Simulated Wind Fields Research Articles

Five-day track forecast skills of WRF model for the western North Pacific tropical cyclones

AbstractIn this study, the characteristics of simulated tropical cyclones (TCs) over the western North Pacific by a regional model (the WRF model) are verified. We utilize 12 km horizontal grid spacing, and simulations are integrated for 5 days from model initialization. One hundred and twenty-five forecasts are divided into five clusters through the k-means clustering method. The TCs in the cluster 1 and 2 (group 1), which includes many TCs moves northward in subtropical region, generally have larger track errors than for TCs in cluster 3 and 4 (group 2). The optimal steering vector is used to examine the difference in the track forecast skill between these two groups. The bias in the steering vector between the model and analysis data is found to be more substantial for group 1 TCs than group 2 TCs. The larger steering vector difference for group 1 TCs indicates that environmental fields tend to be poorly simulated in group 1 TC cases. Furthermore, the residual terms, including the storm-scale process, asymmetric convection distribution, or beta-related effect, are also larger for group 1 TCs than group 2 TCs. Therefore, it is probable that the large track forecast error for group 1 TCs is a result of unreasonable simulations of environmental wind fields and residual processes in the midlatitudes.

Engineering Comprehensive Model of Complex Wind Fields for Flight Simulation

A complex wind field refers to the typical atmospheric disturbance phenomena existing in nature that have a great influence on the flight of aircrafts. Aimed at the issues involving large volume of data, complex computations and a single model in the current wind field simulation approaches for flight environments, based on the essential principles of fluid mechanics, in this paper, wind field models for two kinds of wind shear such as micro-downburst and low-level jet plus three-dimensional atmospheric turbulence are established. The validity of the models is verified by comparing the simulation results from existing wind field models and the measured data. Based on the principle of vector superposition, three wind field models are combined in the ground coordinate system, and a comprehensive model of complex wind fields is established with spatial location as the input and wind velocity as the output. The model is applied to the simulated flight of a rocket projectile, and the change in the rocket projectile’s flight attitude and flight trajectory under different wind fields is analyzed. The results indicate that the comprehensive model established herein can reasonably and efficiently reflect the influence of various complex wind field environments on the flight process of aircrafts, and that the model is simple, extensible, and convenient to use.

Multi-scale numerical simulation of wind field over a coastal complex terrain during a typhoon landfall

Multi-scale numerical simulation of wind field over a coastal complex terrain during a typhoon landfall

Aerodynamic and hydrodynamic force simulation for the dynamics of double-pendulum articulated offshore tower

Articulated towers are one of the class of compliant offshore structures that freely oscillates with wind and waves, as they are designed to have low natural frequency than ocean waves. The present study deals with the dynamic response of a double-pendulum articulated tower under hydrodynamic and aerodynamic loads. The wind field is simulated by two approaches, namely, single-point and multiple-point. Nonlinearities such as instantaneous tower orientation, variable added mass, fluctuating buoyancy, and geometrical nonlinearities are duly considered in the analysis. Hamilton's principle is used to derive the nonlinear equations of motion (EOM). The EOM is solved in the time domain by using the Wilson-Θ method. The maximum, minimum, mean, and standard deviation and salient power spectral density functions (PSDF) of deck displacement, bending moment, and central hinge shear are drawn for high and moderate sea states. The outcome of the analyses shows that tower response under multiple-point wind-field simulation results in lower responses when compared to that of single-point simulation.

Development of a wind turbine gearbox virtual load sensor using multibody simulation and artificial neural networks

A current development trend in wind energy is characterized by the installation of wind turbines (WT) with increasing rated power output. Higher towers and larger rotor diameters increase rated power leading to an intensification of the load situation on the drive train and the main gearbox. However, current main gearbox condition monitoring systems (CMS) do not record the 6‑degree of freedom (6-DOF) input loads to the transmission as it is too expensive. Therefore, this investigation aims to present an approach to develop and validate a low-cost virtual sensor for measuring the input loads of a WT main gearbox. A prototype of the virtual sensor system was developed in a virtual environment using a multi-body simulation (MBS) model of a WT drivetrain and artificial neural network (ANN) models. Simulated wind fields according to IEC 61400‑1 covering a variety of wind speeds were generated and applied to a MBS model of a Vestas V52 wind turbine. The turbine contains a high-speed drivetrain with 4‑points bearing suspension, a common drivetrain configuration. The simulation was used to generate time-series data of the target and input parameters for the virtual sensor algorithm, an ANN model. After the ANN was trained using the time-series data collected from the MBS, the developed virtual sensor algorithm was tested by comparing the estimated 6‑DOF transmission input loads from the ANN to the simulated 6‑DOF transmission input loads from the MBS. The results show high potential for virtual sensing 6‑DOF wind turbine transmission input loads using the presented method.

Numerical simulation of wind field and sand flux in crescentic sand dunes

Sand flux is the key factor to determine the migration of sand dunes and the erosion to the surrounding environment. There are crescent-shaped sand dunes of various scales in the desert, and there are significant differences in spatial wind field and sand flux among them. However, due to the difficulty of monitoring, it is difficult to continuously observe the spatial wind field and sand flux around the larger crescentic dunes. On the basis of the Reynolds-Average Navier–Stokes (RA-NS) equation and the stress and sand flux model, the distribution of wind field and sand flux of a circular dune with a height of 4.2 m and a length of about 100 m during the four evolutionary periods of the evolution into a crescentic dune was simulated in this study. By comparing with the measured results, we verified that the closer to the leeward side, the more the simulated values of the velocity in wind field and sand flux were in line with the measured results. In order to further analyze the influence of the height of dune and other relevant parameters on sand flux, we simulated the influence on wind field and sand flux by changing the air viscosity and wind velocity of upper boundary. We found that the air viscosity mainly affected the amount of deposited sand on the leeward side of sand dune, while the increase of wind velocity would undoubtedly increase the sand flux of the whole sand dune. In addition, the simulation results also showed that the influence of changes in height of dune on the turbulent intensity of leeward side was very significant, and the turbulent intensity increased with the height of dune. The height changes of tall dunes gradually affected the transport of sand caused by wind flow behind the leeward side because that the rotation of the wind flow would form new vortexes at the large pores behind the leeward side, which would increase the turbulent energy in space and thus would increase the distance of migration of the lifting sand. While the low sand dunes could not form extra small vortexes at the bottom of the leeward side, so the wind velocity was small and the eddy currents behind the leeward side were more stable. The simulation results indicated that wind velocity was not the only reason for increasing the amount of sand flux, and the fluctuation of wind flow caused by turbulence could also stimulate the movement of sand particles on the ground.

Toward understanding waked flow fields behind a wind turbine using proper orthogonal decomposition

This study proposes the use of an approach based on proper orthogonal decomposition (POD) to explore reduced-order wake turbulence fields. Waked turbulence fields are first extracted using large eddy simulation (LES) downwind of a wind turbine in a single plane orthogonal to the streamwise flow field. Based on this extracted turbulence field, statistical summaries in the form of covariance matrices and cross power spectral density (CPSD) matrices are estimated. Using proper orthogonal decomposition, important “modes” organized by eigenvalues (dominant energy contributions) are evaluated. Based on a subset of these sorted modes, reduced-order turbulence fields can be generated and these are analyzed and compared directly with the original LES-based target wake turbulence field. Statistical descriptions of the turbulence and their effect on wind turbine loads are investigated. To serve as reference, the free-stream turbulence field upwind of the selected wind turbine is also captured using LES. The same decomposition and simulation procedures are performed on the free-stream field. Compared to POD eigenmodes and eigenvalues of the free-stream field, those for the waked wind fields show distinct patterns that describe a systematic increase in turbulence energy around the top of the rotor. CPSD-based POD (spectral proper transformation) is found to be more efficient in capturing dynamic characteristics and spatial patterns in the waked wind fields using a small number of modes. Reduced-order simulation of waked wind fields using varying numbers of POD modes suggests that the top 10% of these most dominant modes—a greater proportion than what is needed for the free-stream field—is required to yield turbine loads comparable to those based directly on the original LES wind fields.

A height-resolving tropical cyclone boundary layer model with vertical advection process

The height-resolving model is thought to be an optimal scheme for modeling the tropical cyclone (TC) wind fields in the boundary layer because it explicitly depicts the wind structures in that layer as TC evolves over time. However, the vertical advection process which exists in TCs has not been well considered in previously proposed parametric TC models. Neglecting this process may cause deviations of the simulated wind field structure in the boundary layer. Herein, a height-resolving boundary layer wind field model incorporating both the vertical advection and vertical diffusion processes is proposed and a semi-analytical solution to the governing equations is developed. The adequacy of this model is evaluated by comparing with the Weather Research and Forecasting model simulations, the Hurricane Research Division’s H*Wind snapshots, GPS dropsonde datasets and ground measurements of several TC events. Results show that the proposed model with vertical advection can reasonably produce the wind fields of TCs, and its advantage lies in the production of a more realistic three-dimensional wind structure in the boundary layer.

Large Roll Vortices Exhibited by Post-Tropical Cyclone Sandy during Landfall

Roll vortices are frequent features of a hurricane’s boundary layer, with kilometer or sub-kilometer horizontal scale. In this study, we found that large roll vortices with O (10 km) horizontal wavelength occurred over land in Post-Tropical Cyclone Sandy (2012) during landfall on New Jersey. Various characteristics of roll vortices were corroborated by analyses of Doppler radar observations, a 500 m resolution Weather Research and Forecasting (WRF) simulation, and an idealized roll vortex model. The roll vortices were always linear-shaped, and their wavelengths of 5–14 km were generally larger than any previously published for a tropical cyclone over land. Based on surface wind observations and simulated WRF surface wind fields, we found that roll vortices significantly increased the probability of hazardous winds and likely caused the observed patchiness of treefall during Sandy’s landfall.

A Novel Canopy Drag Coefficient Model for Analyzing Urban Wind Environments Based on the Large Eddy Simulation

It is very challenging to capture the drag effects for the computational fluid dynamics numerical simulations of the urban canopy wind environment. This study proposed a novel canopy drag coefficient model for accurate analysis of the urban wind environment based on a large eddy simulation, where the drag coefficients varied with quantitatively identified canopy parameters along with the height. Four computational parameters, namely the average kinetic energy, turbulent kinetic energy, sub-grid scale turbulent kinetic energy, and sub-grid scale dissipation, were incorporated into the conventional drag coefficient. The Meixi Lake International Community in Changsha, China, was considered as a case study. The inlet boundary conditions were provided by the Weather Research and Forecasting model, and the proposed drag coefficient model was utilized to simulate the wind field characteristics. The results showed that the drag coefficient was relatively large near the ground, and it decreased with the increase of height overall. The decay rate of the drag coefficient below 0.4 times the building was significantly higher than the other areas. Finally, compared with the field measurement data, the proposed model had good accuracy of the simulated wind field compared to previous approaches, thus offering a reliable model for analyzing the urban wind environment.

Large eddy simulation of hurricane boundary layer turbulence and its application for power transmission system

Recent extreme hurricanes caused a huge loss in damages to critical civil infrastructure. To estimate hurricane wind loading on structures, spectral methods are widely used to generate neutral atmosphere boundary layer winds, which however are limited to describe extreme wind fields that are non-stationary and more turbulent. To overcome this limitation, a high-fidelity high-resolution computational model is developed to simulate hurricane wind field with detailed physics. A large eddy simulation (LES) solver is developed using a sub-grid-scale model based on open source program OpenFOAM. The simulated wind field is validated through comparison with observations. The generated wind field is applied to analyze structural response of a power transmission system. The proposed hurricane boundary layer (HBL) model and a neutral atmosphere boundary layer (ABL) model are compared in tropical storm and category-3 hurricane scenarios. Compared with the HBL model, the ABL model doesn’t consider the mesoscale terms and overestimates the crosswind velocity and the turbulent kinetic energy (TKE) near the ground. As a result, the ABL model overestimates the dynamic responses of the wires and towers. The developed HBL model captures the main characteristics of hurricane wind and is applicable for modeling civil infrastructure exposed to hurricanes at a large scale.

Assessment of wind datasets on the tropical cyclones’ event (case study: Gonu tropical cyclone)

Even though the occurrence rate of tropical cyclones (TCs) is almost steady as reported in earlier studies, however, the intensity of TCs has shown a significant increase due to global warming. Gonu (2007) and Phet (2010) are examples of TCs, which affected the southern coasts of Iran. The first step in evaluating the effects of TC is the accuracy as well as the correctness of the wind field. For this purpose, the WRF and parametric models have been implemented for the wind field simulation, in the Makran coasts during the Gonu TC. QuikSCAT satellite data and coastal synoptic stations data have been used to evaluate the wind field results. The results indicated that the WRF model can successfully forecast the cyclone’s path and its outputs can be employed to forecast such weather hazards. Comparing the wind field results with satellite data, highlights the accuracy of the WRF model in the coastal areas. Modeling the wind field asymmetry due to the cyclone confinement and more realistic wind distribution, distinguishes the results of WRF model from other studied counterparts. In addition, a comparison of the wind field results with the synoptic data indicates that the WRF model results meet very good accuracy. Furthermore, the study of cyclone damage potential (CDP) index in the Gulf of Oman northern coasts shows that the WRF outcomes have a very high accuracy. This study highlights the capability of the ARW model in simulating the wind field, especially on the southern and southeastern coasts of Iran, which are affected by TCs.

Parameterization of wind evolution using lidar

Abstract. Wind evolution, i.e., the evolution of turbulence structures over time, has become an increasingly interesting topic in recent years, mainly due to the development of lidar-assisted wind turbine control, which requires accurate prediction of wind evolution to avoid unnecessary or even harmful control actions. Moreover, 4D stochastic wind field simulations can be made possible by integrating wind evolution into standard 3D simulations to provide a more realistic simulation environment for this control concept. Motivated by these factors, this research aims to investigate the potential of Gaussian process regression in the parameterization of wind evolution. Wind evolution is commonly quantified using magnitude-squared coherence of wind speed and is estimated with lidar data measured by two nacelle-mounted lidars in this research. A two-parameter wind evolution model modified from a previous study is used to model the estimated coherence. A statistical analysis is done for the wind evolution model parameters determined from the estimated coherence to provide some insights into the characteristics of wind evolution. Gaussian process regression models are trained with the wind evolution model parameters and different combinations of wind-field-related variables acquired from the lidars and a meteorological mast. The automatic relevance determination squared exponential kernel function is applied to select suitable variables for the models. The performance of the Gaussian process regression models is analyzed with respect to different variable combinations, and the selected variables are discussed to shed light on the correlation between wind evolution and these variables.

Combining application of wavelet analysis and genetic algorithm in wind tunnel simulation of unidirectional natural wind field near a sand ground surface.

This study proposes a method for the approximate simulation of field gust in an atmospheric boundary layer wind tunnel driven by an axial fan. Wavelet analysis and genetic algorithm have been adopted to convert actual field gust data into a series of simplified and smooth control signals. One frequency converter is used to receive the signals via a programmable logic controller and change the fan speed correspondingly. Results show that the low-frequency energetic part of field gust on top of a saltation layer has been almost reproduced in the wind tunnel with energy fluctuations ±3.26% from the mean compared with the field data in terms of energy. The appropriate filter frequency for field gust velocity history is 1/32Hz. A unidirectional natural wind field near a sand bed surface can be approximately simulated in the tunnel by adjusting carefully the roughness element arrangement. The time-averaged velocity profile of the simulated wind, which satisfies the logarithmic law, is nearly equivalent to the steady flow with the same average velocity.

Dynamic simulation of wind field in three-dimensional display space considering particle swarm algorithm fuzzy logic

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.

Numerical Simulation of Characteristics of Wind Field at Bridge Sites in Flat and Gorge Terrains under the Thunderstorm Downburst

To investigate the effects of thunderstorm downburst on the characteristics of wind field at bridge sites in flat and gorge terrains, firstly, numerical simulation of wind fields in the flat terrain under the thunderstorm downburst was conducted through the SST k‐ω turbulence model, combined with the impinging jet technology. After verification of the reliability of the numerical model, settings, and methods, the characteristics of wind field over a long‐span bridge site in a gorge terrain under the thunderstorm downburst were investigated and the distributions of wind speed and wind attack angle in the flat and gorge terrains were compared. The results show that, under the effects of the thunderstorm downburst, the wind speeds are relatively maximum at the midspan point of the girder in the flat terrain. Besides, the farther away from the midspan point, the smaller the wind speeds, which is opposite to the case in the gorge terrain. The wind speeds at each typical monitoring point are basically the same in the two terrains, before the thunderstorm downburst hits the bridge girder. Later the wind speeds at each point in the gorge terrain are much higher than those in the flat terrain. Most wind attack angles are negative at the monitoring points in the flat terrain, but the farther away they are from the midspan point, the greater the wind attack angles will be. However, the wind attack angles at the monitoring points in the gorge terrain are generally larger than those in the flat terrain, and they gradually turn to be positive farther away from the midspan point. In the flat terrain, both wind speeds and wind attack angles (or their absolute values) at the girder are large within about t = 75∼130 s, indicating that the thunderstorm downburst may exert significant effects on the bridge. However, in the gorge terrain, due to the large wind speeds and wind attack angles (or their absolute values) at the girder after t = 75 s, full attention needs to be paid to the effects of the thunderstorm downburst during this period.

Design and validation of an adaptive low-power detection algorithm for three-cup anemometer

An adaptive low-power detection algorithm for a cup anemometer is designed. The model of a commercial cup anemometer is applied in the simulation of constant wind fields. When the rotation of the cup rotor is stabilized in the wind field, its speed will fluctuate within certain range. It is found that the distribution of rotational speed approximately conforms to the normal distribution model, and parameters of the model under different wind speeds are obtained. Based on the distribution model, an algorithm for signal processing is designed for the cup anemometer, of which the structure for signal processing is designed to adapt to the algorithm. Experiments show that the algorithm is relatively adaptive so that it can sustain the performance of the anemometer. The anemometer achieves low power consumption, which is less 4.2mW. And the mean velocity error is less than 0.25 m/s among the measured velocity range from 0.9 m/s to 10 m/s.

Fast Hilbert–Wavelet Simulation of Nonstationary Wind Field Using Noniterative Simultaneous Matrix Diagonalization

AbstractThe frequency content and spatial correlation of nonstationary wind fields during extreme events typically present time-variant characteristics. Several effective schemes [e.g., using evolu...

Air quality assessment and health site guidelines for city squares based on RANS method

The concentration of pollutants and pathogens in the air directly affects human health. When the pollution source remains unchanged, effective ventilation determines air quality. It is therefore critically needed to establish a quantitative determination index for effective ventilation, which can be used for real-time evaluation of air quality in specific areas, so as to guide residents to choose healthy outdoor activity places. In this study, Reynolds average Navier-Stokes (RANS) method was used to establish urban air pollution simulation system by computational fluid dynamics (CFD) technology. The correlations among wind speed, pollutant concentration, and pollutant diffusion efficiency were analyzed. With real-time meteorological data, wind field simulation and air quality evaluation were carried out for different periods of urban square space. The results showed that the critical wind speed value at pedestrian height (1.5 m) for the effective diffusion of pollutants was 1.0 m·s-1, which could be used as an air quality evaluation standard. With reference to this judgment index and the real-time weather system link, the pedestrian height wind speed distribution could be obtained through simulation. Therefore, the spatial variation of air quality could be visually displayed in real time, which help realize fair, efficient and reasonable use of urban space resources. This work could provide guidelines for choosing healthy outdoor venues, and provide technologies and means for public disease prevention and health promotion.

Non-intrusive reduced order model of urban airflow with dynamic boundary conditions

To address the problem that urban wind field simulations are limited by high computational requirements, a supervised machine learning framework for the non-intrusive model order reduction of urban airflow is proposed to provide fast predictions with dynamic boundary conditions. An integrated atmospheric modeling system is established by coupling the Parallelized LES Model (PALM) with the Urban Canopy Model (UCM) which embedded in the Weather Research and Forecasting (WRF) model to simulate the high-resolution urban wind field. Within this machine learning framework, encoders and decoders are trained to compress and reproduce the full-order airflow data. The eXtreme Gradient Boost regression models (XGBoost) are trained to map the boundary conditions to the latent vectors in the encoders and decoders. Thus, high resolution urban airflow can be predicted rapidly by the XGBoost-decoder models with the input of boundary conditions. By comparing four types of encoding-decoding models (i.e., the proper orthogonal decomposition models, autoencoders with linear/nonlinear fully connected neural networks and autoencoders with Convolutional Neural Network (AE-CNN)), we find that the AE-CNN model with advantages of portable model size and convenient updating procedure is capable for high resolution simulations of urban airflow with dynamic boundary conditions at a low computational cost.