Real Turbulence Research Articles

Convective heat transfer coefficient for realistic turbulence parameters using LES vs. RANS turbulence models in case of free-standing photovoltaic panel

The efficiency of photovoltaic (PV) and hybrid photovoltaic-thermal (PVT) solar panels partly depends on the heat transfer to the ambient air. The exact value of the convective heat transfer coefficient (HTC) is particularly important for the development of cooling techniques. The HTC values are usually determined from experimental data available for flat plates and similar geometries. Since the HTC depends on the geometrical details of the PV panel and the environment, the HTC values are usually estimated using computational fluid dynamics (CFD) based on the Reynolds-averaged Navier-Stokes equations (RANS). In this work, a free-standing PV panel is considered, and the main objective of the work is to compare the RANS results with the large eddy simulation (LES), which is expected to provide more reliable results compared to the available experimental data. The research includes the effects of inlet velocity, turbulence intensity and turbulence length scale. It was shown that the HTC depends on both turbulence intensity and turbulence length scale. The results show that RANS models significantly overestimate the influence of inlet turbulence on the HTC, by up to 70% at high inlet turbulence intensities. Meanwhile, the LES values are within 5 % of the experimental HTC values.

A theoretical study of a radiofrequency wave propagation through a realistic turbulent marine atmospheric boundary layer based on large eddy simulation

This study aims at modeling and investigating the impact of realistic turbulence inhomogeneity on radiowave propagation by utilizing large eddy simulations (LES). An up-to-date version of the X-LES method for generating realistic turbulent phase screens is first introduced. It combines atmospheric simulations with the classical Tatarski statistical modeling. This method naturally incorporates vertical turbulence inhomogeneity into phase screens at scales resolved by LES. It is then extended to sub-grid scales by weighting statistically generated phase variations with the vertical profile of the turbulent structure constant extracted from atmospheric data. This method is applied to replicate turbulence of a classical tropical marine atmospheric boundary layer. The impact of the generated medium on the propagation of a 10 GHz spherical wave emanating from a Gaussian aperture is analyzed through a statistical study of log-amplitude profiles performed for three different source altitudes. Results first show that contrary to a classical homogeneous turbulence modeling, log-amplitude profiles resulting from the propagation into inhomogeneous turbulence exhibit a statistical heterogeneity strongly dependent of source altitude. Furthermore, classical stochastic phase screen generation from a homogeneous Von-Kàrmàn Kolmogorov spectrum seems to give a statistically significant underestimation of the actual impact of turbulence compared to the X-LES method.

Onsite measurements of pedestrian-level wind and preliminary assessment of effects of turbulence characteristics on human body convective heat transfer

Wind is an important factor affecting outdoor thermal comfort in urban environment, but its turbulence characteristics at the pedestrian level and effects on convective heat transfer (hc) from a human body remain poorly understood. Previous studies were only conducted in wind tunnels with low turbulence intensity, small turbulence integral length scale, and fixed prevailing wind direction. To address this knowledge gap, this field study was conceived to monitor the pedestrian level wind in actual outdoor settings and to measure the hc of a thermal manikin at the same time. The results show that both longitudinal and lateral turbulence intensity significantly enhance whole body hc. It remains to be examined whether the small-scale wind direction variation can be included in the lateral turbulence intensity or vice versa. The integral length scale found at the two sites were larger than a typical manikin dimension, and the whole body hc peaked when these two scales were comparable. As the first major field study to quantify convection heat loss of a thermal manikin exposed to real-life urban boundary layer wind, it is demonstrated crucial to consider realistic turbulence characteristics in the field when evaluating hc over a human body for urban microclimate design.

Efficient Prediction of Turbulent Inflow and Leading-Edge Interaction Noise Using a Vortex Particle Method with Look-up Table Approach

This paper presents a new, efficient approach for predicting turbulent inflow, also known as leading-edge interaction noise. The method combines a low-fidelity Vortex Particle Method (VPM) with a look-up table approach. Its goal is to reconstruct realistic inflow turbulence and airfoil contours using stochastic control variables within a limited vortex window. To model far-field sound emission, Curle’s equation and a vortex sound database are employed. To increase confidence in the methodology, an analysis of inflow turbulence parameters and source characteristics was performed using systematic Large Eddy Simulations (LES). A generic NACA 0012 airfoil test case with different inflow turbulence grids was used for direct comparisons with semi-theoretical and semi-empirical predictions from the literature. The comparison is restricted to Amiet/Gershfeld predictions as the current model is only capable of dealing with homogeneous and isotropic turbulence. However, their usefulness is limited to narrower parameter ranges when compared to the more generally applicable new method. A satisfactory agreement of the results demonstrates the versatility of the proposed method.

Towards synthetic magnetic turbulence with coherent structures

Synthetic turbulence is a relevant tool to study complex astrophysical and space plasma environments inaccessible by direct simulation. However, conventional models lack intermittent coherent structures, which are essential in realistic turbulence. We present a novel method featuring coherent structures, conditional structure function scaling and fieldline curvature statistics comparable to magnetohydrodynamic turbulence. Enhanced transport of charged particles is investigated as well. This method presents significant progress towards physically faithful synthetic turbulence.

Lagrangian Stochastic Modeling of Stratified Atmospheric Boundary Layer

A single-column turbulence model for stratified atmospheric boundary layer (ABL), which solves the transport equations of turbulence probability density function (PDF) using a Lagrangian stochastic modeling (LSM) approach, is proposed in this study. This study adopts previously developed stochastic differential equations (SDEs) for particle velocity and temperature and extends the LSM to simulate inhomogeneous turbulence. The proposed LSM is tested for its ability to fully simulate statistics of inhomogeneous stratified turbulence. In the model, particles evolve by SDEs, and turbulence statistics are calculated by averaging the properties of particles. The model provides a full representation of turbulence PDF and simulates turbulent transport without any modeling assumption. The model performance is evaluated against large-eddy simulation (LES) results in the simulations of convective and stable ABL cases. For the convective ABL, LSM realistically simulates the entrainment process with the temperature and heat flux profiles that closely match with LES. The joint PDF simulated by LSM reproduces a curved and highly skewed shape, and some distinct features, like the asymmetric distribution of vertical velocity and the separation of the PDF in the entrainment zone, are simulated. LSM also reproduces the entrainment enhancement by wind shear in the simulation of sheared convective ABL. The LSM simulation of stable ABL predicts realistic turbulence intensity and mean field profiles, where Gaussian-like PDFs are simulated both in LSM and LES.

Large eddy simulation of aerodynamic wind pressure on a tall rectangular building by modified synthetic volume forcing method

To accurately predict wind pressures on a tall building by numerical Computational Fluid Dynamics (CFD) using the Large-Eddy Simulation (LES) turbulent model, it is essential to generate inflow with realistic turbulence characteristics. The Discretizing and Synthesizing Random Flow Generation (DSRFG) method, as one of the synthetic Fourier methods, has received significant attention in the Computational Wind Engineering (CWE) community because of its ability to strictly satisfy the continuity condition and generate turbulent wind with the desired power spectra. In traditional LES, the desired turbulent wind is normally generated and specified at the inlet. However, this treatment often leads to significant attenuation in turbulence energy in the high-frequency band of the fluctuating wind speed spectrum along the flow direction and unrealistic large-amplitude wind pressure fluctuations, resulting in unsatisfactory prediction performance. The Synthetic Volume Forcing (SVF) method effectively overcomes these limitations by introducing turbulence as volume force into the moment Navier-Stokes (N-S) equations. In this study, the DSRFG method is applied to generate a fluctuating wind field in combination with the SVF method to simulate dynamic wind pressures on a tall rectangular building through open-source software OpenFOAM. The turbulence intensity amplification factor (TIAF) is introduced in the SVF method to further improve its simulation accuracy. Comparison of results with wind tunnel test results verifies that the proposed TIAF-SVF numerical method developed in this study achieved sufficient accuracy in predicting wind pressures on tall buildings.

Intermittency as a Consequence of a Stationarity Constraint on the Energy Flux.

In his seminal work on turbulence, Kolmogorov made use of the stationary hypothesis to determine the power density spectrum of the velocity field in turbulent flows. However, to our knowledge, the constraints that stationary processes impose on the fluctuations of the energy flux have never been used in the context of turbulence. Here, we recall that the power density spectra of the fluctuations of the injected power, the dissipated power, and the energy flux have to converge to a common value at vanishing frequency. Hence, we show that the intermittent Gledzer-Ohkitani-Yamada (GOY) shell model fulfills these constraints. We argue that they can be related to intermittency. Indeed, we find that the constraint on the fluctuations of the energy flux implies a relation between the scaling exponents that characterize intermittency, which is verified by the GOY shell model and in agreement with the She-Leveque formula. It also fixes the intermittency parameter of the log-normal model at a realistic value. The relevance of these results for real turbulence is drawn in the concluding remarks.

The Statistical Mechanics of Ideal Magnetohydrodynamic Turbulence and a Solution of the Dynamo Problem

We review and extend the theory of ideal, homogeneous, incompressible, magnetohydrodynamic (MHD) turbulence. The theory contains a solution to the ‘dynamo problem’, i.e., the problem of determining how a planetary or stellar body produces a global dipole magnetic field. We extend the theory to the case of ideal MHD turbulence with a mean magnetic field that is aligned with a rotation axis. The existing theory is also extended by developing the thermodynamics of ideal MHD turbulence based on entropy. A mathematical model is created by Fourier transforming the MHD equations and dynamical variables, resulting in a dynamical system consisting of the independent Fourier coefficients of the velocity and magnetic fields. This dynamical system has a large but finite-dimensional phase space in which the phase flow is divergenceless in the ideal case. There may be several constants of the motion, in addition to energy, which depend on the presence, or lack thereof, of a mean magnetic field or system rotation or both imposed on the magnetofluid; this leads to five different cases of MHD turbulence that must be considered. The constants of the motion (ideal invariants)—the most important being energy and magnetic helicity—are used to construct canonical probability densities and partition functions that enable ensemble predictions to be made. These predictions are compared with time averages from numerical simulations to test whether or not the system is ergodic. In the cases most pertinent to planets and stars, nonergodicity is observed at the largest length-scales and occurs when the components of the dipole field become quasi-stationary and dipole energy is directly proportional to magnetic helicity. This nonergodicity is evident in the thermodynamics, while dipole alignment with a rotation axis may be seen as the result of dynamical symmetry breaking, i.e., ‘broken ergodicity’. The relevance of ideal theoretical results to real (forced, dissipative) MHD turbulence is shown through numerical simulation. Again, an important result is a statistical solution of the ‘dynamo problem’.

Impact of Momentum Perturbation on Convective Boundary Layer Turbulence

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

Large‐eddy simulation of plume dispersion in a turbulent boundary layer flow generated by a dynamically controlled recycling method

AbstractWhen conducting large‐eddy simulations (LESs) of plume dispersion in the atmosphere, crucial issue is to prescribe time‐dependent turbulent inflow data. Therefore, several techniques for driving LESs have been proposed. For example, in the original recycling (OR) method developed by Kataoka and Mizuno (Wind and Structures, 2002, 5, 379–392), a mean wind profile is prescribed at the inlet boundary, the only fluctuating components extracted at the downstream position are recycled to the inlet boundary. Although the basic turbulence characteristics are reproduced with a short development section, it is difficult to generate target turbulent fluctuations consistent with realistic atmospheric turbulence. In this study, we proposed a dynamically controlled recycling (DCR) method that is a simple extension of the OR procedure. In this method, the magnitude of turbulent fluctuations is dynamically controlled to match with the target turbulent boundary layer (TBL) flow using a turbulence enhancement coefficient based on the ratio of the target turbulence statistics to the computed ones. When compared to the recommended data of Engineering Science Data Unit (ESDU) 85020, the turbulence characteristics generated by our proposed method were quantitatively reproduced well. Furthermore, the spanwise and vertical plume spreads were also simulated well. It is concluded that the DCR method successfully simulates plume dispersion in neutral TBL flows.

A coherence-improved and mass-balanced inflow turbulence generation method for large eddy simulation

Realistic inflow turbulence is crucial in large eddy simulations for obtaining accurate results. In this paper, an improved inflow turbulence generation method is proposed, called the coherence-improved and mass-balanced random flow generation (CMRFG) method. First, a study of the effect of the inlet mass-balanced condition is presented. Subsequently, the proposed method is explicitly deduced to satisfy arbitrary spatial coherence functions and the mass-balanced condition, so the generated turbulent fields effectively preserve the original turbulence characteristics, eliminating the need for additional inlet mass flux corrections. Meanwhile, the novel method retains the advantages of the previous method, satisfying arbitrary turbulence intensities, temporal spectra, temporal correlations, and spatial correlation coefficients. Additionally, the proposed method also ensures compliance with the divergence-free condition and Taylor's frozen hypothesis, which are essential for accurate flow field development. Finally, large eddy simulations of both homogeneous isotropic and anisotropic turbulent fields demonstrate that the turbulent fields generated by CMRFG closely align with experimental results and exhibit no artificial pressure fluctuations within the computational domain.

To What Extent Is Aeroelasticity Impacting Multi-Megawatt Wind Turbine Upscaling? A Critical Assessment

Aeroelasticity is recognized as the key enabler that allowed for the massive upscaling of wind turbines in the last decade, leading to long, slender, and flexible blades that equip rotors with lower specific power and unprecedented energy conversion capabilities. In this study, a selection of case studies with increasing size, specifically the NREL 5 MW, the DTU 10 MW, and the IEA 15 MW Reference Wind Turbines (RWTs) is considered to explore to what extent aeroelastic effects impact the functioning of these rotors. The rotors are not only different in size, with the 15 MW having blades nearly double the length of its 5 MW predecessor, but also in technological level as they belong to different phases of wind turbine development. To evaluate how these machines interact with complex inflow conditions, equivalent boundary conditions have been considered for all simulations, including a realistic atmospheric boundary layer, atmospheric turbulence, and wind shear. To carry out the comparative study, a new aero-servo-elastic module called CALMA is introduced herein, by coupling the engineering software OpenFAST with the CFD software CONVERGE, which solves the wind field and provides inflow conditions for the calculation of loads. Results show how not only aeroelasticity increasingly affects the power performance of the new-generation rotors, but is also a key driver of structural design, for example allowing for an alleviation of 1P load variations due to a sheared and turbulent inflow, thus proving that the inclusion of aeroelasticity in the design process is a key enabler to current and future upscaling trends.

A priori test of Large-Eddy Simulation models for the Sub-Grid Scale turbulent stress tensor in perfect and transcritical compressible real gas Homogeneous Isotropic Turbulence

In this study, the focus lies on the modeling of the subgrid-scale stress tensor in the context of real gas flows. By conducting tests on perfect and dense gas configurations using six different models, the research findings highlight the superiority of gradient models over eddy-viscosity models in capturing the structural behavior of the stress tensor. However, the models’ performance experiences a significant decline when considering the intricate thermodynamics of real gases. To address this challenge, dynamic models that take into account the characteristics of the flow are also tested, resulting in some improvements in the outcomes. Despite these advancements, the achieved results still fall short of being entirely satisfactory. In particular, the models fail to accurately predict the occurrence of large values of the subgrid-scale stress tensor in the real gas flow. The complex thermodynamic nature of real gases therefore significantly influences the subgrid-scale stress tensor and the outcomes of this study underscore the urgent need for continued research to advance our understanding and modeling capabilities of subgrid-scale terms in real gas flows, paving the way for statistically accurate Large-Eddy Simulations of industrial real gas flows using moderately refined grids.

Active noise control with resonant flush-mounted piezoelectric cells in the presence of airflow: Wind tunnel experiments

Methods and technologies to control the noise coming from turbulent flows impinging on outlet guide vanes in turbofan engines are tremendously needed nowadays to comply with new legislation on acoustic environment pollution. The following paper relies on preliminary research proposing a new experimental design of active noise control system to be further integrated into a jet engine outer guide vane prototype, consisting of multiple flush-mounted piezoelectric cells. Here, three active cells are placed on the bottom wall of a wind tunnel with upstream acoustic excitation generating grazing incident waves for different airflow velocities. Using a downstream microphone as an error sensor, the active system succeeds in improving the transmission loss of the sample by 2.5 dB at the target frequency (670 Hz) corresponding to the main piezo acoustic mode with airflow velocities up to 20 m.s−1. These early experimental results confirm the ability of the concept to interact with the ambient acoustics without disturbing the airflow as in passive solutions using porous materials, for instance, leading the path to future experiments with realistic turbulence generating acoustic sources on the leading edge of the vane profile.

Optical adaptive power control based on atmospheric channel reciprocity for mitigating turbulence disturbances in free-space optics communication.

A continuous time-domain adaptive power model of transmitter optical and control algorithm based on atmospheric turbulence channel reciprocity are explored for mitigating the free-space optical communication (FSOC) receiver optical intensity scintillation and bit error rate (BER) deterioration. First, a transmitter optical adaptive power control (OAPC) system architecture using four wavelength optical signals based on atmospheric turbulence channel reciprocity is proposed, and electronically variable optical attenuator (EVOA) and erbium-doped fiber amplifier (EDFA) are employed as the main OAPC units for power adaptation. Moreover, a reciprocity evaluation model for gamma-gamma (G-G) continuous-time signals is generated using the autoregressive moving average (ARMA) stochastic process, which takes into account the delay time and system noise, and a reciprocity-based OPAC algorithm is proposed. Numerical simulations were also performed to analyze the signal reciprocity characteristics under different turbulence, noise, and sampling time mismatch at both ends, as well as the scintillation index (SI) performance under OAPC system operation. Simultaneously, the time-domain signals of continuous quadrature amplitude modulation -16 (QAM-16) and QAM-32 real states are fused with the gamma-gamma (G-G) reciprocal turbulence continuous signals to analyze the probability density function (PDF) and bit error ratio (BER) performance after OAPC correction. Finally, a 64 Gpbs QAM-16 OPAC communication experiment was successfully executed based on an atmospheric turbulence simulator. It is shown that the OAPC correction is carried out using reciprocity at millisecond sampling delay, the light intensity scintillation of the communication signal can be well suppressed, the signal-to-noise ratio (SNR) is greatly improved, the suppression is more obvious under strong turbulence, the overall BER reduction is greater than 2.8 orders of magnitude with the OAPC system, and this trend becomes more pronounced as the received power increases, even reach 6 orders of magnitude in some places. This work provides real time-domain continuous signal samples for real signal generation of communication signals in real turbulence environments, adaptive coding modulation using reciprocity, channel estimation, and optical wavefront adaptive suppression, which are the basis of advanced adaptive signal processing algorithms.

Four-channel orthogonally polarized interferometer for optical phase detection in turbulence

A four-channel orthogonally-polarized interferometer for optical phase detection in turbulence is proposed. It is theoretically and experimentally demonstrated that the interferometer can be employed to detect phase fluctuations of an optical wave through atmospheric turbulence. In this framework, two portions of the optical field are captured, implemented polarization modulation, and performed interference. The orthogonally polarized interferogram is sent through four channels and the phase differences across the two apertures are measured in a single shot. The phase fluctuation and structure-function evaluated from a series of phase differences measured in a laboratory turbulence tank and in real atmospheric turbulence show good agreement with the theoretical prediction for atmospheric turbulence. Our method provided an important complement to Differential wavefront lidar under long-range, weak-light conditions which may be applied in real-time remote atmospheric sensing, and phase-based object transient dynamic tracking.

Highly robust spatiotemporal wavefront prediction with a mixed graph neural network in adaptive optics

The time-delay problem, which is introduced by the response time of hardware for correction, is a critical and non-ignorable problem of adaptive optics (AO) systems. It will result in significant wavefront correction errors while turbulence changes severely or system responses slowly. Predictive AO is proposed to alleviate the time-delay problem for more accurate and stable corrections in the real time-varying atmosphere. However, the existing prediction approaches either lack the ability to extract non-linear temporal features, or overlook the authenticity of spatial features during prediction, leading to poor robustness in generalization. Here, we propose a mixed graph neural network (MGNN) for spatiotemporal wavefront prediction. The MGNN introduces the Zernike polynomial and takes its inherent covariance matrix as physical constraints. It takes advantage of conventional convolutional layers and graph convolutional layers for temporal feature catch and spatial feature analysis, respectively. In particular, the graph constraints from the covariance matrix and the weight learning of the transformation matrix promote the establishment of a realistic internal spatial pattern from limited data. Furthermore, its prediction accuracy and robustness to varying unknown turbulences, including the generalization from simulation to experiment, are all discussed and verified. In experimental verification, the MGNN trained with simulated data can achieve an approximate effect of that trained with real turbulence. By comparing it with two conventional methods, the demonstrated performance of the proposed method is superior to the conventional AO in terms of root mean square error (RMS). With the prediction of the MGNN, the mean and standard deviation of RMS in the conventional AO are reduced by 54.2% and 58.6% at most, respectively. The stable prediction performance makes it suitable for wavefront predictive correction in astronomical observation, laser communication, and microscopic imaging.

Local turbulence generation using conditional generative adversarial networks toward Reynolds-averaged Navier–Stokes modeling

Data-driven turbulence modeling has been extensively studied in recent years. To date, only high-fidelity data from the mean flow field have been used for Reynolds-averaged Navier–Stokes (RANS) modeling, while the instantaneous turbulence fields from direct numerical simulation and large eddy simulation simulations have not been utilized. In this paper, a new framework is proposed to augment machine learning RANS modeling with features extracted from instantaneous turbulence flow data. A conditional generative model is trained to model the probability distribution of the local instantaneous turbulence field given local mean flow features. Then, the generative model is transferred to machine learning RANS modeling. The present work is mainly focused on generating a local instantaneous turbulence field using conditional generative adversarial networks (CGANs). Several GANs are trained first on the turbulence data from channel flow and periodic hill flow to generate complete one-dimensional and two-dimensional turbulence fields. Then, a CGAN is trained on the periodic hill flow data to generate local turbulence fields. Statistical analysis is performed on the generated samples from the GAN models. The first and second moments, the two-point correlation, and the energy spectra conform well to those of real turbulence. Finally, the information learned by the CGAN is used for machine learning RANS modeling by multitask learning, and the feasibility of the framework proposed in this paper is initially verified.

Effect of upstream flow characteristics on the wake topology of a square-back truck

The influence of upstream flow characteristics on the bi-stable flow structure in the wake region of a simplified square-back heavy vehicle model at a Reynolds number of 2.7 × 104 was investigated by using the improved delayed detached eddy simulation method. The asymmetric wake structure of this model and its corresponding aerodynamic response were examined, aiming to identify the effect mechanism of three inlet profiles on the asymmetric wake structure of the named ground transportation system (GTS) model in simulations. The accuracy of the numerical method used in this study was validated by comparison with wake structure data, including the flow states, vortex core's location, and aerodynamic drag obtained from previous large eddy simulations and water channel experiments. The numerical results show that different turbulent inlet velocity profiles lead to different wake topologies. When the turbulent velocity profile with a turbulence intensity of 15% generated by TurbSim, a stochastic inflow turbulence tool for generating turbulent velocity inlet on an atmospheric boundary layer profile, is used, the expected bi-stable flow topology is still observed, but it is not shown in the case by means of the turbulence generator incorporated into ANSYS Fluent. Those turbulent inlet velocity profiles contribute to the increase in GTS model's aerodynamic drag forces. Compared to the uniform velocity profile, the TurbSim velocity profile can achieve a drag increase in 7.23%. In addition, this turbulent profile intensifies the flow fluctuations in the wake region and enhances the transient response frequency of the wake region. Thus, when assessing the vehicle aerodynamic performance in open air, especially under crosswinds, the real turbulence velocity profile, e.g., the profile generated by TurbSim in the current study, is recommended to be used for a more accurate prediction in numerical simulations.