Simulated Wind Fields Research Articles

Drone Photogrammetry-based Wind Field Simulation for Climate Adaptation in Urban Environments

Drone Photogrammetry-based Wind Field Simulation for Climate Adaptation in Urban Environments

Characterizing surface pressure and wind fields of typhoons approaching Hong Kong

In this paper, 17 severe typhoons that have affected Hong Kong are simulated using an advanced numerical atmospheric simulation system - Weather Research and Forecasting model (WRF). The simulated surface pressure and wind fields of these typhoons are validated against a wide range of field observations. Then azimuth-dependent models for the radius of maximum winds and the Holland parameter are established statistically at the surface level. It is observed that the shape parameter of the Holland pressure model is smaller at the surface than that at the gradient level. And the Holland wind field model cannot well reproduce the simulated radial wind profiles due to the complexities of nonuniform surface conditions and typhoon dynamics. It is found that the modified Rankine model provides satisfactory estimates of typhoon wind speeds in Hong Kong. Additionally, wind field asymmetries of typhoons approaching Hong Kong are highly correlated with the typhoon track velocity, vertical wind shear and the angle between them. The proposed statistical models and identified characteristics of wind field asymmetries of typhoons will provide useful information for rapidly assessing typhoon wind hazards.

Deep learning methods for modeling infrasound transmission loss in the middle atmosphere

Accurate modeling of infrasound transmission losses (TLs) is essential to assess the performance of the global International Monitoring System (IMS) infrasound network. Among existing propagation modeling tools, parabolic equation method (PE) enables TLs to be finely modeled, but its computational cost does not allow exploration of a large parameter space for operational monitoring applications. To reduce computation times, Brissaud et al. (2022) explored the potential of convolutional neural networks (CNNs) trained on a large set of regionally simulated wavefields (>1000 km from the source) to predict TLs with negligible computation times compared to PE simulations. However, this new method shows difficulties in upwind conditions, especially at low frequencies, and causal issues with winds at large distances from the source affecting ground TLs close to the source. In this study, we have developed an optimized CNN network designed to minimize prediction errors while predicting TLs from globally simulated combined temperature and wind fields spanning over propagation ranges of 4000 km. Our approach enhances the previously proposed one by implementing key optimizations that improve the overall architecture performances. The implemented model predicts TLs with an average error of 20 dB in the whole frequency band (0.1-4 Hz) and explored realistic atmospheric scenarios.

Evaluating and comparison of WRF-chem model configurations for wind field impact on the April 2022 dust episode in western Iran

Accurate estimation of wind direction and speed is essential for enhancing the simulation and prediction of dust storms. Being highly susceptible to dust storms, Western Iran necessitates a detailed evaluation of dust concentration and wind fields. This study employs the WRF-Chem model to simulate these parameters over the period from April 7 to 26, 2022. Four different model configurations were tested, involving the Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ) boundary layer schemes, as well as the Lin and WRF Single-Moment 6-Class (WSM6) microphysics schemes. The results indicate that during the selected period, different synoptic systems led to the release of dust from Iraq and Saudi Arabia and its transport to western Iran. The mid-level southerly and southwesterly wind directions have a significant impact on dust transport to the northwestern regions of Iran by high and complex mountainous terrain. The horizontal and vertical distribution of simulated dust demonstrates good agreement with TERRA satellite imagery, MERRA-2 dust surface concentration, and CALIPSO, respectively. The daily dust concentration of the WRF-Chem model has a correlation of −0.32 to −0.96 with visibility and 0.68 to 0.86 with MERRA-2 data in Western Iran. The simulated dust concentration relation with visibility and AERONET AOD (Aerosol Optical Depth at 500 nm) was calculated at −0.78 and 0.29, respectively in Zanjan station. The horizontal and vertical distribution, temporal series, and statistical indices of the wind field show that the WRF-Chem model performs well in the Iran West boundary, especially in the west and northwest, where the 10-m wind speed increased to 14 m s−1. The boundary layer scheme in the WRF-Chem model has a more significant impact than the microphysics scheme in simulated 10-m wind speed and dust concentration. The final result shows that the combination of the YSU boundary layer and WSM6 microphysics schemes performs very well in simulating wind fields and dust in western Iran under various weather conditions.

Application of convolutional neural network for efficient turbulence modeling in urban wind field simulation

Accurate flow field estimation is crucial for the improvement of outdoor environmental quality, but computational fluid dynamics (CFD) based on the widely used Reynolds-averaged Navier–Stokes method has limitations in this regard. This study developed a turbulence modeling framework based on a convolutional neural network (CNN) to model turbulence in urban wind fields. The CNN model was trained by learning the Reynolds stress patterns and spatial correlations with the use of high-fidelity datasets. Next, the model was integrated into the CFD solver to generate accurate and continuous flow fields. The generalization capability of the proposed framework was initially demonstrated on the simplified benchmark configurations. The validated framework was then applied to case studies of urban wind environments to further assess its performance, and it was shown to be capable of delivering accurate predictions of the velocity field around an isolated building. For more complex geometries, the proposed framework performed well in regions where the flow properties were covered by the training dataset. Moreover, the present framework provided a continuous and smooth velocity field distribution in highly complicated applications, underscoring the robustness of the proposed turbulence modeling framework.

Research on the Collaborative Regeneration of Cohousing Under Spatial Densification Mode

Urban renewal is a necessary process for the transformation from incremental space to stock space, and old communities, as an important part of the urban space system, play a non-negligible role in the reconstruction of community spatial order. From the perspective of community remodeling, From the perspective of community remodeling, this paper summarizes the latest research progress through the analysis tool CiteSpace, explores and researches the design of old residential areas in Hangzhou based on the urban air index oriented residential renewal design based on the planning concepts of "co-living community", "urban spatial morphology" and "community microclimate system". On the basis of combining 3D wind field simulation and fluid mechanics software calculation, this paper explores the collaborative regeneration path of old residential areas under spatial densification mode, this paper studies how to combine scientific planning with resident sharing in a new mode, and on this basis, through the self-regulation function of the environment, let the residential area spontaneously form a complete shared living system, and carry out detailed exploration in the protection and reconstruction of the living environment of the old community, and how to promote the spiritual development of modern neighborhoods through transformation. In order to improve the quality of life of urban residents in Hangzhou, the renewal and regeneration design of old residential areas and the transformation and upgrading of future communities have brought new thinking.

Simulation of Urban Carbon Sequestration Service Flows and the Sustainability of Service Supply and Demand

Simulating ecosystem carbon sequestration service (ECSS) flows is crucial for optimizing the carbon cycle in ecosystems and achieving sustainable balance between the supply and demand of the ECSS. This study integrates least-cost path analysis with Kriging interpolation to simulate the dominant wind direction and corrects the interpolated wind speeds to account for terrain and surface conditions. Carbon emissions are spatially distributed using points of interest and road network data. Ultimately, by traversing the carbon emission rate grids along wind directions, the ECSS flows are simulated. The results reveal that the study area has a small carbon sink area but a high total carbon emission, leading to a situation where the supply of ECSS is insufficient to meet demand. The ECSS flows, based on the simulated wind field, demonstrate high spatial resolution and highlight the service flow corridors with distinct spatial heterogeneity. The study area has a significant carbon surplus, requiring a forest area ten times larger than the study area itself to fully sequester this carbon. These findings provide valuable insights for urban sustainable development and carbon emission reduction strategies.

Design and Development of a Side Spray Device for UAVs to Improve Spray Coverage in Obstacle Neighborhoods

Electric multirotor plant protection unmanned aerial vehicles (UAVs) are widely used in China for efficient and precise plant protection at low altitude for low volumes. Unstructured farmland in China has various types of obstacles, and UAVs usually use a detour path to avoid obstacles due to flight altitude limitations. However, existing UAV spray systems do not spray when in obstacle neighborhoods during obstacle avoidance, resulting in insufficient droplet coverage and reduced plant protection quality in the area. To improve the droplet coverage in obstacle neighborhoods, this article carries out a study of side spray technology with an electric quadrotor UAV, and proposes the design and development of a side spray device. The relationship between the obstacle avoidance path of the UAV and the spray pattern of the side spray device and their effect on droplet coverage in obstacle neighborhoods was explored. An accurate measurement method of the relative position between the UAV and obstacles was proposed. Spray angle calculations and nozzle selection for the side spray device were carried out in conjunction with the relative position. A rotor wind field simulation model was designed based on the lattice Boltzmann method (LBM), and the spatial layout of the side spray device on the UAV was designed based on the simulation results. To explore suitable spray patterns for the side spray device, comparative experiments of droplet coverage in obstacle neighborhoods were carried out under different environments, spray patterns, and flight parameter combinations. The relationship between the flight parameter combinations and the distribution uniformity of droplets and the effective swath width of the side spray device was explored. The experimental results were analyzed by an analysis of variance (ANOVA) and a relationship model was obtained. The results showed that the side spray device can effectively improve droplet coverage in obstacle neighborhoods compared to a device without side spray using the same flight parameter combinations. The effective swath width in obstacle neighborhoods can be increased by a minimum of 6.35%, maximum of 35.32%, and average of 15.25% using the side spray device. The error between the predicted values of the relational model and the field experiment results was less than 15%. The results verify the effectiveness and rationality of the method proposed in this article. This study can provide technical and theoretical references for improving the plant protection quality of UAVs in obstacle environments.

Reproducing vortex-induced vibrations of rooftop twin-mast by multi-scale coupled simulation of urban wind fields

The Shenzhen Electronics Group (SEG) Plaza in Shenzhen, China, experienced visible vibrations attributed to significant vortex-induced vibrations of the large spacing twin-mast atop the building. The vibration event occurred under complex urban wind environments. In order to reproduce wind fields around SEG Plaza, a multiscale simulation was carried out by integrating the Weather Research and Forecasting (WRF) and Computational Fluid Dynamics (CFD) models. The aerodynamic characteristics and wake modes of twin-mast are investigated by a downscale CFD simulation in detail. Finally, vortex-induced vibration (VIV) of twin-mast was analyzed considering fluid-structure interaction. This work reveals that wind conditions during the SEG Plaza vibration incident were appropriate for the VIV occurrence of twin-mast, and the results of VIV simulation agree well with the field monitoring results by computer vision identification. This study effectively reproduces the full pictures of VIVs of the rooftop twin-mast during this rare event, offering a critical view for the analysis of this event.

Enhancing wind field resolution in complex terrain through a knowledge-driven machine learning approach

Wind energy, an essential component in the fight against climate change, relies heavily on precise, detailed wind field simulations to optimize wind farms, particularly in complex terrain with intricate wind patterns. However, conventional high-resolution simulations come with a hefty computational cost, limiting their applicability in real-time decision-making. This research addresses this challenge by proposing a machine learning-driven, computationally efficient approach utilizing a modified Generative Adversarial Network. The contribution of this work is threefold. Firstly, we provide access to a unique high-resolution dataset of wind fields in complex terrain. Secondly, we introduce a knowledge-based modification to the loss function, ensuring that the algorithm captures crucial characteristics of the flow within complex terrains. Finally, we demonstrate the potential of our approach to enhance wind flow resolution in real-life wind farms. Through this, our method delivers comparable accuracy to high-resolution simulations while substantially reducing computational demands. This advancement greatly enhances the accessibility and efficiency of high-resolution wind field simulations, facilitating real-time optimization of wind farms. Moreover, we illustrate that by designing an appropriate loss function informed by domain knowledge, we can mitigate the need for adversarial training.

Fire behavior simulation of Xintian forest fire in 2022 using WRF-fire model

IntroductionThe behavior of forest fire is a complex phenomenon, and accurate simulation of forest fire is conducive to emergency response management after ignition. In order to further understand the characteristics of forest fire spread and the applicability of WRF-Fire in China, which is a coupled fire-atmospheric wildfire model, this study simulated a high-intensity forest fire event that occurred on October 17, 2022 in Xintian County, southern Hunan Province.MethodsBased on the fire-atmosphere coupled WRF-Fire model, we used high-resolution geographic information, meteorological observation and fuel classification data to analyze the forest fire behavior. At the same time, the simulation results are compared with the fire burned area observed by satellite remote sensing forest fire monitoring data.ResultsThe study found that, the simulated wind speed, direction and temperature trends are similar to the observation results, but the simulated wind speed is overestimated, the dominant wind direction is N, and the temperature is slightly underestimated. The simulated wind field is close to the actual wind field, and the simulation results can show the spatial and temporal variation characteristics of the local wind field under complex terrain while obtaining the high-resolution wind field. The simulated fire burned area is generally overestimated, spreading to the north and southwest compared with the observed fires, but it can also capture the overall shape and spread trend of the fire well.DiscussionThe results show that the model can accurately reproduce the real spread of fire, and it is more helpful to forest fire management.

Numerical simulations of downburst wind fields: A comparative analysis of stationary and moving storms using the impinging jet model

Numerical simulations of downburst wind fields: A comparative analysis of stationary and moving storms using the impinging jet model

Simulation of multivariate ergodic stochastic processes using adaptive spectral sampling and non-uniform fast Fourier transform

The simulation of multivariate ergodic stochastic processes is critical for structural dynamic analysis and reliability evaluation. Although the traditional spectral representation method (SRM) has a wide application in many areas, it is highly inefficient in simulating stochastic processes with many simulation points or long durations due to the significant computational cost associated with matrix factorizations concerning frequency. To address the encountered challenge, this paper presents an efficient approach for simulating ergodic stochastic processes with limited frequencies. Central to this approach is a fusion of the adaptive spectral sampling and the non-uniform fast Fourier transform (NUFFT) techniques. The adaptive spectral sampling of the envelope spectrum enables the determination of limited non-equispaced frequencies, which are randomly sampled according to a uniform distribution. Thus, the Cholesky decomposition is only required at limited specific frequencies, which dramatically reduces the computational cost of matrix factorizations. Since the randomly sampled frequencies are not equispaced, utilizing FFT to accelerate the summation of trigonometric functions becomes impractical. Then, the NUFFT that adapts the non-equispaced sampling points is employed instead to expedite this process with the non-uniform increment approximated through reduced interpolation. By taking the wind field simulation of a long-span suspension bridge as an example, a parametric analysis is conducted to investigate the effect of random frequencies on the simulation error of the developed approach and the convergence of spectra. Finally, the developed approach is further validated by focusing on the spectra and probabilistic density functions of the simulated wind samples, and the simulation performance is compared with that of the traditional approach. The analytical results demonstrate the efficiency and accuracy of the developed approach in simulating ergodic stochastic processes.

Numerical investigation of turbulence effect on flight trajectory of spherical windborne debris: A multi-layered approach

Accurate modeling of the turbulent wind field is a crucial component of risk analysis for structures to windborne debris damage. Existing studies typically simplify the complexities of wind turbulence, and the potential influence on the accuracy of debris flight modeling has not been systematically demonstrated. This study takes a multi-layered approach to numerically simulate the flight trajectory of spherical debris in a turbulent wind field. Complexities are incrementally added to the simulated wind field to systematically investigate the influence of spatial correlation and non-Gaussian features of turbulence on debris flight behavior. The sensitivity of debris flight behavior to turbulent wind features will inform the design of debris flight tracking wind tunnel tests and building façade debris vulnerability modeling efforts.

The reproduction of 2-D non-synoptic wind field in an actively controlled wind tunnel

This work mainly discusses the simulation of 2-D non-synoptic wind field in a novel actively controlled wind tunnel. The vibrating fins with airfoil shape are installed at the downstream of multiple fans in the updated active wind tunnel, which will work with fans simultaneously to generate 2-D non-synoptic flow. The fins mainly control the vertical flow while the fans control the along-wind flow, and the input signal of equipment can be adjusted in a predefined way. Then, based on Banach fixed-point theorem, the input signal of fans and fins is constantly updated by an iteration-based method to derive the generated wind characteristics to approach the different target values within an acceptable error range. According to the degree of interference between the longitudinal and the vertical wind characteristics, different iteration strategies are proposed for different wind fields. Two typical non-synoptic wind fields are taken as application examples: irregular turbulence spectra in typhoons and non-stationary winds in mountainous terrains. After iterations, both case studies were generated appropriately in the active tunnel. The simulated wind fields are crucial for wind-resistant design of wind-sensitive structures under non-synoptic wind climates.

Study of Wind Field and Surface Wind Pressure of Solar Greenhouse Group under Valley Topography Conditions

There is a wind interference effect between greenhouses in a group arrangement of solar greenhouse groups. To ensure the structural integrity of greenhouse groups situated in valleys, it becomes imperative to analyze both the wind pressure distribution patterns and the wind interference effects. This arises from the recognition that the wind load coefficients applicable to solar greenhouse groups nestled within valleys deviate from those observed in flat plains. The application of the contour modeling method facilitated a realistic reconstruction of the authentic topography within the study area. Subsequently, a wind field simulation was executed specifically for the constructed valley. The resultant wind field data for the studied valley area were then obtained. In the valley, nine solar greenhouses were systematically arranged in a three by three configuration. Special attention was directed towards assessing the surface wind pressures derived meticulously from the simulated wind field and wind direction angle of 0°. The findings elucidate the following: (a) The wind speed ratio exhibits a diminution on the leeward side of the mountain as compared to the windward side, with a notably reduced wind speed ratio observed in proximity to the mountain. (b) An amplification effect is discernible in the peripheral zone adjacent to the leading row of greenhouses, proximate to the incoming airflow. Particular emphasis is warranted regarding the reversal of wind direction observed in the secondary row of greenhouses positioned along the north wall and front roof, specifically at a wind angle of 0°, owing to the pronounced influence of interference effects. Hence, when undertaking the design and construction of a cluster of solar greenhouses within the valley terrain of Tibet, meticulous consideration must be directed towards both the meticulous calculation of wind loads within the periphery of the greenhouses and the judicious selection of the grouping’s location.

Multi-scale simulation of typhoon wind field at building scale utilizing mesoscale model with nested large eddy simulation

Based on the mesoscale WRF (Weather Research Forecast) and LES (Large Eddy Simulation), an integrated numerical simulation framework aiming to resolve typhoon wind fields around urban building blocks has been developed. The holistic multi-scale simulation spans four scales: macroscale (∼1000 km), mesoscale (∼100 km), microscale (∼1 km), and building scale (0.1–100m). By interactively sharing the meteorological data among different scales, this simulation framework addressed the challenge of downscaling typhoon effects in urban environments. Typhoon weather reanalysis and urban wind field simulation were conducted by the WRF model with nested computational domains incorporating high-resolution topography data. For the downscaled LES model with urban buildings, the wind profiles produced by the WRF model were used at the interface with provided turbulent fluctuations in the flow. K11 building is a 270-m-tall building located in a densely built-up area of Hong Kong. Wind velocity and pressure fields surrounding the K11 building in Hong Kong during Typhoon Kammuri were obtained by the proposed framework, and the simulation results were validated by comparing with the meteorological data and full-scale measurements at the top of the K11 building. The interactions of the wind fields and building clusters resulting in vortex shedding, separation, and channeling effects have been resolved at high resolutions. Probabilistic distributions and higher-order statistics of wind pressure, i.e., skewness and kurtosis, were presented to highlight non-Gaussian characteristics of the simulated local wind pressure on the K11 building. Based on the simulated wind pressure, wind-induced vibration of the K11 building during the typhoon was analyzed and compared to the measurements.

Wind resource assessment at mountainous wind farm: Fusion of RANS and vertical multi-point on-site measured wind field data

RANS (Reynolds-averaged Navier-Stokes) has become one of the mainstream methods to determine the wind field in the wind resource assessment of the complex terrain. However, before the simulation of wind field by RANS, defining the inlet boundary condition often depends on user's experience, and lacks of theoretical guidance, which brings great uncertainties to the accuracy of simulation results. In this paper, based on the vertical multi-point wind speed data (including wind direction) obtained from the on-site measurement and the wind speed data simulated by RANS, a data fusion method called the RANS-VMM (Vertical Multi-point on-site Measurement) method is proposed. In this method, through the polar coordinate diagram (PCD) that can express the wind direction and wind profile index at the same time, the vertical multi-point measured wind speed of wind measurement tower and the RANS simulation results are fused via multiple iterations, which can reconstruct the wind field distribution with spatial variability in complex mountainous areas, thus improving the accuracy of wind resource assessment in the complex terrain. The evaluation and verification of the proposed method are conducted through an real wind farm with complex terrain, and the results indicate that the RANS-VMM method can improves the accuracy of wind resource assessment in the complex terrain.

Wind-resistant reliability assessment of a super-high tower crane considering the randomness and correlation of turbulent spectral parameters

The need for wind-sensitive super-high tower cranes during the construction of high-rise structures has been growing, which makes it critical to assess the wind-resistant reliability of cranes. The accuracy of assessment is dominated by the refined simulation of real stochastic wind fields, which is usually based on the deterministic turbulent spectra including fixed spectral parameters. However, it might cause significant errors to estimate extreme responses of structures. Therefore, a simulation method for stochastic wind fields considering the randomness and correlation of turbulent spectral parameters is proposed in this study. The random functions of correlated spectral parameters are constructed based on several independent elementary random variables. A novel simulation method for stochastic wind fields involving the established random turbulent spectral functions is utilized to generate fluctuating wind samples at the Ma'anshan Yangtze River (MYR) Bridge site. In combination with the probability density evolution method, the stochastic response analysis and reliability assessment of wind-induced vibration of the crane are addressed. Results prove the effectiveness of the proposed approach in depicting probabilistic properties of real wind fields. Meanwhile, the wind-resistant comfort reliability of the tower crane is higher when considering the randomness and correlation of turbulent spectral parameters.

Exploring the influence of building form parameters on three-dimensional ventilation potential in urban centers: A case study of Nanjing, China

In urban areas, variations in the functional usage of buildings or their clusters directly influence the 2D/3D morphology of buildings which can lead to changes in the ventilation potential (VP) at different heights, but there is a lack of refined quantitative relationship analysis between 3D building form parameters (BFPs) and VP at different heights within a certain urban area. The objective of our study is to obtain simulated wind field data from different heights, considering distances from roads, and transverse and longitudinal sections. We employ partial correlation analysis, simple correlation analysis, and Geographic detectors to uncover the extent and mechanisms of the influence of BFPs on the ventilation effectiveness of neighborhoods in a major urban center in China, specifically Nanjing. The findings demonstrate that, at all heights, there is an inverse relationship between wind speed and building density (BD), with the location of higher wind speed generally aligning with the intersection points. The correlation coefficients between BD and simulated wind speed are 0.040 (1.5 ​m), −0.475 (10 ​m), and −0.314 (30 ​m), while the correlation coefficients between building height (BH) and simulated wind speed are 0.237. However, no significant correlation is observed between floor area ratio (FAR) and simulated wind speed. Geographic detector analysis reveals differences in the correlation between BFPs and simulated wind speed at different heights within various building functional areas. Our study provides some practical information for urban planners and designers to carry out wind sensitivity and adaptation planning and urban design.