Pedestrian-level Wind Environment Research Articles

Wind tunnel measurement of pedestrian-level gust wind flow and comfort around irregular lift-up buildings within simplified urban arrays

The implementation of lift-up buildings has demonstrated their practicality in enhancing urban wind comfort in high-density cities. The pedestrian-level wind environment around a central lift-up building surrounded by low-rise buildings was measured using wind tunnel experiments. The time-averaged velocity field and turbulence statistics, including the turbulent kinetic energy, normal component of the Reynolds stresses, gust factor, and gust wind velocity field, were discussed. Based on the results, the pedestrian-level gust wind flow and comfort for two typical building shapes (Arc, V-shaped) were compared with Rectangular lift-up buildings under different wind directions (0∘, 90∘ and 180∘), the pedestrian-level wind environments (PLWEs) were assessed following two wind criteria for weak and windy wind conditions by wind speed thresholds and maximum allowed exceedance probabilities. The results showed that the erection of the high-rise lift-up building modified the pedestrian-level wind environment around the building groups, owing to the interaction between the downwash flow around the building and the surrounding building blocks. A region of high mean and gust wind velocity was observed at the lateral and rear side of the central lift-up building due to the lateral entrained wind and Venturi effect between elevated columns, indicating that lift-up buildings can enhance PLWEs even in the presence of surrounding buildings. The Arc-shaped lift-up building tends to generate a larger “Intolerable” area compared with V- and Rectangular-shaped buildings due to its curved surface. The wind impacts the convex portion of the building, leading to airflow divergence and facilitating downstream ventilation.

Smart urban windcatcher: Conception of an AI-empowered wind-channeling system for real-time enhancement of urban wind environment

The dense configuration and rapid proliferation of high-rise buildings in central Hong Kong have led to increasing stagnation of pedestrian-level airflows, lowering the wind speed and exacerbating issues in wind and thermal comfort. Addressing these problems can be difficult without significant building renovations and urban re-planning. This paper introduces a novel framework for the real-time enhancement of the local urban wind environment using motion-controlled billboards, or smart urban windcatchers, managed by a deep reinforcement learning (DRL) agent. The DRL agent determines the windcatchers' optimal positions based on street-level sensor data, independent of meteorological data. The framework's effectiveness was assessed using a simplified city grid model, where two windcatchers aimed to optimize the pedestrian-level wind environment on a specific street. Simulation results indicated that the windcatchers could effectively alter the flow direction in the streets, promoting or diverting air passages per demand. The DRL agent also gave accurate instructions to the windcatchers under various weather conditions, achieving near-optimal wind environment scores. This paper introduces the conception and confirms the feasibility of the windcatcher system, laying the groundwork for future research—as it is much needed and welcomed—to enhance the system and overcome the acknowledged challenges in large-scale, real-world implementation.

Effects of Wind Shields on Pedestrian-Level Wind Environment around Outdoor Platforms of a Megatall Building

Effects of Wind Shields on Pedestrian-Level Wind Environment around Outdoor Platforms of a Megatall Building

Large eddy simulation study on pedestrian-level wind environments around elevated walkways and influential factors in ideal urban street canyons

Constructing elevated walkway systems is an effective and prevalent strategy for densely populated cities to improve pedestrian walkability and road safety. Nevertheless, adding an elevated walkway inside the street will inevitably influence the local wind environment, which has rarely been investigated. This study aims to examine the pedestrian-level wind environment around the elevated walkway in three-dimensional (3D) ideal urban street canyons using large eddy simulations. The impacts of street aspect ratio (H/W = 1, 2, 3), elevated walkway width (Wew/W = 0.2, 0.4, 0.6), and sidewall type (open, semi-hermetic, hermetic) on the mean wind velocity and gust wind velocity fields were quantified. Results indicate that the elevated walkway has an adverse effect on the pedestrian-level wind environment. After adding an elevated walkway, the area-weighted average mean and gust wind velocities of the target street are decreased, with a maximum rate of over 20% and 30%. Increasing H/W may be positive or negative for the pedestrian-level wind environment, as the overall mean and gust wind velocities do not show monotonic variations with H/W. Extremely wide elevated walkways should be avoided as the pedestrian-level mean and gust wind environments worsen with increased walkway width. Using semi-hermetic or hermetic sidewalls slightly improves the pedestrian-level mean and gust wind environments. This study promotes the knowledge of the impacts of elevated walkways, street aspect ratio, and walkway designs on pedestrian-level mean and gust wind environments, providing a scientific basis for further research.

Numerical Study of Pedestrian-Level Wind Environment Around Elevated Walkways and Influential Factors in Ideal Urban Street Canyons

Numerical Study of Pedestrian-Level Wind Environment Around Elevated Walkways and Influential Factors in Ideal Urban Street Canyons

Improving the pedestrian-level wind comfort by lift-up factors of panel residence complex: Field-measurement and CFD simulation

High-rise buildings in modern cities can hinder airflow and cause a weak local wind condition that intensifies pedestrian-level thermal discomfort. The lift-up design has been recognized as an effective way to improve wind comfort at pedestrian height levels due to its wind amplification effect. However, previous research has focused mainly on isolated buildings, while the influences of lift-up factors and their interactions on the pedestrian-level wind comfort have not been studied comprehensively enough. Therefore, this study aims to investigate the effects of lift-up ratio and positions of lift-up design on the pedestrian-level wind environments around a residence complex by combining field measurement and Computational Fluid Dynamics (CFD) simulation. An array of 12 panel buildings located in Chongqing was selected to collect relevant environmental parameters, including the mean wind velocity ratio (MVR) for model validation. Different simulation scenarios were set to quantitatively analyze the wind condition improvement in both the lift-up layer and the target research area of the residence complex. Results show that the lift-up position at both ends or in the middle has the most significant effect—about 94.83% and 96.03%—on improving lift-up layer MVR. In addition, the target area MVR of the optimal condition is 36.35% higher than that of the basic condition and continues steady growth with the increasing lift-up ratio. Findings in this study provide scientific references for city planners to improve pedestrian-level wind comfort.

Assessment of the influences of post-construction facilities on pedestrian-level wind environment: An experimental study in Changsha, China

With continuous urbanisation, an increasing number of post-construction facilities (such as high-rise buildings and green plants) have altered the original layout of the community. Which has resulted in deterioration of the wind environment. However, there is a deficiency of qualitative studies on the pedestrian-height wind environment that focus on the influence of post-construction facilities. The presents research takes Changsha universal time community as a case study. A wind tunnel test at a scale of 1:250 was performed to analyse the wind environment by considering the post-construction facilities. 81 sets of cases with different inflow patterns, wind directions, adjacent high-rise buildings, and plants were examined to reveal the flow field distribution characteristics. Furthermore, the exceedance probability method was introduced to assess the wind environment of the community in different cases. The results indicate that the index distribution coefficient of wind velocity and the turbulence intensity profile inside the practical community is significantly larger than the code values. A roughness distance of 800 m can generate highly effective mean wind profiles. However, it is unable to generate the desired turbulence profiles. Considering the post-construction facilities, high-rise buildings cause acceleration effects on the average wind velocity and the acceleration effects are inversely proportional to the distance of the post-construction facilities. Large, medium, and small trees cause deceleration effects of the average wind speed and improve the wind environment comfort quality of the community.

Investigation of Pedestrian-Level Wind Environment with Skyline Quantitative Factors

This paper presented a Computational Fluid Dynamics (CFD) study on the relationship between skyline quantitative factors and the wind environment. At present, most researches on skyline revealed the changes of skyline quantitative factors on the aesthetic degrees but neglected the influence of the factors on the outdoor wind environment. This paper addresses the gap in using the changing factors for the prediction of outdoor wind speed. It provides a standardized range for aesthetic degrees in the comfortable range of the wind environment and an exact relationship between the factors and the wind environment. To validate the effectiveness of the proposed approach, a case study is undertaken on the existing skyline of Qianjiang New City in Hangzhou and extracts the following three skyline quantitative factors in skyline contour: contour tortuosity, building undulation, and skyline rhythm index. The result shows that the proposed range and relationship are ready to provide a quantitative understanding of the skyline under outdoor wind conditions.

Assessment of the Influences of Post-Construction Facilities on Pedestrian-Level Wind Environment: An Experimental Study in Changsha, China

Assessment of the Influences of Post-Construction Facilities on Pedestrian-Level Wind Environment: An Experimental Study in Changsha, China

Pedestrian-Level Wind Environment Assessment of Shenyang’s Residential Areas through Numerical Simulations

In recent decades, increasing urbanization has increased construction land shortages, which has made people pay more attention to the utilization of vertical space. The emergence of more and more high-rise buildings has affected the wind environment at the pedestrian level, especially in residential areas. In this research, the typical patterns of the layouts of residential buildings in Shenyang were investigated and summarized, and the wind environment of the residential areas of different architecture layouts was simulated according to the climatic conditions in Shenyang. After analyzing the simulation results, a typical layout mode for the residential areas in Shenyang was developed to facilitate the establishment of a favorable wind environment. In comparison with different building layouts, a staggered layout of slab buildings, half-enclosed layout of point buildings with openings on the south side, slab-point combined buildings with slab buildings on the north side, and point buildings on the south side were found to be the most suitable layouts for Shenyang’s climate. Thus, this study can provide guidance to designers and urban planners in addition to practical suggestions for residential planning.

Generic models for predicting pedestrian-level wind around isolated square-section high-rise buildings

High-rise buildings have significant effects on pedestrian-level wind in their vicinity, and are closely related to people's daily lives. The social implications of this problem have caused worldwide concern. Thus, an accurate and fast way for assessing the pedestrian-level wind environment has become increasingly important in the preliminary design of tall buildings. Some mathematical formulae for predicting pedestrian-level wind, referred to as generic models (GM), have been developed from experimental results. In this study, GMs reflecting the different contributions of physical causes, such as Type I (Slenderness) Effect and Type II (Height) Effect, on pedestrian-level wind are proposed and verified based on quantitative analyses and wind tunnel test results. The proposed GMs may be applied to assess pedestrian-level winds for various square-section high-rise and super-high-rise buildings, with widths from 25 m to 75 m, and heights from 60 m to 600 m.

Predicting wind flow around buildings using deep learning

The wind velocity field around buildings provides deep insights into the aerodynamic characteristics of buildings and indicates the pedestrian-level wind environment around buildings. Particle image velocimetry (PIV) is usually employed to measure the wind velocities around building models. Due to laser-light shielding, measuring instantaneous wind velocities at some shielded locations around a building model remains difficult. As a result, analyzing the wind flow pattern with these unmeasured wind velocities is difficult. Using machine learning techniques to impute unmeasured values allows for a comprehensive study of wind flow patterns with laser-light shielding. Unmeasured velocities around building models were imputed in this study using machine learning (ML) models such as the generative adversarial imputation network (GAIN), multiple imputations by chained equations (MICE), and neighbored distanced imputation (NDI). GAIN was the best model with a minimum variance and standard deviation of 1.508 and 1.228, respectively. Compared with experimental wind velocities, GAIN produced the minimum average mean squared error of 2.4%. The correlation between the experimental and predicted wind velocities was 98.2%. Thus, the validated GAIN model is recommended to be integrated into the PIV study to impute the unmeasured wind velocities to obtain a complete wind flow pattern.

Improving local pedestrian-level wind environment based on probabilistic assessment using Gaussian process regression

Many wind comfort assessment standards have been proposed to evaluate wind comfort and safety in spaces with intended use for pedestrians, such as pathways, building entrance areas, amenity spaces, and outdoor sitting spaces. However, the optimization of the wind environment presents a unique combination of complexities in assessment, simulation, and design. Conventionally, designers rely heavily on wind tunnel experiments or computational fluid dynamics simulations based on which only limited proposals are examined to select the one with the best wind performances. A new design framework for proactively improving the wind conditions at various measuring positions is demonstrated in this paper. Gaussian process regression models are combined with the Latin hypercube sampling method to approximate the relationships between design variables and wind velocities at discrete locations. Gaussian process regression is a non-parametric model well-suited for modeling the non-linear and stochastic wind behaviors. Moreover, it can provide the prediction mean and variance, and the latter is incorporated into a prediction quality function to quantify the modeling uncertainty. In the case study, with the objectives of maximizing the winter and summer wind comfort and minimizing the modeling errors, the robust and near-optimal designs of a target building in an infill development project are explored using the evolutionary search algorithm. We believe that this framework can be migrated to other urban design practice to better predict and simultaneously optimize the microclimate performances at locations of interest, such as solar access, indoor ventilation efficiency, and thermal comfort.

Improved urban heat island mitigation using bioclimatic redevelopment along an urban waterfront at Victoria Dockside, Hong Kong

Bioclimatic design provides solutions to mitigating the urban heat island (UHI) effect and improving urban quality of life. Waterfront settings provide a unique opportunity for UHI mitigation, as cool winds (i.e. sea breezes) provide good cooling conditions. We used ENVI-met numerical simulations to investigate the synergistic mitigation effects of redeveloped urban forms, ventilation corridors, and extensive greenery on local microclimate and outdoor thermal comfort at an urban waterfront in Victoria Harbour, Hong Kong. The thermal performance along the waterfront and within an inner urbanised area was evaluated in three scenarios: existing configuration (Case A), redeveloped building form (Case B), and Case B with a ventilation corridor and extensive greenery added. In the study area's subtropical climate, the additional strategies used led to a synergistic improvement in microclimate and thermal comfort in both settings. The appropriate use of combined urban forms and ventilation corridors along waterfronts can thus lead to a more acceptable pedestrian-level wind environment and enhance the ventilation potential within inner urbanised areas. The cooling intensity of greenery (turf and green facades) along such waterfronts can also be extended for further benefits. Overall, the synergistic mitigation effects of redeveloped urban forms, ventilation corridors, and extensive greenery in proximity to water bodies demonstrated here provide science-based guidance for the use of bioclimatic design along urban waterfronts in order to achieve improved microclimates and thermal comfort at neighbourhood scales.

Multi-fidelity shape optimization methodology for pedestrian-level wind environment

In this study, a multi-fidelity shape optimization framework is proposed for the pedestrian-level wind environment (PLWE). In the proposed framework, low-fidelity computational fluid dynamics (CFD) models based on steady Reynolds-averaged Navier–Stokes equations (RANS) models and high-fidelity CFD models based on large-eddy simulation (LES) are efficiently integrated into the optimization process to improve the optimization reliability while maintaining its computational speed in an affordable range for practical engineering applications. The optimization solver is coupled with an approximation model generated by low-fidelity CFD samples obtained using a design of experiments (DOE) technique. The optimal candidates are then evaluated according to the degree of improvement of the objective function compared to the reference case. If the degree of improvement shows significant deviations between the low-fidelity and high-fidelity models, suitable corrections and modifications are applied to improve the reliability of the optimization process. The applicability of the proposed method was investigated in terms of minimizing the high-wind-speed area, as the optimization objective, around a high-rise building considering (a) uniform urban blocks and (b) real urban blocks with different frequency distributions of wind directions associated with two different local wind climates. In summary, a significant reduction in the critical strong-wind area around the target building was realized using the proposed optimization framework. Furthermore, the application of the proposed multi-fidelity optimization framework highlighted the importance of considering the local wind climate in architectural design.

Hybrid framework for rapid evaluation of wind environment around buildings through parametric design, CFD simulation, image processing and machine learning

High-efficient evaluations of building performance are often required for comparisons of different design alternatives in architectural sustainable design processes. General Computational Fluid Dynamics (CFD) simulations are usually complicated and time-consuming for wind environment investigation and evaluation. A hybrid framework for rapid evaluation of pedestrian-level wind environment will be proposed in the present work. This framework will then be formulated by integrating parametric design, CFD simulation, image processing, and machine learning, and it could immediately predict the Low-Velocity Areas (LVAs) around rectangular-form buildings. A large amount of data of 300 building cases generated by parametric design, CFD simulation, and image processing to train a Machine Learning Model (MLM) could be applied for the prediction of LVAs. In the case investigations, MLM was tested in the prediction of the other new 24 building cases with random geometric parameters. The comparison of MLM and CFD results showed that their solutions were close to each other. Efficiency and accuracy of the hybrid framework were further demonstrated through quantitative analysis of statistical discrepancies of MLM and CFD results. Hybrid framework was an original attempt to integrate multiple emerging computational tools, and it could provide high-efficient quantitative analysis of wind environment and give practical design optimization information in the early stage.

Comparison of hexahedral, tetrahedral and polyhedral cells for reproducing the wind field around an isolated building by LES

The wind field around a 1:1:2 isolated building was predicted by large-eddy simulation for evaluating the pedestrian-level wind environment. This study focused on the effects of cell types (hexahedral, tetrahedral and polyhedral cells) and boundary layer mesh on the time-averaged and fluctuating wind characteristics. The minimum cell size and stretching ratio were set to be the same among all cases. The case composed of hexahedral cells was found to have the best agreement with the experiment among the three cell types. The accuracies of the polyhedral cases are close to that of the hexahedral case, and better than those of the tetrahedral cases. However, the polyhedral mesh is most economical for the computational resources since the cell numbers of the polyhedral cases are less than half of that of the hexahedral case and about a quarter of those of the tetrahedral cases. It was also found that the boundary layer mesh does not improve the numerical accuracy under any circumstances. For both tetrahedral and polyhedral meshes, the boundary layer mesh can improve the numerical accuracy in the region above the flat ground by reducing the mesh non-orthogonality and skewness. However, the boundary layer mesh was found to worsen the mesh quality in the local region around the sharp corners of the building for both tetrahedral and polyhedral meshes. As a result, the boundary layer mesh did not lead to the expected improvement of numerical accuracy of wind velocity in the sensitive region of the separated flow from the sharp corners.

A Gaussian Process-Based emulator for modeling pedestrian-level wind field

Wind tunnel tests and computational fluid dynamics (CFD) simulations remain the main modeling techniques in wind engineering despite being expensive, time-consuming, and requiring special facilities and expert knowledge. There is a clear need for a fast, accurate, but, at the same time, computationally economical substitute. This study proposes a Gaussian Process-based (GP-based) emulator to predict the pedestrian-level wind environment near a lift-up building – an isolated, unconventionally configured building. The proposed GP-based emulator transcends the limitations of previous emulators as it can handle many inputs (8) and output parameters (384) and a large dataset (150 CFD simulations). To increase computational efficiency, the current study proposes a data reduction method based on Principal Component Analysis (PCA) and a technique to estimate hyper-parameters based on optimization. The latter can efficiently compute 250 hyper-parameters and requires no prior knowledge of their probability distributions. The emulator is faster, by a factor of 107 than CFD simulations in predicting wind speeds, and its accuracy is substantiated using both qualitative and quantitative analyses, which reveal that the emulator's predictions of all-prominent flow features near a building have no systematic bias, are highly accurate, and have great reproductivity.

Classification and pedestrian-level wind environment assessment among Tianjin's residential area based on numerical simulation

In this study, Tianjin's 36 practical residential areas were classified into four main categories and nine subcategories of layout modes based on actual planning methods. The wind conditions of each layout mode were evaluated with ENVI-met software and compared using three wind environment factors: wind speed, calm wind area ratio and wind speed dispersion. Further, correlations between spatial morphological factors and wind environment factors were established. Results indicate that the classification method of layout modes used in this study can fully reflect spatial differences between real residential areas. From comparison of the three wind environment factors, the mid-rise enclosed mode was found to exhibit the worst wind environment due to its low wind speed while the mid-rise parallel and mid high-rise modes are recommended as the most suitable for Tianjin's climate. The wind environment of high-rise layout modes are not as favourable as the wind environments of the mid-rise and mid high-rise modes. Frontal area density and average building height are shown to be key spatial morphological factors which affect the pedestrian-level wind environment. They can be used in residential planning practices to improve the wind condition. This research presents an opportunity to assist urban planners and researchers in developing a comprehensive understanding of pedestrian-level wind conditions in different residential layout modes.

Improvement Strategies Study for Outdoor Wind Environment in a University in Beijing Based on CFD Simulation

The outdoor wind environment is one of the most important factors influencing the biological environment and human comfort. The campus of China University of Mining & Technology (Beijing) (CUMTB) is the case study for this research. PHOENICS simulation software was used to carry out a numerical simulation study of the outdoor wind environment. The pedestrian-level wind (PLW) environments for both winter and summer were investigated. Based on the numerical simulation results, the overall evaluation and subregional analysis of the campus’ current outdoor wind environment were carried out. Then, according to the results and problems of wind environment assessment, improvement measures and strategies of outdoor wind environment in universities are proposed from the aspects of campus planning, single building form, and greening configuration. The main goal is to further improve the outdoor space and environment of universities in Beijing and provide general guidelines to improve the quality of the universities’ wind environment effectively. The strategies can provide a reference for the same type of campus on wind environment renovation and improvement. This study can also provide data support and reference significance for outdoor thermal environment/pedestrian environment research.