When wind passes through the rotor of a wind turbine, the velocity is decreased while turbulence is increased. The region of decreased wind speed behind the rotor is known as the wind turbine wake and is bounded by a complex structure of helical vortices. This structure occurs to be more stable in low ambient turbulence and low tip speed ratio conditions, leading to a delayed recovery of the wake. The diminished wind speed in the wake leads to a decline in power output for downstream wind turbines, with this loss scaling proportionally to the cube of the velocity. This study uses field tests and simulations to evaluate enhanced wake recovery with segmented Gurney flaps on a 3.8-MW research wind turbine. Four Gurney flaps were attached at regions near the tip of each blade. This configuration is hypothesized to induce turbulence that destabilizes the vortex system, resulting in faster wake recovery. Field tests using a scanning LiDAR were conducted to quantify the wind turbine wake recovery between the baseline and the retrofitted configuration in various atmospheric conditions. The results show a consistent increase in wake recovery for the Gurney flap configuration, generally at all downstream distances. This was illustrated by a reduction of axial velocity deficits of roughly 10% at hub height, at five diameters downstream distance. The influence of retrofitting on turbine power and loads was limited. Summarizing, a very successful field test campaign was executed, which demonstrated the use of segmented Gurney flaps as a promising add-on to promote enhanced wind turbine wake recovery for improved overall wind farm performance.

Atmospheric gravity waves (AGWs) are large-scale wave-like flow structures commonly generated when atmospheric flows are vertically perturbed by topographical features or meteorological phenomena. These transient phenomena can significantly affect wind turbine outputs and loads; however, their influence on wake dynamics remains poorly understood, posing challenges for accurate wind farm modeling. In this study, we perform large-eddy simulation of wind turbines operating under an atmospheric condition reconstructed by assimilating lidar measurements of AGWs. Our results show that (i) low-frequency wake meandering becomes more pronounced owing to large-scale AGW flow structures and intensified smaller-scale turbulent structures. This enhanced meandering, combined with stronger turbulent mixing, accelerates mean wake recovery. (ii) The turbulence kinetic energy (TKE) spectrum in the wake region exhibits a peak Strouhal number of approximately 0.3, although the inflow spectrum peaks at significantly lower frequencies. This observation indicates that, under AGW conditions, wake turbulence generation follows a convective instability mechanism. Notably, faster wake recovery reduces wake shear, leading to lower amplification of TKE. Power analysis for two turbines arranged in a streamwise column further highlights the dominant role of convective instabilities. Large-amplitude, low-frequency power fluctuations observed at the most upstream turbine are significantly attenuated for downstream turbines as low-frequency velocity fluctuations are suppressed in the far-wake region. These findings add further insights into wake meandering and turbulence generation, offering guidance for modeling wind turbine and farm flows under non-stationary atmospheric conditions.

Accurate modeling of atmospheric turbulence is critical for the design and operation of next-generation large-scale wind turbines, particularly those exceeding 15 MW rated capacity and spanning well above the atmospheric surface layer (typically 10 − 20% of the atmospheric boundary layer (ABL)). In this study, Large Eddy Simulations (LES) were performed to investigate turbulence characteristics at high altitudes, up to 300 m above ground level — a region increasingly relevant for large turbine rotors. Turbulence coherence was analyzed and compared with field measurements to assess the fidelity of numerical predictions. Coherence estimates from LES were validated against lidar-based measurements obtained under stable, neutral, and unstable atmospheric conditions. Results show good agreement in the coherence decay rates and cross-spectral characteristics, with notable discrepancies only at very low frequencies (on the order of several 10^(−4) Hz) and large spatial separations (on the order of several 10^(2) m). Consequently, a LES-tuned empirical lateral coherence model is proposed, featuring distinct coherence decay rates for each atmospheric stability regime (stable, neutral, and unstable ABL), offering improved representation of turbulence structures across a range of operating conditions. These findings provide a valuable reference for refining turbulence models for improving load estimation methodologies for next-generation wind turbines operating at hub heights above 200 m.

Benchmarking numerical models is essential for validating their accuracy and ensuring consistency across simulation platforms. This study presents a comparative benchmark analysis of two widely used Large Eddy Simulation (LES) codes, AMR-WIND and NREL SOWFA-6, focusing on wind turbine rotor performance, wake dynamics, and atmospheric boundary layer (ABL) representation. The evaluation includes an actuator line model (ALM)-based uniform inflow wind turbine simulation and ABL precursors under neutral and unstable conditions. The uniform inflow wake analysis examined differences in wind turbine induction and wake development between the two codes. Additionally, neutral and unstable atmospheric boundary layer precursors were generated for an offshore environment and compared. Results indicate a difference in wake breakdown location between the codes (one contributing factor was the difference in numerical schemes used for the advection terms.) The number of actuator points required for smooth velocity distribution across the rotor was higher for SOWFA-6 than AMR-WIND. In ABL precursors, time-averaged flow fields showed strong agreement, though minor discrepancies in turbulence were observed, particularly in unstable conditions, affecting coherence analysis. The energy distribution across wavenumbers showed a good match between the codes, with slight discrepancies observed in the large and small wavenumber regions. The cutoff wavenumber was found to be similar for both codes. Lateral and vertical coherence at small and large separations were in close agreement for the neutral ABL. However, in the unstable ABL, notable differences in coherence were observed between the codes for separations greater than 40 m.

Large wind turbines face more intricate atmospheric conditions with turbulent coherent structures sized similarly to the rotor diameter, posing loading challenges. The present study assesses twelve distinct wind fields using the Large Eddy Simulations (LES) and International Electrotechnical Commission (IEC) Kaimal model scaled to their LES counterpart. The hub height wind speed in the different cases was set to 8.5 m/s (below-rated), 11.5 m/s (at-rated), and 14.5 m/s (above-rated). In a previous study, it was found that the unscaled IEC model-based wind field is conservative and scaled IEC model-based wind fields were found to yield different loads than upon use of LES-based wind fields in different atmospheric stability conditions. The present study aims to understand these differences. Utilizing Spectral Proper Orthogonal Decomposition (SPOD), the original wind fields were decomposed and reconstructed to study the influence of large and small coherent structures represented by their distinct frequencies. SPOD analysis was complemented by wind field spectral analysis considering atmospheric surface layer height, integral length scales, and co-coherence estimates. Integral length scales in the scaled IEC Kaimal model were found to be half of those in unstable atmosphere LES wind fields. The aero-elastic impact on the IEA 22 MW reference wind turbine with a 280 m rotor diameter was evaluated. The analysis reveals that large coherent structures, particularly low-frequency (≤0.06 Hz) ones, significantly impact wind turbine loads, contingent upon atmospheric stratification. Compared to the scaled IEC Kaimal model wind field, the maximum tower fore–aft bending moment and the maximum blade root flap-wise bending moment were found to be higher, for example, by 10% and 5% respectively in an unstable atmosphere during below-rated wind turbine operation. In the same scenario, standard deviation of the tower fore–aft bending moment was found to be higher by up to 50% while standard deviation of the blade root flap-wise bending moment was found to be lower by up to 25%. These findings underscore the critical importance of accurately modeling atmospheric turbulence and its coherent structures for more reliable design and operation of large wind turbines.

Synthetic wind fields generated for wind turbine simulations do not satisfy incompressibility condition, thus, are not divergence-free. This results in spurious pressure fluctuations when input as a boundary condition to, for example, incompressible large eddy simulations (LES). This study investigates the impact of divergence-free correction on synthetic wind fields and their influence on wind turbine loads. Although divergence-free correction methods exist, they often modify the wind field energy spectrum and unsteady characteristics. Ongoing research addresses these challenges, but the acceptability of such changes and their impact on wind turbine loads has not been adequately studied. This work enforced incompressibility using the Helmholtz–Hodge decomposition, solved through spectral and spatial methods. An efficient Fourier-based spectral method was implemented, validated, and tested against the traditional finite difference method used for the spatial approach. Synthetic wind fields based on three coherence models were analyzed under three turbine operating conditions. An aeroelastic analysis of the IEA (Formula presented.) MW wind turbine was performed in the (Formula presented.) wind fields before and after divergence correction. Spectral analysis revealed a reduction in energy at specific frequencies after the correction for incompressibility. Additionally, the standard deviations of the wind velocities changed (despite similar means), consequently affecting the aeroelastic turbine response. A new iterative correction method is proposed to mitigate these effects, which preserves first- and second-order statistics while enforcing a divergence-free condition. This method is recursively applied, maintaining RMSE changes to the wind field within user-specified bounds. Key findings show that the iterative method yields an excellent match in the longitudinal wind field energy spectrum and a closer match in wind field standard deviation across the rotor, reducing discrepancies in turbine response. Some discrepancies in the lateral and vertical velocity components' higher order statistics were observed. Standard divergence correction (without RMSE constraints) led to a decrease of up to 20% in the tower fore-aft moment, while the proposed method reduces this change to −10%. The tower top side-side moment was found to increase by (Formula presented.) % by using the former approach, while the proposed correction reduced this increase to (Formula presented.) %. Blade root flap-wise bending moment was less affected (up to 5% reduction). Divergence-free wind fields, even with similar statistical properties, influence aeroelastic loads. The proposed method aims to achieve physically consistent and more comparable wind field analyses and resulting wind loads.

With the growing trend towards larger wind turbine rotor diameters, the impact of wind shear on rotor performance and loads becomes increasingly significant. Atmospheric stability strongly influences wind shear, leading to higher wind shear under stable atmospheric conditions. In this study, the aeroelastic performance of the IEA 22 MW rotor is assessed under inflow conditions generated by different methods. Inflow conditions were generated using turbulence models specified in the IEC Standards and also by Large Eddy simulations. Standalone OpenFAST simulations were conducted with the respective inflow conditions. It was found that at rated and above-rated wind speeds, the time-averaged wind turbine design loads were higher in stable atmospheric conditions, in comparison to the IEC NTM inflow conditions, while the opposite held for below-rated wind speeds. Specifically, the time-averaged root flapwise bending moment and rotor thrust were found to be higher by up to 7% in stable atmospheres. However, maximum design and fatigue loads were considerably higher in the IEC NTM case due to elevated turbulence levels. Compared to the IEC NTM case, the damage equivalent root flapwise bending moment was found to be 30% to 70% lower in the different scenarios.

Wind power is one of the fastest-growing renewable energy technologies, with global installed wind-generation capacity having increased by a factor of almost 75 in the past two decades. The wind turbine rotors are increasing in diameter to achieve higher power output which poses various challenges in terms of parameters such as structural costs, logistics, maintenance and manufacturing standardization. Multi Rotor Wind Turbines are one potential betterment to Single Rotor Wind turbines. The aim of this study is to compare the performance of Multi Rotor Wind Turbine to a Single Rotor Wind Turbine using Computational Methodology. A total of 8 Horizontal Axis wind turbines which vary in terms of number of rotors, the rotor diameter and the placement of rotors, have been modelled using SolidWorks®. The flow simulations are carried out on ANSYS Fluent®. It is found that a 4 Rotor configuration with rotors placed in a square formation provides an increase in power output by 35% in comparison to its Single Rotor counterpart. Analysis of wake patterns shows that wake recovery is faster in lesser diameter configurations. The drag force is also found to be low in these configurations, which is beneficial in terms of structural costs and tip losses.

The airline industry faces a crisis in the future as consumer demand is increasing, but the environmental effects and depleting resources of kerosene mean that growth is unsustainable. Hydrogen is touted as the leading candidate to replace kerosene, but it needs significant technological and economical endeavors. In such a scenario, cryogenic liquid hydrogen (LH2) is predicted to be the most feasible method of using hydrogen. The major challenge of LH2 as an aircraft fuel is that it requires approximately four times the storage volume of kerosene—due to its lower density. Thus the design of cryogenic storage tanks to handle larger quantities of fuel is becoming increasingly important. But the increase in drag associated with larger storage tanks causes an increase in fuel consumption. Hence, this paper aims to evaluate the aerodynamic performance of different storage configurations and aid in the selection of an economic and efficient storage system. Using an Airbus A321 replica as the base model, we sized internal and external tanks to meet the mission fuel requirements and modelled the composite aircraft on SolidWorks®. Then we carried out flow simulation in ANSYS Fluent® to compute the lift and drag values of each storage configuration. For external tanks, we observed that a novel airfoil cross-section tank had the lowest drag value; it performed better than the capped cylinder tanks. Also external tanks kept below the wing lead to minimal disruption of the airflow. Among the internal configurations, we found that increasing the fuselage length is the most aerodynamically efficient way to store the fuel.