamwise APG gives rise to inflectional mean velocity profiles and the associated formation of an embedded shear layer, which is shown to play a dominant role in the subsequent flow development. Similarity scaling is developed for both the mean velocity and turbulent stresses that is found to provide self-similar collapse of profiles for different regions of the ramp flow. Despite the highly non-equilibrium flow environment, a new similarity scaling proved capable of providing self-similar turbulent stress profiles over the full streamwise extent of flow separation and downstream reattachment.

Extension of the local domain-free discretization method to large eddy simulation of compressible flows

Most of the flow problems encountered in practical engineering are wall-bounded turbulent flows at high Reynolds numbers. Wall-modeled large eddy simulation (WMLES) is one of the most viable approaches for predicting these realistic flows. Immersed boundary (IB) approach is an efficient computational technique to solve flow problems involving complex and/or moving geometries. This work extends a sharp-interface IB method, named the local domain-free discretion (DFD), to WMLES of compressible flows at high Reynolds numbers. An equilibrium wall model based on solving the simplified compressible turbulent boundary layer equations is utilized to alleviate the requirement of high near-wall mesh resolution. In conjunction with the approximate boundary conditions prescribed by the modeled wall shear stress and wall heat flux, the tangential velocity and temperature at an exterior dependent node are evaluated. Then, the closure of the discrete form of governing equations at an interior node in the immediate vicinity of the immersed wall is accomplished. A simple non-equilibrium correction of the wall shear stress provided by the equilibrium wall model is introduced explicitly. The WMLES/DFD method is applied to a supersonic zero-pressure-gradient turbulent boundary layer flow, a shock wave/flat-plate boundary layer interaction, a supersonic compression ramp flow and high-speed turbulent Couette flows with various thermal boundary conditions. The influence of grid resolution is investigated in the simulation of zero-pressure-gradient turbulent boundary layer flow. By comparing the computed results with the referenced experimental data and/or numerical results, the accuracy and ability of the WMLES/DFD method to simulate compressible turbulent flows are verified.

JAX-Fluids 2.0: Towards HPC for differentiable CFD of compressible two-phase flows

In our effort to facilitate machine learning-assisted computational fluid dynamics (CFD), we introduce the second iteration of JAX-Fluids. JAX-Fluids is a Python-based fully-differentiable CFD solver designed for compressible single- and two-phase flows. In this work, the first version is extended to incorporate high-performance computing (HPC) capabilities. We introduce a parallelization strategy utilizing JAX primitive operations that scales efficiently on GPU (up to 512 NVIDIA A100 graphics cards) and TPU (up to 1024 TPU v3 cores) HPC systems. We further demonstrate stable parallel computation of automatic differentiation gradients across extended integration trajectories. The new code version offers enhanced two-phase flow modeling capabilities. In particular, a five-equation diffuse-interface model is incorporated which complements the level-set sharp-interface model. Additional algorithmic improvements include positivity-preserving limiters for increased robustness, support for stretched Cartesian meshes, refactored I/O handling, comprehensive post-processing routines, and an updated list of state-of-the-art high-order numerical discretization schemes. We verify newly added numerical models by showcasing simulation results for single- and two-phase flows, including turbulent boundary layer and channel flows, air-helium shock bubble interactions, and air-water shock drop interactions.

Non-equilibrium turbulent boundary layers in high reynolds number flow at incompressible conditions: effects of streamline curvature and three dimensionality

The physics and computational prediction of turbulent boundary layer flow over axisymmetric and three-dimensional bodies are examined. Three cases were considered for which extensive experimental results and companion Reynolds-averaged Navier Stokes (RANS) solutions were obtained and/or available in the open literature. These cases all have Reynolds numbers based upon the freestream velocity and body geometric scale on the order of 10 5 to 10 6 , which is large for laboratory scales but small compared to the maximum scales observed for full-scale vehicles. Despite significant differences in approach flow fields and geometries for these three cases, some common themes emerged in the findings. All cases involved complications due to pressure gradients combined with streamwise curvature, and all exhibited regions of turbulence reduction due to accelerated flow. These complications led to discrepancies in computed results even in attached flow regions where it is often assumed that RANS models provide reliable predictions. The authors recommend further work on modelling approaches that can capture rapid distortion effects on turbulence transport that can be incorporated into industry-useful frameworks. Two cases involving laterally symmetric, three-dimensional wall-mounted hills with aft-body separation revealed that asymmetric mean flow fields are likely to result. This finding has been observed in experiments conducted in multiple facilities and in computations using multiple solvers and turbulence models. It is concluded that non-unique and asymmetric global flow solutions are fundamental to flow cases with lateral geometric symmetry involving turbulent boundary layer separation. Further work is also needed to accurately predict low-frequency unsteadiness due to geometries that produce non-unique mean flow fields. For such flows, it remains to be definitively determined whether experimentally observed modes of the mean flow are equivalent, or nearly equivalent, to asymmetric mean flow solutions obtained using RANS approaches.

Small-scale Helmholtz resonators with grazing turbulent boundary layer flow

ABSTRACT Helmholtz resonators flush-mounted in a wall beneath turbulent boundary layer flow are studied by focusing on their flow-induced excitation and effect on the grazing turbulent flow. A particular focus lies on single resonators tuned to the most intense spatio-temporal fluctuations in the near-wall vertical velocity and wall-pressure, residing at a spatial scale of λ x + ≈ 250 (or temporal scale of T + ≈ 25 ). Resonators are examined in a boundary layer flow at R e τ ≈ 2280 . Two neck-orifice diameters of d + ≈ 68 and 102 are considered, and for each value of d + three different resonance frequencies are studied (corresponding to a period of T + ≈ 25 , as well as one lower, and one higher, period). The response of the TBL flow is analysed by employing velocity data from hot-wire anemometry and particle image velocimetry measurements. Passive resonance only affects streamwise velocity fluctuations in the region y + ≲ 25 , while vertical velocity fluctuations due to resonance reach up to y + ≈ 100 . A narrow-band increase in streamwise turbulence kinetic energy at the resonance scale co-exists with a more than 20% attenuation of lower-frequency energy. Current findings on single resonator cases will aid in the development of passive surfaces with distributed resonators for boundary-layer flow control.

Analysis of drag reduction and partial setup of riblets surface on the airfoil

Using riblet structures to modulate the turbulent boundary layer to reduce frictional drag is important for vehicle stability and range. The flow on the airfoil surface at different angles of attack is different, and the effect of the riblets structure on the turbulent boundary layer flow will be changed, which in turn affects the drag reduction effect. In this paper, the drag reduction characteristics of V-shaped riblets are investigated experimentally by the particle image velocimetry technique. The distributions of mean velocity, friction coefficient, drag reduction rate, and coherent structure in the boundary layer on the airfoil surface at angles of attack from 0° to 12° are analyzed, and the effects of smooth and riblets surfaces on the turbulent flow characteristics near the wall are compared. Based on these results, the airfoil surface was zonally covered with riblets to investigate further the effects of the riblets' covering positions on the drag reduction of the airfoil at different angles of attack. The results show that the riblets reduce the intensity, distribution, and probability of the eject and sweep events in the turbulence bursts by suppressing the velocity fluctuations at the near-wall surface, thus realizing the reduction of turbulence drag. The zoned arrangement of riblets can effectively regulate the airfoil surface flow and reduce the unfavorable effects of the riblets on the laminar flow region and flow separation region on the surface of the airfoil with different angles of attack, and the results of the study can provide a reference for the influence of the coverage range of the riblets on the drag reduction effect.

Impacts of building modifications on the turbulent flow and heat transfer in urban surface boundary layers

This study examines turbulent airflow and upward heat transport in real urban environments using a building-resolving large-eddy simulation model to understand the characteristics of turbulent airflow and upward heat transport when geometrical distributions of buildings are modified. The target areas were two real urban districts within Osaka City, Japan, having different morphological features. In the numerical experiments, the initial condition was set to a neutral condition in which temperature is uniformly distributed vertically, and buildings emitted heat at a constant rate. The results in the two districts indicated that the features of turbulence and heat transport distinctly differed with different building arrangement. Specifically, taller buildings significantly decelerated airflows and induced warming behind buildings. More high-rise buildings (which resulted in a larger building variability) in a district with a larger building density caused a large heat flux and warming at higher levels. The sensitivity experiments in which a density and height variability of buildings were modified showed that a building density at higher levels and a building height variability significantly influenced warming at upper levels. An increased building height variability weakened wind speed and disturbed horizontal heat advection, whereas a large building density caused numerous heat sources.

Parallel and scalable AI in HPC systems for CFD applications and beyond

This manuscript presents the library AI4HPC with its architecture and components. The library enables large-scale trainings of AI models on High-Performance Computing systems. It addresses challenges in handling non-uniform datasets through data manipulation routines, model complexity through specialized ML architectures, scalability through extensive code optimizations that augment performance, HyperParameter Optimization (HPO), and performance monitoring. The scalability of the library is demonstrated by strong scaling experiments on up to 3,664 Graphical Processing Units (GPUs) resulting in a scaling efficiency of 96%, using the performance on 1 node as baseline. Furthermore, code optimizations and communication/computation bottlenecks are discussed for training a neural network on an actuated Turbulent Boundary Layer (TBL) simulation dataset (8.3 TB) on the HPC system JURECA at the Jülich Supercomputing Centre. The distributed training approach significantly influences the accuracy, which can be drastically compromised by varying mini-batch sizes. Therefore, AI4HPC implements learning rate scaling and adaptive summation algorithms, which are tested and evaluated in this work. For the TBL use case, results scaled up to 64 workers are shown. A further increase in the number of workers causes an additional overhead due to too small dataset samples per worker. Finally, the library is applied for the reconstruction of TBL flows with a convolutional autoencoder-based architecture and a diffusion model. In case of the autoencoder, a modal decomposition shows that the network provides accurate reconstructions of the underlying field and achieves a mean drag prediction error of ≈5%. With the diffusion model, a reconstruction error of ≈4% is achieved when super-resolution is applied to 5-fold coarsened velocity fields. The AI4HPC library is agnostic to the underlying network and can be adapted across various scientific and technical disciplines.

Prediction of Turbulent Boundary Layer Flow Dynamics with Transformers

Time-marching of turbulent flow fields is computationally expensive using traditional Computational Fluid Dynamics (CFD) solvers. Machine Learning (ML) techniques can be used as an acceleration strategy to offload a few time-marching steps of a CFD solver. In this study, the Transformer (TR) architecture, which has been widely used in the Natural Language Processing (NLP) community for prediction and generative tasks, is utilized to predict future velocity flow fields in an actuated Turbulent Boundary Layer (TBL) flow. A unique data pre-processing step is proposed to reduce the dimensionality of the velocity fields, allowing the processing of full velocity fields of the actuated TBL flow while taking advantage of distributed training in a High Performance Computing (HPC) environment. The trained model is tested at various prediction times using the Dynamic Mode Decomposition (DMD) method. It is found that under five future prediction time steps with the TR, the model is able to achieve a relative Frobenius norm error of less than 5%, compared to fields predicted with a Large Eddy Simulation (LES). Finally, a computational study shows that the TR achieves a significant speed-up, offering computational savings approximately 53 times greater than those of the baseline LES solver. This study demonstrates one of the first applications of TRs on actuated TBL flow intended towards reducing the computational effort of time-marching. The application of this model is envisioned in a coupled manner with the LES solver to provide few time-marching steps, which will accelerate the overall computational process.

Abyssal Slope Currents

Abstract Realistic computational simulations in different oceanic basins reveal prevalent prograde mean flows (in the direction of topographic Rossby wave propagation along isobaths; a.k.a. topostrophy) on topographic slopes in the deep ocean, consistent with the barotropic theory of eddy-driven mean flows. Attention is focused on the Western Mediterranean Sea with strong currents and steep topography. These prograde mean currents induce an opposing bottom drag stress and thus a turbulent boundary-layer mean flow in the downhill direction, evidenced by a near-bottom negative mean vertical velocity. The slope-normal profile of diapycnal buoyancy mixing results in down-slope mean advection near the bottom (a tendency to locally increase the mean buoyancy) and up-slope buoyancy mixing (a tendency to decrease buoyancy) with associated buoyancy fluxes across the mean isopycnal surfaces (diapycnal downwelling). In the upper part of the boundary layer and nearby interior, the diapycnal turbulent buoyancy flux divergence reverses sign (diapycnal upwelling), with upward Eulerian mean buoyancy advection across isopycnal surfaces. These near-slope tendencies abate with further distance from the boundary. An along-isobath mean momentum balance shows an advective acceleration and a bottom-drag retardation of the prograde flow. The eddy buoyancy advection is significant near the slope, and the associated eddy potential energy conversion is negative, consistent with mean vertical shear flow generation for the eddies. This cross-isobath flow structure differs from previous proposals, and a new one-dimensional model is constructed for a topostrophic, stratified, slope bottom boundary layer. The broader issue of the return pathways of the global thermohaline circulation remains open, but the abyssal slope region is likely to play a dominant role.

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

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

Determination of Local Heat Transfer Coefficients and Friction Factors at Variable Temperature and Velocity Boundary Conditions for Complex Flows

Transient conjugate heat transfer measurements under varying temperature and velocity inlet boundary conditions at incompressible flow conditions were performed for flat plate and ribbed channel geometries. Therefrom, local adiabatic wall temperatures and heat transfer coefficients were determined. The data were analyzed using typical heat transfer correlations, e.g., Nu=CRemPrn, determining the local distributions of C and m. It is shown that they are closely linked. A relationship lnC=A−mB is observed, with A and B as modeling parameters. They could be related to parameters in log-law or power-law representations for turbulent boundary layer flows. The parameter m is shown to have a close link to local pressure gradients and, therewith, near wall streamlines as well as friction factor distributions. A normalization of the C parameter allows one to derive a Reynolds analogy factor and, therefrom, local wall shear stresses.

High-flexibility reconstruction of small-scale motions in wall turbulence using a generalized zero-shot learning

This study proposes a novel super-resolution (or SR) framework for generating high-resolution turbulent boundary layer (TBL) flow from low-resolution inputs. The framework combines a super-resolution generative adversarial neural network (SRGAN) with down-sampling modules (DMs), integrating the residual of the continuity equation into the loss function. The DMs selectively filter out components with excessive energy dissipation in low-resolution fields prior to the super-resolution process. The framework iteratively applies the SRGAN and DM procedure to fully capture the energy cascade of multi-scale flow structures, collectively termed the SRGAN-based energy cascade reconstruction framework (EC-SRGAN). Despite being trained solely on turbulent channel flow data (via ‘zero-shot transfer’), EC-SRGAN exhibits remarkable generalization in predicting TBL small-scale velocity fields, accurately reproducing wavenumber spectra compared to direct numerical simulation (DNS) results. Furthermore, a super-resolution core is trained at a specific super-resolution ratio. By leveraging this pretrained super-resolution core, EC-SRGAN efficiently reconstructs TBL fields at multiple super-resolution ratios from various levels of low-resolution inputs, showcasing strong flexibility. By learning turbulent scale invariance, EC-SRGAN demonstrates robustness across different TBL datasets. These results underscore the potential of EC-SRGAN for generating and predicting wall turbulence with high flexibility, offering promising applications in addressing diverse TBL-related challenges.

Benchmarking Data Assimilation Algorithms For 3D Lagrangian Particle Tracking

This paper reports a comparison of three state-of-the-art data assimilation (DA) algorithms for 3D Lagrangian particle tracking (LPT): Vortex-In-Cell sharp (VIC#), FlowFit3, and neural-implicit particle advection (NIPA). Particle trajectories, termed “tracks,” are spatially sparse, and a reconstruction algorithm is commonly employed to estimate dense Eulerian fields using position, velocity, and/or acceleration data from the tracks. DA algorithms for LPT combine the tracks with a set of governing equations (or constraints) to enhance the accuracy of the velocity field, relative to interpolation methods, and infer additional quantities like pressure. We compare the performance of VIC#, FlowFit3, and NIPA with respect to their accuracy and computational cost. Accuracy is assessed in terms of the mean inter-particle distance, frame rate, and magnitude of tracking errors, and costs are reported in wall time. Synthetic and experimental data sets for homogeneous isotropic turbulence and turbulent boundary layer flows are evaluated; direct numerical simulations are used for the synthetic tests, and realistic localization errors are added to the simulated tracks. All three DA methods perform well in cases with the highest spatio-temporal sampling of the flow, and all three methods are relatively robust to the frame rate and magnitude of localization errors. NIPA is more resilient to sparse seeding than FlowFit or VIC#, which exhibit similar performance, but NIPA is also the most expensive technique by some margin. DA reconstructions are superior to interpolation across the board, with a reduction of error up to 80% in the experimental demonstration.

Near-Wall Flow Features In ZPG-TBL At Various Reynolds Numbers Using Dense 3D Lagrangian Particle Tracking

The 3D Lagrangian particle tracking method Shake-The-Box (STB) and, subsequently, the data assimilation method FlowFit3 have been applied to measure the flow field in a narrow wall-parallel volume inside the nearwall region of a zero-pressure-gradient (ZPG) turbulent boundary layer (TBL) flow at various Reynolds numbers. The STB experiments have been conducted in the 1m- wind tunnel facility of DLR in Göttingen at relatively high particle image densities (~0.07 ppp) using µm-sized DEHS particles and high-repetition pulse laser at up to 38.1 kHz. The results show that the chosen methodology is able to volumetrically resolve almost all features of the flow inside the viscous sub-, buffer- and lower logarithmic- layer in space and time at Reynolds numbers up to Re θ = 5,455. The gained data consists of time-series of spatially well resolved 3D velocity, acceleration and pressure fields, as well as a huge amount of long Lagrangian particle trajectories. Selecting the viscous sublayer part of the measurement volume provides time-series of the 2D distribution of both components of the instantaneous wall-shear stresses w,x/z . The resulting data are used for conditional and time-resolved 3D analyses of coherent structures, rare (e.g. back flow) events and two-point space-timecorrelations.

Estimating Velocity Correlations Using Single Pixel PIV

In this work, we analyze the possibility of determining correlations of turbulent velocity fluctuations from PIV data with improved spatial resolution. The analysis is based on the method presented by Oldenziel et al. (2023), where a joint probability density function of the velocity at two locations is calculated from the single-pixel ensemble correlation for these locations. Synthetic PIV images are used to discuss the occurrence of random and systematic errors and to derive the number of image pairs required for a determination of the correlation coefficient with desired uncertainty, depending on the particle image density. Compared to classical window correlation, the presented method can improve the spatial resolution by about one order of magnitude if a very large number of PIV image pairs are available and/or many statistically independent points with identical flow properties can be used. As an example of application, we show the spatial distribution of a two-point correlation in a compressible turbulent boundary layer flow for a reference point near the wall.

Exploring thermal buoyant flow in urban street canyons: Influence of approaching turbulent boundary layer

Turbulent boundary layer inflow is a critical factor in urban climate research, shaping canyon flow dynamics, air ventilation patterns, and heat flux distribution. In numerical simulation studies, it serves as a fundamental inflow boundary condition, profoundly influencing overall results. In this study, simultaneous Particle Image Velocimetry and Laser-Induced Fluorescence (PIV-LIF) measurements are utilized within a large closed-circuit water tunnel. This approach allows comprehensive flow data to be gathered under varied flow and thermal conditions, encompassing a spectrum of Richardson numbers ranging from 0.01 to 1.34. The investigation aims to elucidate the effects of turbulent boundary layer flows on heat transfer mechanisms and flow behaviours within a two-dimensional street canyon model with a unit aspect ratio. The analysis reveals distinct heat and fluid flow characteristics, highlighting the interplay between thermal conditions and flow dynamics. The three chosen turbulent boundary layer flows demonstrate unique influences on flow characteristics and heat removal capacity. Significant variations in ventilation rates are observed, with a maximum difference of 80% among the tested boundary layer flows. Additionally, the most pronounced variation in heat removal capacity is approximately 45%. Thicker boundary layers with lower velocities near the canyon exhibit reduced ventilation and heat removal capabilities. Furthermore, the investigation reveals that varied turbulence inlet profiles result in diverse fluctuating features at the canyon roof level, with a comparatively lesser impact on the deeper regions of the canyon.

Large-Eddy Simulations of Flow over a Backward-Facing Ramp with a Wall-Mounted Cube

Passive flow control devices, such as vortex generators (VGs), can effectively modulate the turbulent boundary layer flow near regions of adverse pressure gradients, but the interactions between the salient flow structures produced by VGs and those of the separated flow are not fully understood. In this study, a spatially evolving turbulent boundary layer interacting with a wall-mounted cube ahead of a backward-facing ramp is investigated using wall-resolved large-eddy simulations for a Reynolds number of 19,600, based on the inlet boundary layer thickness and freestream velocity. Different cube configurations are examined to isolate the effects of cube height and streamwise position. The large counter-rotating flow produced by the larger cubes generated more turbulent kinetic energy, thereby resulting in smaller separated regions over the ramp. Although significantly lower levels of turbulent kinetic energy dissipation than production are observed in the outer flow regions of the horseshoe vortex and in the induced counter-rotating flow, the spatial distribution of dissipation is similar to that of the turbulent kinetic energy. When the upstream position of an isolated single cube, relative to the leading ramp edge, is more than three cube heights, the streamwise decay of the counter-rotating flow results in lower levels of turbulent kinetic energy.

Aerodynamic and production comparison of wind farms with downwind versus conventional upwind turbines

Ever-increasing turbine scales and their associated logistical challenges have reignited questions about the performance of downwind rotor configurations. A particular potential benefit of downwind rotor configurations is the farm-scale power increase that may be conferred by tilt-driven downward wake entrainment and associated wake recovery. In this work, a comprehensive aerodynamic analysis is carried out to understand the mechanisms for wake entrainment and recovery across a spectrum of velocity and inflow alignment conditions on a small, structured farm in order to understand the impact of downwind rotors on farm production. The results show that the benefits demonstrated previously in the literature for downwind-rotor farms in aligned flows are fragile, and, outside of strong farm/flow alignment conditions, power production benefits for small farms with downwind rotor configurations are significantly if not completely mitigated by misalignment effects. The work indicates that farm-scale benefits for downwind rotors must be realized either from large-scale entrainment benefits, with more exotic farm arrangements that can take advantage of the aerodynamic effects, or from beneficial fatigue impacts from entrainment of less turbulent outer boundary layer flows.