Wind Tunnel Data Research Articles

Investigation of the integration of an oscillating aerofoil-based energy harvester into the building roof

The increasing energy efficiency requirements have led to innovative renewable energy solutions being integrated into buildings. Several works have shown the potential of micro wind turbines on buildings. However, their implementations have been hindered by several challenges. Flow energy harvesting devices such as oscillating aerofoils provide potential, yet a literature gap exists regarding their integration into buildings. This study addresses this gap by investigating oscillating aerofoil wind energy harvesting system performance through numerical modelling. A coupled numerical model was introduced, integrating a novel computational approach using ANSYS Fluent with one degree of freedom in rotational motion. This methodology was introduced to analyze the dynamic behaviour and predict mechanical power output of the oscillating aerofoil wind energy harvesting system, which is a novel exploration in existing literature. Moreover, validation of the computational fluid dynamics model was conducted through using experimental wind tunnel data in the literature, and results demonstrated agreement between numerical and experimental results. To improve the wind energy harvesting system of a single oscillating aerofoil, it was integrated into building roof to take advantage of acceleration effects of building roof shape. The design improvement comprises of a novel wind energy harvesting system design of an oscillating aerofoil integrated into three different building roof including flat, pitched, and curved shapes to enhance energy efficiency. The numerical analysis demonstrated that integrating an oscillating NACA 0012 aerofoil into a curved roof resulted in the highest average power output. Specifically, the integration of the curved roof and the aerofoil yielded 18 watts, while the flat roof generated only 0.6 watts at a wind speed of 3 m/s. Integration into a pitched roof achieved 12 watts at 9 m/s. Comparatively, integrating the curved roof with the aerofoil increased power output by 50% compared to the pitched roof design at 9 m/s wind speed. Thus, variations in wind speed significantly impact performance. In addition, changes in wind direction from 0 to 10 degrees led to reduced efficiency and lower predicted power output. Lastly, the power spectral density for NACA 0012 integrated into the pitched and curved roof buildings revealed peaks at 5.8 Hz in 9 m/s wind speed conditions.

Design of Pseudo-Command Restricted Controller for Tailless Unmanned Aerial Vehicles Based on Attainable Moment Set

This work investigates the pseudo-command restricted problem for tailless unmanned aerial vehicles with snake-shaped maneuver flight missions. The main challenge of designing such a pseudo-command restricted controller lies in the fact that the necessity of control allocation means it will be difficult to provide a precise envelope of pseudo-command to the flight controller; designing a compensation system to deal with insufficient capabilities beyond this envelope is another challenge. The envelope of pseudo-command can be expressed by attainable moment sets, which leave some open problems, such as how to obtain the attainable moment sets online and how to reduce the computational complexity of the algorithm, as well as how to ensure independent control allocation and the convexity of attainable moments sets. In this article, an innovative algorithm is proposed for the calculation of attainable moment sets, which can be implemented by fitting wind tunnel data into a function to solve the problems presented above. Furthermore, the algorithm is independent of control allocation and can be obtained online. Moreover, based on the above attainable moment sets algorithm, a flight performance assurance system is designed, which not only guarantees that the command is constrained within the envelope so that its behavior is more predictable, but also supports adaptive compensation for the pseudo-command restricted controller. Finally, the effectiveness of the AMS algorithm and the advantages of the pseudo-command restricted control system are validated through two sets of independent simulations.

Influence of Various Urban Morphological Parameters on Urban Canopy Ventilation: A Parametric Numerical Study

Numerical simulation is vital for evaluating urban ventilation. However, accurate urban-scale ventilation modeling requires extensive building surface simulation for computational demand. The distributed drag force approach simplifies the urban canopy by modeling buildings as a porous volume that accounts for momentum and turbulence. This method is a practical solution for simulating urban airflow. The drag force coefficient (Cd) is a crucial aerodynamic parameter in this approach. This study examines how Cd varies with urban design parameters such as plan area density (λp), average building height (H), frontal area density (λf), floor aspect ratio (AR), and sky view factor (SVF). Employing extensive numerical simulations conducted under neutral atmospheric conditions, we explore ranges of λp = 0.04–0.07 and λf = 0.1–1.2. The numerical model has been validated against existing wind tunnel data. The results show that Cd is insensitive to the model scale and background wind speed. We discover a nonlinear relationship between Cd and the parameters λp, λf, and SVF. For urban layouts with cubic-shaped buildings, Cd peaks at different λp within the range of 0.2~0.8. When λp and H are constant, Cd has a linear relationship with AR and λf. It is recommended to use λp, SVF, and AR as predictors for Cd across various urban configurations.

Stochastic modelling of the instantaneous velocity profile in rough-wall turbulent boundary layers

The statistical properties of uniform momentum zones (UMZs) are extracted from laboratory and field measurements in rough wall turbulent boundary layers to formulate a set of stochastic models for the simulation of instantaneous velocity profiles. A spatiotemporally resolved velocity dataset, covering a field of view of $8 \times 9\,{\rm m}^2$ , was obtained in the atmospheric surface layer using super-large-scale particle image velocimetry (SLPIV), as part of the Grand-scale Atmospheric Imaging Apparatus (GAIA). Wind tunnel data from a previous study are included for comparison (Heisel et al., J. Fluid Mech., vol. 887, 2020, R1). The probability density function of UMZ attributes such as their thickness, modal velocity and averaged vertical velocity are built at varying elevations and modelled using log-normal and Gaussian distributions. Inverse transform sampling of the distributions is used to generate synthetic step-like velocity profiles that are spatially and temporally uncorrelated. Results show that in the wide range of wall-normal distances and $Re_\tau$ up to $\sim O(10^6)$ investigated here, shear velocity scaling is manifested in the velocity jump across shear interfaces between adjacent UMZs, and attached eddy behaviour is observed in the linear proportionality between UMZ thickness and their wall normal location. These very same characteristics are recovered in the generated instantaneous profiles, using both fully stochastic and data-driven hybrid stochastic (DHS) models, which address, in different ways, the coupling between modal velocities and UMZ thickness. Our method provides a stochastic approach for generating an ensemble of instantaneous velocity profiles, consistent with the structural organisation of UMZs, where the ensemble reproduces the logarithmic mean velocity profile and recovers significant portions of the Reynolds stresses and, thus, of the streamwise and vertical velocity variability.

Tehnika smanjenja opterećenja na unutrašnjim aerovagama tokom supersoničnih prelaznih pojava

Design of slender supersonic missiles requires a comprehensive experimental support in the form of wind tunnel data for a wide range of flight parameters (angle of attack and Mach number). However, in supersonic wind tunnel testing, the problem exists of transient loads at the times of the starting and stopping of the supersonic flow. In the environments of pronounced transient loads, characteristic of blowdowin wind tunnels like the T-38 of the Military technical Institute in Belgrade, it is necessary to provide control of the use of internal wind tunnel balances in the permitted design load ranges. The presented technique is related to the definition and implementation of a methodology for reducing the transient loads on wind tunnel balances in supersonic wind tunnel tests. By limiting the clearance between the model and its tail support (sting) to a magnitude which permits normal tests, but results in model-support contact during the excessive loads, part of the loads is transferred to the support sting, relieving the balance. The technique improves control over the wind tunnel test process, improves measurement accuracy and prevents damage to sensitive instrumentation (wind tunnel balances).

Experimental investigation and multi-objective optimization of savonius wind turbine based on modified non-dominated sorting genetic algorithm-II

A numerical data set will be developed to assist in the design of Savonius wind turbines. The main objective of study is to improve Savonius turbine blade designs to increase torque coefficients, rotational speeds, and pressure coefficients. Simulating 3D models and validating them with wind tunnel data were part of the experimental design methodology. Multi-objective optimization is used to optimize turbine performance. Twist angle, aspect ratio, and overlap ratio are all important factors in determining the optimal torque and power coefficients. Data-driven objective functions were modeled using the group method of data handling (GMDH). Using an evolutionary Pareto-based optimization approach, polynomial models were used to plot Pareto fronts and TOPSIS to calculate optimal commercial points. The torque coefficient, rotational speed, and power coefficient are all improved by 13.74%, 0.071%, and 5.32%, respectively. As a result of the multi-objective optimization of the turbine, some significant characteristics of objective functions were discovered.

Free-vortex models for wind turbine wakes under yaw misalignment – a validation study on far-wake effects

Abstract. Near-wake effects of wind turbine models using the free-vortex wake have been studied extensively, but there is a lack of validation for such predictions in the mid to far wake. This paper presents a novel validation study using three free-vortex wake models of increasing complexity: an actuator disc, an actuator disc with rotation, and a lifting-line model. We emphasise the application for dynamic wind farm flow control optimisation with a focus on wake redirection using yaw misalignment. For this purpose, wake models should provide sufficiently accurate power predictions at a low computational expense to enable real-time control optimisation. Three sets of wind tunnel data are used for validation: flow measurements under steady yaw misalignment, time-resolved flow measurements for a step change in yaw, and turbine output measurements with yaw control and simulated wind direction variation. Results indicate that the actuator-disc model provides the best balance between computational cost and accuracy in power predictions for the mid to far wake, which is not significantly improved upon by the addition of rotation. In the near wake, the added complexity of the lifting-line model may provide value as it models blade loading and individual tip vortices. Altogether, this study provides important validation for further studies into optimisation of wake steering under time-varying conditions and suggests that the actuator-disc model is a suitable candidate for use in a model-predictive wind farm flow control framework.

Estimating omnidirectional urban vertical wind speed with direction-dependent building morphologies

A main external factor that limits the energy assessment of high-rise buildings in urban areas is the vertical wind conditions. Conventional buildings' energy assessment tools apply a universal vertical wind profile estimation equation in all directions and only consider four typical terrain types. However, the various shape and configurations of buildings in cities can induce the unique wind speed in each direction, and the vertical wind speeds in the same terrain type can be different even in the same city. To get more realistic vertical wind conditions, this study developed an omnidirectional urban vertical wind speed estimation method with direction-dependent building morphologies. A pie-shaped segment method is applied to calculate building morphological features in approaching wind direction. Machine learning methods are developed to calculate parameters of the modified direction-dependent power law urban wind function to convert the Typical Meteorological Year (TMY) wind speed to urban vertical wind speeds. To validate the proposed method, wind tunnel data in Hong Kong are collected for a case study. The results indicate that the proposed method with morphological inputs can effectively estimate the vertical wind speed at different wind directions and heights, and deep neural networks and support vector regression have better performance.

Flow morphology of a supersonic gravitating sphere

ABSTRACT Stars and planets move supersonically in a gaseous medium during planetary engulfment, stellar interactions, and within protoplanetary discs. For a nearly uniform medium, the relevant parameters are the Mach number and the size of the body, R, relative to its accretion radius, RA. Over many decades, numerical and analytical work has characterized the flow, the drag on the body, and the possible suite of instabilities. Only a limited amount of work has treated the stellar boundary as it is in many of these astrophysical settings, a hard sphere at R. Thus, we present new 3D athena++ hydrodynamic calculations for a large range of parameters. For RA ≪ R, the results are as expected for pure hydrodynamics with minimal impact from gravity, which we verify by comparing to experimental wind tunnel data in air. When RA ≈ R, a hydrostatically supported separation bubble forms behind the gravitating body, exerting significant pressure on the sphere and driving a recompression shock, which intersects with the bow shock. For RA ≫ R, the bubble transitions into an isentropic, spherically symmetric halo, as seen in earlier works. These two distinct regimes of flow morphology may be treated separately in terms of their shock stand-off distance and drag coefficients. Most importantly for astrophysical applications, we propose a new formula for the dynamical friction, which depends on the ratio of the shock stand-off distance to RA. That exploration also reveals the minimum size of the simulation domain needed to accurately capture the deflection of incoming streamlines due to gravity.

A numerical study on urban-like block arrays’ drag force and its correlation with ventilation efficiency

This work conducted Computational Fluid Dynamics (CFD) simulations to investigate the drag force (F) and its relation to ventilation of four groups of urban-like block arrays with planar area index (λP ) ranging from 0.0625 to 0.56. Simulations were performed employing the standard k-ε turbulence model after conducting a grid sensitivity test and validating the computational settings against wind tunnel data. The results showed that cases with larger λp , slab-shaped buildings, and staggered layout have higher values of F. As for the subcases within each group, F shows a significant increase for 0.0625 < λp < 0.25, and then only a slight increase for 0.25 < λp < 0.56; while the drag coefficient (Cd ) shows a linear increase along with λp . The further linear regression analysis showed that the spatially averaged velocity and air change rate are strongly negatively correlated with F, which supports the effectiveness of F in reflecting ventilation efficiency, particularly for evaluating urban block-scale ventilation.

A Synthetic Integrated Wireless Aerodynamic Evaluation System for Train–Bridge System

The development of high-speed railway networks and the increased running speeds of high-speed trains (HSTs) have made the aerodynamic interference between HSTs and their surrounding environments increasingly important. Compared with a traditional wind tunnel test, systematically understanding the aerodynamic characteristics of HSTs involves relatively more stringent requirements, highlighting the need to develop experimental methods and technologies with enhanced dynamic performance. Central South University (CSU) developed a wireless data acquisition system, named as the in-model sensory and wireless data acquisition — remote control and processing system (ISWDA-RCPS), which can operate onboard a novel moving train and infrastructure rig. The system was developed to meet current wind tunnel data collection needs, and it avoids the physical cables used in conventional devices, which are extremely susceptible to induced noise. The system accepts inputs from various sensors and transfers the data wirelessly to an access point outside a wind tunnel’s test section. To analyze the feasibility of the ISWDA-RCPS concerning its sensing capabilities and wireless communications, we conduct experiments in multiple operating conditions. Finally, pressure measurements are acquired from a moving Fuxing HST model at different points and used to analyze the aerodynamic behavior of the model.

Establishment and validation of a relationship model between nozzle experiments and CFD results based on convolutional neural network

The acquisition of experimental data in a supersonic wind tunnel often faces challenges of complexity and high costs. Furthermore, there are limitations in the control of experimental conditions and measurement techniques. In this study, experiments were conducted on the start-up and shutdown processes of a single expansion ramp nozzle (SERN), and a dataset was established in conjunction with computational fluid dynamics (CFD). By utilizing experimental data and CFD simulation results, we employed a deep learning-based approach, utilizing one-dimensional convolutional neural networks (CNN), to establish a relationship model between the experimental and CFD results, with the aim of using CFD results to predict experimental outcomes. We provide detailed descriptions of the experimental methods, numerical simulation methods, and CNN model, and conduct training and testing of the model. The results demonstrate that the CNN model is capable of accurately predicting the wall pressure distribution of the SERN, with low prediction errors. In interpolation and extrapolation cases, the model exhibits good accuracy and generalization ability, with coefficients of determination above 96%. Compared to CFD calculations, the CNN model proves to be more reliable and accurate in predicting SERN performance. Additionally, we establish a comparative model that does not utilize CFD data to verify the superiority of the proposed CNN model. The results show that the CNN model with CFD data improves performance on average by 14%. This approach reduces reliance on experiments to a certain extent, lowering experimental costs and complexity. It not only saves the resources and time required for experiments but also compensates for the limitations in controlling experimental conditions and measurement techniques. Therefore, this research provides a viable solution to overcome the challenges and limitations of acquiring experimental data.

Prediction of aerodynamic characteristics of high-lift Common Research Model in ground effect

Abstract Reynolds Averaged Navier-Stokes (RANS) simulations are performed to investigate the aerodynamic characteristics of the NASA Common Research Model (CRM) in its high-lift (HL) configuration in close proximity to the ground. The RANS simulations are conducted at a moderate Reynolds number of $Re = 5.49 \times {10^6}$ and $M = 0.2$ with the use of the Spalart-Allmaras (SA) turbulence model. out of ground effect (OGE) simulation results are validated against available wind tunnel data before proceeding to in ground effect (IGE) simulations. The obtained computational results in the immediate vicinity of the ground with asymmetric aircraft attitudes demonstrate significant changes in the longitudinal and lateral-directional aerodynamic characteristics, which should be taken into account in flight dynamics analysis of aircraft during take-off and landing in crosswind conditions.

Trajectory reconstruction of a wingtip segment separated from an aircraft using CFD simulation

Reconstructing the trajectory of the disintegrated component in an aircraft using numerical methods is anticipated to be a valuable technology for air crash investigation. The motion of separated objects in the air is significantly influenced by aerodynamic loads, making it necessary to employ computational fluid dynamics to estimate the forces and moments acting on the objects. To address the limitations of current methods, a multi-zone dynamic mesh method was utilized and validated via a store separation case, demonstrating good consistency with wind tunnel data. Since the trajectory of the wingtip is highly dependent on the center of gravity and mass properties, a predictive-level finite element model was developed using 3D scanning and reverse engineering techniques. Trajectories of the wingtip for a Tu-154M under various initial conditions were reconstructed, revealing nonlinear variations over time. By comparing the predicted crash position with the actual one, it is possible to ascertain the aircraft's condition at the moment when the wingtip separated.

QES-Plume v1.0: a Lagrangian dispersion model

Abstract. Low-cost simulations providing accurate predictions of transport of airborne material in urban areas, vegetative canopies, and complex terrain are demanding because of the small-scale heterogeneity of the features influencing the mean flow and turbulence fields. Common models used to predict turbulent transport of passive scalars are based on the Lagrangian stochastic dispersion model. The Quick Environmental Simulation (QES) tool is a low-computational-cost framework developed to provide high-resolution wind and concentration fields in a variety of complex atmospheric-boundary-layer environments. Part of the framework, QES-Plume, is a Lagrangian dispersion code that uses a time-implicit integration scheme to solve the generalized Langevin equations which require mean flow and turbulence fields. Here, QES-Plume is driven by QES-Winds, a 3D fast-response model that computes mass-consistent wind fields around buildings, vegetation, and hills using empirical parameterizations, and QES-Turb, a local-mixing-length turbulence model. In this paper, the particle dispersion model is presented and validated against analytical solutions to examine QES-Plume’s performance under idealized conditions. In particular, QES-Plume is evaluated against a classical Gaussian plume model for an elevated continuous point-source release in uniform flow, the Lagrangian scaling of dispersion in isotropic turbulence, and a non-Gaussian plume model for an elevated continuous point-source release in a power-law boundary-layer flow. In these cases, QES-Plume yields a maximum relative error below 6 % when compared with analytical solutions. In addition, the model is tested against wind-tunnel data for a uniform array of cubical buildings. QES-Plume exhibits good agreement with the experiment with 99 % of matched zeros and 59 % of the predicted concentrations falling within a factor of 2 of the experimental concentrations. Furthermore, results also emphasize the importance of using high-quality turbulence models for particle dispersion in complex environments. Finally, QES-Plume demonstrates excellent computational performance.

Reynolds number effect correction of multi-fidelity aerodynamic distributions from wind tunnel and simulation data

Conventional wind tunnels cannot simulate actual flight Reynolds numbers because of testing condition constraints. The changes in aerodynamic characteristics caused by differences in the Reynolds number are especially sensitive on transonic supercritical airfoils and wings. Accordingly, this study proposes a correction method for the Reynolds number effect based on feature extraction of multi-fidelity aerodynamic distributions. Correcting wind tunnel test results at low Reynolds numbers with large amounts of numerical simulation data across various Reynolds numbers allows this method to achieve greater precision on airfoil pressure distribution predictions at high Reynolds numbers. The first step is to extract the primary features of the surface pressure distribution of the supercritical airfoil using the proper orthogonal decomposition technique. Next, a multi-fidelity neural network model is employed to relate the (low-fidelity) simulation data to the (high-fidelity) wind tunnel data acquired at low Reynolds numbers. Finally, the model is used to predict the airfoil pressure distributions at high Reynolds numbers, and the predictions are validated using wind tunnel test data collected from the RAE2822 airfoil. The results indicate that this approach can provide more accurate estimations than numerical simulations and single-fidelity models. Additionally, it can effectively reduce the impact of the Reynolds number difference on the transonic aerodynamic properties of supercritical airfoils.

Data Exploratory Analysis and Feature Selection of Low-Speed Wind Tunnel Data for Predicting Force and Moment of Aircraft

This paper discusses exploratory data analysis (EDA) and feature selection of aircraft test results in Indonesia's low-speed wind tunnels (ILST). First, we briefly explain input and output parameters and data processing to make readable and higher accurate data. Then, we used feature selection using embedded and random forest methods to find parameters that most affect the force coefficient of aircraft. The research activities carried out in this study are to review literature from either scientific journals, the internet, or books and interview with an engineer who tests aircraft models at ILST. Then create a program for processing data from test results, such as data extraction, data cleaning, exploratory data analysis, and feature selection with python. After applying the feature selection method, we found that all the methods show similar results and have succeeded in separating the powerful features from the weak ones with a significant score difference. We decide to use the Random Forest method. The three most strongest features in the coefficient of an aircraft model in the ILST test (CL, CD, CM25, CYAW, CROLL and CY) are the following: for CL are ALFA (0.984), T0 (0.008), P0 (0.004), on for CD is are ALFA (0.965), T0 (0.009), RE (0.007), in CM25 are ALFA (0.416), P0 (0.285), T0 (0.168), in CYAW are BETA (0.44), T0 (0.141), ALFA (0.141), in CROLL is BETA (0.79), ALFA (0.091), P0 (0.036), and in CY are BETA (0.842), ALFA (0.114) and T0 (0.014). The results of this paper can be used to help build a model for the coefficient of aircraft design using machine learning based on the data from the ILST test more effectively and efficiently.

Uncertainty Quantification and Simulation of Wind-Tunnel-Informed Stochastic Wind Loads

The simulation of stochastic wind loads is necessary for many applications in wind engineering. The proper-orthogonal-decomposition-(POD)-based spectral representation method is a popular approach used for this purpose, due to its computational efficiency. For general wind directions and building configurations, the data-informed POD-based stochastic model is an alternative that uses wind-tunnel-smoothed auto- and cross-spectral density as input, to calibrate the eigenvalues and eigenvectors of the target load process. Even though this method is straightforward and presents advantages, compared to using empirical target auto- and cross-spectral density, the limitations and errors associated with this model have not been investigated. To this end, an extensive experimental study on a rectangular building model considering multiple wind directions and configurations was conducted, to allow the quantification of uncertainty related to the use of short-duration wind tunnel records for calibration and validation of the data-informed POD-based stochastic model. The results demonstrate that the data-informed model can efficiently simulate stochastic wind loads with negligible model errors, while the errors associated with calibration to short-duration wind tunnel data can be important.

Wind hazard on earthquake damaged buildings

AbstractThis study proposes a holistic approach to multihazard performance‐based assessment of a tall steel building, partially damaged by earthquake, and then subjected to wind. The case study is a 16‐storey LD‐CBF building in Montreal, designed in accordance with the Canadian code and steel standard. Advanced numerical models are developed in OpenSees; hence, they account for material nonlinearity including low‐cycle fatigue to simulate brace fracture. Wind histories are generated from wind tunnel data. The sequence of analyses is: (i) design the LD‐CBF building to respond to code‐based earthquake (2475 years return period) and verify the LD‐CBF members to design wind load (1‐in‐500 years), as well as, the interstorey drift under the service wind (1‐in‐10 years); (ii) apply the 60 min. wind load history on earthquake damaged building; (iii) assess the building response in terms of interstorey drift and residual interstorey drift, and (iv) compare the results of the case study under (1) earthquake on intact building, (2) wind on intact building, and (3) wind on earthquake damaged building. The findings are significant and allow the realistic representation of the effects of multiple hazards on steel buildings. In summary, the consequent hazard on building safety has a detrimental effect.

Lift and Tip Vortices Generated by Tapered Backward-Swept and Forward-Swept Wings under Stationary Ground Proximity

An experimental investigation of the aerodynamics and near-field tip-vortex flow field behind tapered backward- and forward-swept wings with a stationary ground effect was conducted at Reynolds number (Re)=1.81×105. The results showed a large lift increase of 26.7% and 12.3% for the backward-swept wing (BSW) and forward-swept wing (FSW), respectively, with reduced ground clearance, along with a significant drag reduction of 45% and 30% for the BSW and FSW. For the BSW, a multiple-vortex system appeared in close ground proximity, consisting of a tip vortex, a corotating ground vortex, and a counterrotating secondary vortex. The ground vortex strengthens the tip vortex, whereas the secondary vortex negates its vorticity. For the FSW, the multiple-vortex system was not readily identifiable due to its unique geometry, which always keeps the inboard region of the wing at a close ground effect while leaving the tip region less affected by the ground effect. The root stall of the FSW also produced a continuously strengthening tip vortex with the increasing angle of attack. In contrast, the tip stall of the BSW led to a monotonically increasing vortex strength only up to the static-stall angle. Regardless of the wing model, the weak tip vortex also translates into a small lift-induced drag compared with the total drag. Finally, the lift force computed through the integration of the spanwise circulation distribution, inferred from the cross-flow measurements, at selected ground distances was also found to be in good agreement with the direct wind-tunnel force-balance data, with 101% and 98% consistency for BSW and FSW, respectively. The aerodynamics and tip-vortex measurements of both wing models outside the ground effect were also acquired to serve as a comparison.