Open AccessArticle

Numerical Simulation and Optimization of Outdoor Wind Environment in High-Rise Buildings Zone of Xuzhou City

Huanhuan Fang

¹,

Xiang Ji

²,

Jiuxin Wang

³,

Jijun Lu

³,

Mengcheng Yang

¹,

Jiajun Li

³ and

Zhongcheng Duan

^3,*

School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221000, China

Jiangsu Collaborative Innovation Center for Building Energy Saving and Construction Technology, Jiangsu Vocational Institute of Architectural Technology, Xuzhou 221000, China

School of Architecture and Design, China University of Mining and Technology, Xuzhou 221000, China

Author to whom correspondence should be addressed.

Buildings 2025, 15(2), 264; https://doi.org/10.3390/buildings15020264

Submission received: 15 December 2024 / Revised: 14 January 2025 / Accepted: 15 January 2025 / Published: 17 January 2025

(This article belongs to the Section Building Energy, Physics, Environment, and Systems)

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Abstract

High-rise developments frequently exert adverse impacts on the outdoor wind environment, leading to a deterioration in the overall quality of urban surroundings and a reduction in the comfort levels of residents. This study systematically investigates typical high-rise settlements in Xuzhou City and proposes optimization strategies to address wind environment issues through an in-depth analysis of building planning parameters. Utilizing Computational Fluid Dynamics (CFD) simulations, the research identifies key wind-related challenges associated with high-rise buildings in representative settlements. The study comprehensively examines the effects of building height, width, orientation, spacing, and layout on the outdoor wind field, progressing from individual building units to clusters. Based on these findings, optimization strategies are formulated and validated through CFD simulations conducted on a representative high-rise settlement in Xuzhou. The results reveal that typical high-rise buildings in Xuzhou exhibit a height of 54 m, a width of 48 m, and an orientation ranging from 15° to 30° southeast. The front-to-rear building spacing is approximately 1.44 times the building height, with an additional 15 m spacing from mountain walls. Optimal wind conditions are achieved with a center-vacant building layout. The optimization of building form, spacing, and orientation substantially improves the outdoor wind environment by alleviating stagnant wind zones and reducing wind pressure differentials between the building fronts and rears, thereby enhancing the comfort of residents. This study provides a valuable reference for the planning and design of high-rise settlements, contributing to an improvement in urban environmental quality and the enhancement of livability.

Keywords:

high-rise settlements; outdoor wind environment; computational fluid dynamics (CFD) simulation; building planning

1. Introduction

Residential neighborhoods, as fundamental components of urban areas, play a crucial role in shaping people’s living conditions [1]. Poorly planned residential buildings can have a significant impact not only on the local microclimate but also on the overall comfort of residents [2]. In the case of high-rise residential developments, these effects are particularly pronounced, leading to issues such as downdrafts between buildings, extensive wind shadow zones, and street canyon winds [3,4,5].

There are three primary research methods for studying wind environments: in situ measurements [6], wind tunnel tests [7], and numerical simulations. Field measurements are greatly affected by the surrounding environment, and the resulting conclusions should aim to be more broadly applicable. Wind tunnel tests can be expensive and may not provide sufficient accuracy for large-scale settlement environments [8]. Computational fluid dynamics (CFD) simulations are the main tool used to analyze large-scale wind environments [9]. In terms of research focus on buildings in such environments, the study direction can be divided into monolithic and clustered aspects.

In the field of studying the outdoor wind environment of single high-rise buildings, the building’s morphology plays a crucial role in influencing the wind conditions. This includes factors such as the building’s structure [10], openings [11], and scale [12]. While single high-rise buildings may have a limited impact on the urban microclimate, they can still influence the surrounding wind patterns, particularly in relation to pollutants and air pressure. Yu et al. investigated the dispersion of air pollutants around cruciform high-rise buildings, observing that pollutants on the windward side predominantly descend along with the wind, whereas those on the leeward side exhibit distinct dispersion patterns [13]. Ishida et al. explored how a single high-rise building affects nearby low-rise structures, finding that when both types of buildings face the same wind direction, the low-rise building experiences a significant negative pressure, especially during extreme weather events like typhoons [14].

For high-rise building clusters, the building layout plays a crucial role in shaping the outdoor wind environment [15]. Research indicates that closed building layouts can hinder airflow in residential neighborhoods [16], while parallel layouts [17] or layouts oriented toward prevailing winds can improve ventilation [18]. Additionally, controlling the density and plot ratio of residential areas can enhance the wind environment [19]. Jin et al. explored the correlation between building density, plot ratio, wind projection angle, average building height, and the relative position of high-rise buildings in residential areas. They developed a model to predict the average pedestrian-level wind speed ratio. However, low-density high-rise examples are not widespread in China’s current residential land-use practices [20].

The specific architectural form of high-rise residential areas can impact the surrounding wind environment. For instance, altering the building form and scale perpendicular to the prevailing wind direction can increase the surrounding wind speed, leading to a “canyon wind” effect. Adjusting the aspect ratio can enhance the wind environment in high-rise residential areas located in both calm and high-wind-speed regions [21]. Additionally, modifying the gable spacing of high-rise buildings and the distance between front and rear buildings can influence the outdoor wind field [22].

Upon reviewing the aforementioned studies, it is evident that the majority of the existing literature focuses on optimization strategies for the outdoor environment of high-rise building clusters from a broad perspective. Many of these optimizations involve comparing various layout configurations and lack a systematic approach. Therefore, this paper conducts an analysis of the current outdoor wind environment of typical high-rise residential buildings in Xuzhou, considering the specific climatic conditions of the area. The study then delves into a detailed examination of the outdoor wind environment at the individual building level, deriving optimization strategies for single buildings. Subsequently, these single-unit optimization strategies are applied to optimize the high-rise district building complex using appropriate methods. This research employs a micro-to-macro optimization approach to effectively enhance the outdoor wind environment surrounding typical high-rise residential buildings in Xuzhou. The results of this study offer important insights for optimizing the design and spatial arrangement of high-rise buildings in the region.

2. Research Methodology

2.1. Research Object

This paper examines 11 completed high-rise residential districts in Xuzhou, analyzing their building height, building face width, building orientation, and building layout. The specific statistical results are presented in Table 1.

Among the residential buildings surveyed, 124 buildings are primarily concentrated between the 15th and 18th floors, which constitutes 52% of the total surveyed buildings, In the Arcadia, the proportion of buildings within the 15–18 floor range is the highest, accounting for 75% of the buildings in this area. Of the 11 high-rise residential areas surveyed, 9 are designed with staggered layouts, while one follows a parallel layout and one utilizes a free-form layout, Arcadia is a typical example of a staggered layout configuration. In Xuzhou, the predominant orientation of high-rise residential buildings is toward the south; however, due to the influence of factors such as local topography, surrounding road planning, and architectural design, some buildings exhibit slight deviations from the southward orientation. Specifically, in the case of Arcadia, the buildings are mainly oriented toward the south, with a slight tilt to the southwest. With regard to the facade width, buildings within the 40 to 49 m range make up the largest proportion, constituting 26% of the surveyed buildings. However, in Arcadia, 90% of the buildings have facade widths exceeding 60 m, making this characteristic particularly distinctive within the surveyed sample.

Through site visits and in-depth surveys, it was observed that the residents of Arcadia demonstrate the highest willingness for renovation. Based on these findings and the surrounding environmental context, Arcadia was selected as the case study for this research.

2.2. Numerical Simulation

2.2.1. Modeling

The shape of a building typically affects the distribution of wind around it. When simulating the outdoor wind environment of a building, the three-dimensional model should accurately represent the building’s size and intricate details within its height boundary. However, in practice, simplifying the computational model of the actual building is often necessary to reduce computation time and speed up convergence [23]. This simplification involves minimizing the complexity of concave and convex parts of the building while ensuring it does not impact the flow field distribution around the building [24].

In the process of model development, reasonable simplifications were made to the building models. Due to the large scale of the buildings, the influence of exterior facade ornamentation on the wind environment is negligible. Consequently, while simplifying the facade details, the geometry of the buildings was preserved with the highest possible accuracy to ensure the integrity of the model. This is illustrated in Figure 1.

2.2.2. Calculation Field Settings

In the computational domains, where H (Hight) represents the height of the tallest building within the considered area, the distance between the inlet and the buildings was set to at least 5H. This distance constraint was also applied to the outlet boundary, as well as to the lateral boundaries of the buildings. The height of the computational domain was defined as 6H. Following a grid sensitivity analysis, hexagonal meshes with a resolution of 1 m were employed in the areas of interest, while a finer grid resolution of 0.5 m was applied near the building wall boundaries and emission sources. This mesh resolution is consistent with that used in similar studies [25,26,27]. The total number of cells in the discretized domain ranged from 550,000 to 2.8 million, depending on the specific area being considered.

2.2.3. Computational Meshing

The computational domain was discretized into small cells using the surface-grid extrusion method proposed by van Hooff and Blocken [28]. Initially, a surface mesh with controlled grid dimensions was generated, which was then extruded vertically (or perpendicular to the surface mesh) to achieve optimal control over the grid topology (Figure 2). Additionally, four cells were included up to the pedestrian-level height, in accordance with the recommendations of best practice guidelines. The discretized computational domain consisted solely of hexahedral cells, which is crucial for ensuring the accuracy of CFD simulations [29,30,31].

In this study, to ensure both the accuracy of visualization and computational efficiency, the grid was defined with 100, 100, and 20 divisions along the X, Y, and Z axes, respectively. Additionally, a secondary grid refinement was applied in the region surrounding the model, with a refinement factor of 2. To further improve the smoothness and precision of the simulation results, a grid stretching ratio of 1.3 was applied in all directions, ensuring finer and more accurate results in the model’s vicinity, to enhance mesh density near the model [32]. The Jiangsu Province [33] and Beijing Green Building Design Standard [34] specify that, in pedestrian areas adjacent to buildings, the grid division at 1.5 m or 2 m height should contain a minimum of 10 grids, with key observation areas positioned at the third grid level or beyond. Based on these standards, this study employed an appropriate grid division, illustrated using Arcadia in Figure 2.

2.2.4. Calculation Boundary Condition Setting

Entrance condition setting: The inlet boundary conditions are primarily determined by the variation in the average wind speed with height, known as the wind speed gradient, which defines the velocity distribution curve. Near-ground airflow is influenced by surface friction, causing a reduction in wind speed. This reduction diminishes as the height from the ground increases, resulting in a wind speed distribution curve with lower speeds near the ground and higher speeds at greater heights. In computational simulations, an exponential function is commonly used as a simplified model to estimate wind speed at different heights, as shown in Equation (1):

\frac{U_{z}}{U_{s}} = {(\frac{Z}{Z_{s}})}^{α}

(1)

where Zs is the reference height (m), with a typical reference height of 10 m; Us is the average wind speed at the reference height (m/s); and Uz is the average wind speed at height Z (m/s). The exponent α represents the degree of wind speed reduction near the surface, where an increase in α indicates an increase in surface roughness. According to the ground roughness classification and corresponding α values provided in the “Code for Design of Building Structures Loads” [35], this study adopts a value of 0.3, in accordance with the actual conditions specified in Table 2.

The turbulence model and fluid material: This solver was modified to include an Eulerian passive scalar transport equation to account for pollutant dispersion, which is commonly used to model gaseous [26] or particulate matter dispersion [36]. The partial differential equations were solved using the Reynolds-Averaged Navier–Stokes (RANS) methodology and an RNG k-ε turbulence model [37]. This solver was previously validated by Reiminger, Vazquez, Blond, Dufresne, and Wertel [38]. The RNG k-ε turbulence model is commonly used for outdoor wind simulations, with the fluid material typically set as ’0’ for gas.

The number of iterations and step length: The software initially sets the number of iterations to 100 and the step length to 1, but these values should be adjusted according to the specific research context. In this study, the number of iterations was increased to 2000, while the step length remained at 1 [39,40].

Convergence parameters: The simulation was terminated upon achieving sufficient convergence. Convergence was considered satisfactory when the values at the specified observation points no longer changed, or when the root-mean-square (RMS) residuals dropped below 10⁻⁴. In this study, the convergence criterion was set to 0.01%. The European COST guidelines recommend an iterative convergence criterion of 0.001 for industrial applications, which is relatively stringent compared to the criteria typically applied in non-industrial applications. For simulations of the wind environment around buildings, convergence was determined when the residuals were reduced to 10⁻⁴. In addition to monitoring residual changes, the target variables were also assessed. If the values of the variables stabilized or fluctuated within a narrow range around a specific value, convergence was deemed to have been achieved [41,42].

2.3. Evaluation Criteria

This article integrates existing wind environment assessment standards with the climatic characteristics of Xuzhou [43,44,45]. It assesses the outdoor wind environment of residential areas in Xuzhou during winter and summer, focusing on wind speed, wind pressure, and wind speed amplification factor. Specifically, in summer, high-rise settlements should have wind speeds between 1 m/s and 5 m/s, a wind amplification factor below 2, a wind pressure difference of more than 1.5 Pa between the front and rear of 75% of buildings, and should avoid wind vortices. In winter, high-rise settlements should have wind speeds below 5 m/s, a wind speed amplification factor below 2, a wind pressure difference of less than 5 Pa between the front and rear of buildings, and should avoid wind vortices. The specific statistical results are presented in Table 3.

3. Results

The transitional seasons of spring and autumn in Xuzhou are relatively short, and their climatic characteristics are not as pronounced. Therefore, for climate simulation studies, it is more appropriate to focus on the summer and winter seasons, which exhibit more distinct climatic features. Summer is typically characterized by high temperatures and abundant rainfall, while winter is cold and dry. These two seasons feature more prominent climatic conditions, making them more suitable for detailed wind environment simulations and analysis.

This study simulates and analyzes the outdoor wind environment of Arcadia, a high-rise residential area in Xuzhou. The simulation includes summer conditions with easterly wind (E) at a speed of 2.3 m/s and winter conditions with northeasterly wind (ENE) at a speed of 2 m/s.

3.1. Verification of Numerical Simulations Through Comparison with Experimental Data

This study compares the measured and simulated results. In the field measurements are shown in Figure 3. Point 1 is located at the South Gate, Point 2 is at the East Gate Plaza, Point 3 is on the pedestrian path between the Comprehensive Building and Building 3, and Point 4 is situated in the landscape green space between Building 5 and Building 8. These measurement points were mapped to the corresponding locations in the simulation results. In the simulation, Point 1 is located in the calm wind zone with the minimum wind speed of 0.62 m/s, while Points 2 and 3 exhibit relatively higher wind speeds of 1.12 m/s and 1.41 m/s, respectively. The wind speed at Point 4 is 1.09 m/s, which is lower than that at Points 2 and 3. Overall, the wind speed pattern is Point 3 > Point 2 > Point 4 > Point 1 in both the measured and simulated results. The comparison indicates that the simulated wind speeds are generally higher than the measured ones, and there exists a certain degree of correlation between the values at each measurement point.

3.2. Summer Simulation Analysis of Arcadia’s Outdoor Wind Environment

Through the simulation, the summer wind environment of Arcadia Figure 4 is shown. During summer monsoon conditions, the wind speed in the Arcadia residential area typically ranges from 0 to 5 m/s. The occurrence of 5 m/s wind speed is attributed to the ’narrow tube effect’, where a single air inlet between Building 4 and Building 7 on the east side of the residential area acts as a natural Guiding Canyon. The limited number of air inlets has led to significant areas within the residential area experiencing wind speeds below 1 m/s at a height of 1.5 m. This paper divides the community buildings into three groups and uses the X-axis slice wind pressure cloud map to visually observe the distribution of wind pressure in front of and behind (north–south direction) each row of buildings. At the same time, the wind pressure values at a height of 10 m on the X-axis slice are measured using the Plot variable profile tool. Combining the results of both methods, the wind pressure distribution in front of and behind each group of buildings is analyzed, and the data are organized as shown in Table 4, where the wind pressure difference is taken as the absolute value.

Figure 3. (a) Measuring point positioning in Arcadia residential area; (b) Wind speed at 1.5 m of Arcadia residential area in summer; (c) Comparison of measured results with simulation results.

In the summer, wind pressure on the building surfaces of the entire community decreases gradually from east to west due to the influence of the easterly wind. To visually represent the distribution of wind pressure on the residential area surfaces, this study utilizes the Plot variable profile tool to analyze wind pressure values at a height of 10 m on the X-axis slice according to the grouping of residential buildings, and presents the findings in Table 4.

The presence of suction pressures on both sides of a building can be explained by examining the dynamics of airflow as it interacts with structural elements. According to Bernoulli’s Principle, an increase in the velocity of the airflow results in a decrease in pressure along the flow path. Consequently, the sides of the building, which experience accelerated wind due to the diversion around the building’s edges, manifest lower pressure regions, or suction pressures. This effect is particularly pronounced at sharp corners or any structural features that enhance flow separation and acceleration. Furthermore, the geometry and orientation of the building significantly influence where these low-pressure zones develop. Buildings with distinct, protruding features or irregular shapes are more likely to exhibit multiple points of airflow separation, leading to suction pressures on various facing and adjacent sides.

Through an investigation into the wind pressure difference between the front and rear of three groups of buildings, under the influence of east winds during the summer, it was observed that the wind pressure variance between the front and rear of the buildings was minimal. Building 5 was the only structure with a pressure difference exceeding 1.5 Pa, accounting for 9.1% of the total sample. Additionally, there were six buildings with a pressure difference ranging between 1 Pa and 1.5 Pa, constituting 54.5% of the total, while four buildings displayed a pressure difference below 1 Pa, accounting for 36.4%. These results suggest that most buildings did not meet the standard, which requires 75% of buildings to exhibit a wind pressure difference exceeding 1.5 Pa during the summer.

3.3. Winter Simulation Analysis of Outdoor Wind Environment in Arcadia

The simulation results of the outdoor winter wind environment in Arcadia are shown in Figure 5.

Under the influence of a 2 m/s wind coming from the east-northeast during winter, the wind speed distribution at a height of 1.5 m outdoors in the Arcadia residential area ranges from 0 m/s to 5 m/s. These wind speeds are insufficient to adversely affect pedestrian activities. The wind speed amplification factor is below two, indicating that there are no significant wind gusts that could jeopardize pedestrian safety. Most areas experience wind speeds below 1.5 m/s, with slightly higher speeds observed near the east gate.

The winter building wind pressure also demonstrates a high-pressure system in the east and a low-pressure system in the west. However, in comparison to summer wind pressure, the winter wind pressure predominantly moves northward, causing the high-pressure system of the entire cell to shift toward the northern side. Table 5 presents the organized data on the three groups of building surface wind pressures.

The table shows that Building No. 2 in the subdivision displays a wind pressure difference greater than 5 Pa between its front and rear. Furthermore, the wind pressure variance between building No. 9 and building No. 4 approaches the standard 5 Pa. Hence, it is essential to modify the building layout to enhance winter wind pressure in the residential area.

4. Discussion

4.1. The Influence of Building Planning Factors on the Outdoor Wind Environment

The Section 3.3 presented an overview of the outdoor wind environment in the high-rise district of Xuzhou during both the winter and summer seasons. This Section will delve into the impact of different factors on the outdoor wind environment, focusing on building planning. The paper will explore five key planning factors: building height, width, orientation, spacing, and layout.

4.1.1. Influence of Building Height on Outdoor Wind Environment

The study reveals that the majority of high-rise buildings in Xuzhou have heights ranging from 10 to 20 floors, with each floor considered to be 3 m in height. Therefore, building heights (H) of 30 m, 36 m, 42 m, 48 m, 54 m, and 60 m are obtained by incrementing every 6 m. The simulation results for these six building heights under summer wind conditions are presented in Figure 6.

The wind speed cloud diagram illustrates that as the height of the building increases, the area affected by the wind shadow at the rear of the building expands. Between building heights of 48–54 m, the previously low wind field begins to split into two distinct areas, leading to a more complex wind environment behind the building.

4.1.2. Influence of Building Width on Outdoor Wind Environment

Xuzhou’s high-rise residential buildings predominantly feature slab towers with face widths ranging from 20 m to 80 m. This study focuses on six groups of buildings with varying widths (W)—24 m, 36 m, 48 m, 60 m, 72 m, and 84 m. All groups have the same depth and height. The simulation results of wind speed at a height of 1.5 m are presented in Figure 7.

As the facade width of the building increases, the crossing wind will act on the sides of the building, and there is a noticeable enlargement in the width of the wind shadow region at the building’s rear. Although the length of the wind shadow area also extends, this increase is comparatively modest. Importantly, when the facade width reaches 48 m, discernible corner streaming winds emerge on both sides of the building. As the facade width continues to augment, the velocity of these corner streaming winds on either side of the structure markedly intensifies, and their area of influence correspondingly broadens. It can be postulated that should the external initial wind speed rise to a certain threshold, the corner turns on both sides of the building could potentially generate wind speeds that may compromise pedestrian safety.

Controlling building face widths can reduce wind speeds on both sides of the building. Chongqing Municipality [46] mandates that high-rise buildings over 54 m tall should have a maximum continuous spread face width of 65 m. Similarly, the city of Huai’an, closer to Xuzhou, specifies that buildings over 50 m in height should not exceed a face width of 50 m. Based on simulation results and these regulations, this study concludes that the face width of high-rise buildings should not surpass 50 m.

4.1.3. Influence of Building Orientation on Outdoor Wind Environment

The impact of building orientation on the outdoor wind environment was studied through simulations under seven different working conditions: 0°, 15°, 30°, 45°, 60°, 75°, and 90° angles between the building normal and the incoming wind direction. The study examined the wind shadow area of the building and the wind pressure on its surfaces under these varying conditions.

The findings presented in Figure 8 indicate that as the angle of the building increases in relation to the wind direction, the wind shadow area behind the high-rise residential building gradually decreases from 90°. Specifically, when the building is oriented at an angle of 0° with the wind, a larger vortex area forms behind the building leading to turbulent airflow. However, as the angle increases from 30° to 60°, the airflow becomes smoother, allowing for efficient ventilation within the building spacing. Based on the simulation results and the influence of building orientation on ventilation and lighting, this study suggests that buildings in Xuzhou can achieve optimal ventilation when oriented between south and southeast angles within the range of 30°.

Figure 9 shows that the wind pressure difference between the front and rear surfaces of tall buildings decreases as the angle between the building and the wind increases. At an angle of 75°, the wind pressure differential between the building’s front and rear surfaces is significantly reduced. This suggests that when the wind angle exceeds 75°, it will lessen the impact of building wind pressure ventilation. Given that the prevailing wind direction in Xuzhou during summer is easterly, it is optimal to orient the building between 15° and 30° east-south.

4.1.4. Influence of Building Spacing on Outdoor Wind Environment

The discussion in this Section focuses on two aspects of building spacing: longitudinal spacing and wall spacing. Longitudinal spacing impacts the lighting, ventilation, and wind environment between buildings, particularly affecting the rear row of buildings. On the other hand, wall spacing primarily considers fire prevention and ventilation within the building.

Based on the survey results of 11 high-rise residential communities in Xuzhou, the typical characteristics of high-rise residential buildings in Xuzhou are summarized. In order to study the effect of longitudinal spacing of buildings on the wind flow field, this study set up two identical high-rise building blocks with dimensions of 54 m in height, 48 m in width, and 14 m in depth.

In compliance with Xuzhou City’s sunshine regulations, this article utilizes a sunshine spacing coefficient of 1.44. This means that with a building height of 54 m, the minimum spacing between buildings should be 78 m. Building on this requirement, the study simulates different front and rear building spacings at 78 m, 88 m, 98 m, and 108 m to analyze the outdoor wind environment. The evaluation of simulation results is conducted by examining wind pressure cloud diagrams and wind speed vector diagrams along the X-axis slice through the building center, as depicted in Figure 10.

The findings suggest that as the distance between buildings increases, the impact of the wind shadow area of the front residential building on the rear building diminishes, while the wind pressure difference from front to back of the rear building intensifies. Specifically, when L = 98 m, the wind pressure difference between the front and rear buildings in the rear row reaches 1.5 Pa. Similarly, at L = 78 m, the wind pressure difference between the front and rear buildings in the rear row approaches 1.5 Pa. Moreover, adjusting the building angle can also meet the wind pressure difference requirements. In conclusion, the minimum longitudinal distance (L) between front and rear buildings should be at least 1.44 times the building height.

The building gable spacing in this study follows the guidelines outlined in the Jiangsu Province Urban Planning Management Technical Regulations regarding the minimum distance between high-rise residential gables [47]. The minimum simulated spacing B is 15 m, with increments of 5 m in sequence, resulting in a total of six sets of experiments conducted.

The analysis presented in Figure 11 demonstrates that as the distance between gables increases, the high wind speed area at pedestrian height (1.5 m) also increases. However, the wind speed amplification coefficient between building gables remains relatively stable, with the highest value not exceeding 1.5 in any of the six experimental groups. Despite the interaction of wind shadow areas behind two closely spaced high-rise residential buildings, the mutual influence of these areas persists up to a distance of 30 m. This underscores the unavoidable impact of the rear wind shadow area. Considering economic factors, it can be concluded that the evaluation criteria outlined in this article are met when the gable spacing is 15 m.

4.1.5. Influence of Building Layout on Outdoor Wind Environment

Building parameters simulated in this Section include a height of 54 m, width of 48 m, longitudinal spacing of 78 m, and wall spacing of 15 m. Based on the analysis in the Section 4.1.4, five typical high-rise settlement layouts in Xuzhou are considered: side-by-side, center vacancy, parallel staggered (left), parallel staggered (right), and front-to-back staggered. The final evaluation involves examining the wind speed contour map at 1.5 m height and the wind pressure contour map at 10 m height on the Z-axis slice to assess the simulation results.

4.1.6. Analysis of Summer Simulation Results

Summer simulation results, as depicted in Figure 12, reveal that buildings arranged in parallel configurations (such as side-by-side, center-vacant, and parallel staggered (left and right)) allow for effective wind flow between them, enhancing outdoor natural ventilation in the summer. Specifically, the side-by-side, center-vacant, and parallel staggered (left and right) layouts exhibit superior ventilation compared to the front and back staggered layouts. The central green space in the center-vacant layout minimizes obstructions to wind circulation in residential areas, making it the most effective layout for outdoor natural ventilation in high-rise residential areas during the summer. In conclusion, this study suggests that in summer, the outdoor ventilation effectiveness of residential areas follows this order: center-vacant layout > parallel layout ≈ parallel staggered layout (left and right) > front and back staggered layout.

The wind pressure simulation results show that the parallel and staggered parallel (left and right) building layouts exhibit positive pressure only on the windward side of the first column on the east side of the building. The second and third columns of the building experience negative pressure, and the wind pressure difference between the front and rear surfaces does not facilitate natural ventilation during the summer. The wind pressure in the center-vacant building layout is slightly better than the first two methods. The front-back staggered column type demonstrates the most favorable summer wind pressure distribution among the five layouts. In conclusion, the distribution of wind pressure difference between the front and back of the building in summer ranks is as follows: front and back staggered layout > center-vacant layout > side-by-side layout ≈ parallel staggered layout (left and right).

The prevailing wind direction in winter is ENE, and the buildings significantly impact the wind flow. Analysis of Figure 13 reveals that side-by-side and parallel staggered (left and right) building layouts provide effective wind protection due to their horizontal arrangement that blocks incoming wind. The center-vacant layout shows slightly weaker winter wind protection compared to the other layouts. The front and back staggered building layout, with larger spacing between walls, allows for better airflow but offers lower wind protection. In summary, the winter wind protection effectiveness of the five building layouts ranks as follows: parallel staggered (left and right) layout ≈ parallel layout > center vacancy layout > front and back staggered layout.

The analysis of the wind pressure distribution map indicates that during winter, buildings located in the first row on the north side and the first column on the east side of the back row experience the highest wind pressure on the windward side. A significant wind pressure disparity between the front and back of a building in winter can lead to cold wind infiltration, negatively impacting the building’s thermal efficiency. Hence, it is essential to minimize the wind pressure difference between the front and back of buildings during winter. Among the five building layouts examined, the parallel staggered row (right) layout emerges as the least favorable due to greater exposure to incoming flow and a larger wind pressure difference between the front and back of the buildings. Conversely, the front-to-back staggered layout displays a more favorable wind pressure distribution profile compared to the other layouts, as it features staggered openings at the front and back that reduce the windward surface area. In terms of reducing cold wind infiltration in buildings during winter, the ranking from most to least effective is front-back staggered layout > parallel staggered (left) ≈ side-by-side ≈ center-vacant > parallel staggered (right).

The simulation results in Xuzhou suggest that achieving good outdoor ventilation in summer requires attention to strengthening wind pressure differences between the front and back of buildings. In winter, the focus should be on outdoor wind protection in residential areas and reducing wind vibration and cold wind infiltration through building windows. Based on these findings, the center vacancy type building layout is considered ideal among the five building layouts.

4.2. Summary of Optimization Strategy

Optimization strategies for high-rise residential areas in Xuzhou can be summarized as follows: 1. To minimize the impact of quiet wind areas and building wind shadow areas, it is recommended to maintain a moderate overall enclosure degree in the residential area. 2. Considering ventilation needs in both summer and winter, the layout should prioritize a central and open design. 3. The ideal dimensions for high-rise residential areas in Xuzhou are as follows: building height of 54 m, building width of 48 m, building orientation between 15° and 30° southeast, front and rear building distance at 1.44 times the building height, and gable distance of 15 m.

4.3. Optimization Practice

4.3.1. Outdoor Wind Environment Optimization Design Strategy of Arcadia

Building Form Optimization Strategy

The simulation results in Section 3 demonstrate that the row of podiums on the east side of the Arcadia neighborhood impacts the incoming wind during the summer season when easterly winds prevail, leading to generally low wind speeds at the eastern 1.5 m of the neighborhood. To optimize the situation, the row of podiums on the east side was modified to create openings that direct easterly winds into the area. Moreover, the wide building width of Building 3 creates a significant wind shielding effect, resulting in a disordered wind environment around it and a large static wind area on the south side. Field research revealed that Building Three consists of two parallel buildings, prompting the optimization of Building 3 to be split into two separate buildings (3a and 3b) to reduce the original building width.

Building Spacing Optimization Strategy

The narrow spacing between Buildings 1, 2, and 3 hinders air circulation. To address this, Building 3 was disassembled into 3a and 3b, and shifted southward to increase the gap between the buildings. This adjustment led to the southwest relocation of Building 5 due to the influence of Building 3a. Given Xuzhou’s prevailing easterly winds in the summer, Buildings 7 and 11 on the eastern side of the neighborhood were moved southward to prevent a canyon effect and facilitate wind flow into the area.

Building Orientation Optimization Strategy

Xuzhou experiences dominant east winds in summer and northeast winds in winter. Simulation results reveal that there is a small wind pressure difference between the front and rear of the first column of buildings on the east side during summer, hindering effective wind pressure ventilation. Conversely, in winter, a larger wind pressure difference between the front and rear of the first column of buildings on the east side leads to the possibility of cold wind penetration. To address this issue, this study proposes deflecting Building 4, Building 7, and Building 11 to the east by 15°. This adjustment successfully improves the wind pressure difference between the front and back of the buildings while maintaining optimal lighting and ventilation conditions. The optimized settlement layout can be observed in Figure 14.

4.3.2. Optimization Results

Through the optimization, the wind environment in the winter and summer seasons is significantly improved, as shown in Figure 15.

Summer Simulation Results

Following the optimization, the static wind zone in the Arcadia neighborhood during summer decreased notably, leading to a general increase in wind speed in the residential area without exceeding 5 m/s. Specifically, wind speed in the residential area rose from 1.5 m/s to 2.5 m/s. By incorporating vents to channel wind between Buildings 2 and 4, the static wind area was reduced significantly. Furthermore, dividing Building 3 into two separate structures, 3a and 3b, with a staggered layout, resulted in the disappearance of a large static wind zone on the south side. The deflection of the three buildings to the east by 15° also enhanced wind pressure differences between the front and rear of most buildings post-optimization, leading to an overall improvement in wind pressure conditions within the settlement.

Winter Simulation Results

The high-rise settlement’s layout was optimized to significantly reduce the area of static wind in winter, as depicted in Figure 14, with no wind speeds exceeding 5 m/s. By adjusting the orientation of the first column of buildings on the east side toward the east, the angle with the prevailing northeasterly wind in winter was successfully minimized, consequently reducing the wind pressure differential before and after the buildings during winter. Post-optimization, it is evident from the figure that the wind pressure on the north side of Building 2 surpasses that on the south side, and the wind pressure disparity between the front and rear of the initial building on the east side has been lessened, leading to a significant enhancement in the wind pressure conditions within the settlement during winter.

5. Conclusions

This study investigates the current outdoor wind environment of typical high-rise buildings in Xuzhou and examines the architectural planning factors that influence these settlements. It subsequently proposes an optimization strategy for the wind environment of high-rise settlements in the region. The main findings are as follows: (1) The typical high-rise settlements in Xuzhou generally consist of 18 floors, with building widths ranging from 30 to 60 m. (2) The study establishes wind environment evaluation standards specific to Xuzhou, focusing on criteria such as wind speed, wind pressure differences, and wind vortex avoidance, for both summer and winter conditions. (3) The analysis reveals that in Xuzhou, high-rise buildings typically have a height of 54 m, a width of 48 m, and an orientation of 15–30° southeast. The front-to-rear building spacing is 1.44 times the building height, with 15 m of spacing from mountain walls. The optimal wind environment is achieved with a center-vacant building layout. (4) Optimization of the typical high-rise settlements in Xuzhou, based on these planning factors, significantly reduces static wind areas at pedestrian height, resulting in increased wind pressure in summer and decreased wind pressure in winter on the east side of the buildings.

There are numerous factors influencing the outdoor wind environment of buildings, including architectural layout, vegetation distribution, and the form of urban blocks. This study focuses specifically on the impact of building planning factors within high-rise residential communities on the wind environment, excluding the effects of vegetation, pedestrian traffic, vehicles, and surrounding buildings on the wind conditions at the study site. Future research should integrate these additional factors to provide a more comprehensive understanding of the wind environment in urban residential areas.

With the advancement of computational sciences, simulating natural environments has become increasingly efficient and precise. In the context of accelerated urbanization in China, the integration of Computational Fluid Dynamics (CFD) technology for wind environment simulations provides a valuable tool to address wind-related challenges specific to urban areas. By employing the controlled variables method, simulations can be conducted to identify underlying patterns and propose optimal design strategies. This approach enables the enhancement of residential comfort through the optimization of spatial layouts and architectural forms. The “simulation-design” feedback loop offers a promising mechanism to improve ventilation quality in high-rise residential buildings, contributing to the creation of more favorable urban microclimates.

Author Contributions

H.F. analyzed the data and wrote the paper; X.J. (Jijun Lu) and Z.D. participated in the revision of the paper; J.W. and J.L. (Jiajun Li) designed the research framework and analyzed the data; M.Y. and J.L. participated in the revision of the paper. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the study on the optimal design of a village external environment in a cold area of Jiangsu Province based on physical performance analysis, grant number SJXTBZ2101, and the National Key Research and Development Program of China, grant number 2018YFD1100203.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data used to support the study can be obtained from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Arcadia Simulation Model.

Figure 2. Grid division of the Arcadia computational domain.

Figure 4. (a) Summer wind speed cloud at 1.5 m height; (b,c) Wind pressure distribution at profile A; (d,e) Wind pressure distribution at profile B; (f,g) Wind pressure distribution at profile C.

Figure 5. (a) Wind speed cloud at 1.5 m height in winter; (b,c) Wind pressure distribution at profile A; (d,e) Wind pressure distribution at profile B; (f,g) Wind pressure distribution at profile C.

Figure 6. (a) Wind speed map when the building height is 30 m; (b) Wind speed map when the building height is 36 m; (c) Wind speed map when the building height is 42 m; (d) Wind speed map when the building height is 48 m; (e) Wind speed map when the building height is 54 m; (f) Wind speed map when the building height is 60 m.

Figure 7. (a) Wind speed map for building width is 24 m; (b) Wind speed map for building width is 36 m; (c) Wind speed map for building width is 48 m; (d) Wind speed map for building width is 60 m; (e) Wind speed map for building width is 72 m; (f) Wind speed map for building width is 84 m.

Figure 8. (a–g) Wind speed clouds at angles of 0°, 15°, 30°, 45°, 60°, 75°, and 90° between building average and incoming wind direction; (h) Schematic diagram of angles between building average and wind direction.

Figure 9. (a–g) Wind pressure distribution on the front and rear elevations of the building when the wind angle θ = 0°, 15°, 30°, 45°, 60°, 75°, 90°; (h) Legend of Wind Pressure Distribution.

Figure 10. (a,b) Wind pressure cloud diagrams and wind speed vectors at 78 m between the front and rear buildings; (c,d) Wind pressure cloud diagrams and wind speed vectors at 88 m between the front and rear buildings; (e,f) Wind pressure cloud diagrams and wind speed vectors at 98 m between the front and rear buildings; (g,h) Wind pressure cloud diagrams and wind speed vectors at 108 m between the front and rear buildings.

Figure 11. (a) Wind speed amplification coefficient at 1.5 m height when the spacing between walls is 15 m; (b) Wind speed amplification coefficient at 1.5 m height when the spacing between walls is 20 m; (c) Wind speed amplification coefficient at 1.5 m height when the spacing between walls is 25 m; (d) Wind speed amplification coefficient at 1.5 m height when the spacing between walls is 30 m; (e) Wind speed amplification coefficient at 1.5 m height when the spacing between walls is 35 m; (f) Wind speed amplification coefficient at 1.5 m height when the spacing between walls is 40 m.

Figure 12. (a,b) Parallel 1.5 m high wind speed and 10 m high wind pressure clouds in summer; (c,d) Center-vacant 1.5 m high wind speed and 10 m high wind pressure clouds in summer; (e,f) Parallel staggered (left) 1.5 m high wind speed and 10 m high wind pressure clouds in summer; (g,h) Parallel staggered (right) 1.5 m high wind speed and 10 m high wind pressure clouds in summer; (i,j) Staggered 1.5 m high wind speed and 10 m high wind pressure maps in summer.

Figure 13. (a,b) Parallel 1.5 m high wind speed and 10 m high wind pressure clouds in winter; (c,d) Center-vacant 1.5 m high wind speed and 10 m high wind pressure clouds in winter; (e,f) Parallel staggered (left) 1.5 m high wind speed and 10 m high wind pressure clouds in winter; (g,h) Parallel staggered (right) 1.5 m high wind speed and 10 m high wind pressure clouds in winter; (i,j) Staggered 1.5 m high wind speed and 10 m high wind pressure maps in winter.

Figure 14. (a) Initial Building Layout of Arcadia Subdivision; (b) Optimized Building Layout of Arcadia Subdivision.

Figure 15. (a) Wind speed map at 1.5 m height in summer before optimization; (b) Wind speed map at 1.5 m height in summer after optimization; (c) Wind pressure map at 10 m height in summer before optimization; (d) Wind pressure map at 10 m height in summer after optimization; (e) Wind speed map at 1.5 m height in winter before optimization; (f) Wind speed map at 1.5 m height in winter after optimization; (g) Wind pressure map at 10 m height in winter after optimization; (h) Wind pressure map at 10 m height in winter after optimization.

Table 1. Survey Summary of 11 High-Rise Residential Communities.

Name	Built	Oriented	Building Floor					Building Width
			10–14	15–18	20–24	25–29	≥30	20–29 m	30–39 m	40–49 m	50–59 m	≥60 m
Lakeside Garden	2004	South Southeast	7	14	5	-	2	2	11	-	12	3
Arcadia	2008	South Southwest	2	6	-	-	2	-	-	1	-	9
Greenland Century City	2008	South	17	33	3	-	-	8	3	21	9	12
Bashan Xinyuan	2009	South	15	9	-	-	-	10	12	2	-	-
China Railway Future City	2011	South Southeast	17	9	-	-	-	1	2	17	0	6
GuojichengbangPhase II	2012	Southwest	6	10	-	-	-	-	-	2	8	6
Shimao Dongdu	2013	South Southeast Southwest	-	2	11	-	-	-	2	4	-	7
Zijindong CountyPhase II	2013	South	5	10	-	-	-	-	-	2	11	2
Yunlong Huafu	2015	South Southeast	1	6	7	-	-	1	3	2	8
Peace east	2016	South	-	11	2	3	-	2	11	-	2	1
Green landPeace nickname	2016	South Southeast	-	14	7	-	-		7	10	4
Total (Building)			70	124	35	3	4	24	51	61	54	46

Table 2. Ground roughness index values for different terrain types [35].

Ground Type	Applicable Area	Roughness Index Value	Gradient Wind Height (m)
A	Offshore areas, lakeshore, and desert areas	0.12	300
B	Fields, hills, small and medium-sized cities, and suburbs of large cities	0.15	350
C	Large urban areas with dense buildings	0.22	450
D	Urban areas with dense clusters of buildings and taller houses	0.30	550

Table 3. Standard for evaluation of outdoor wind environment for residential buildings.

Season	Wind Speed	Wind Vortex	Wind Speed Amplification	Wind Pressure
Summer	1 m/s ≤ V ≤ 5 m/s	Avoid	<2	75% of buildings have a wind pressure difference greater than 1.5 Pa before and after
Winter	V ≤ 5 m/s	Avoid	<2	The wind pressure difference before and after the building is less than 5 Pa

Table 4. Differential pressure before and after summer construction in Arcadia.

		South Wind Pressure (Pa)	North Wind Pressure (Pa)	Wind Pressure Difference (Pa)
A-A section	8#	−3	−1.8	1.2
	5#	−3.5	−0.8	2.7
	0#	−4.7	−6	1.3
B-B section	9#	−3.4	−2.2	1.2
	6#	−0.9	0.4	1.3
	3#	0.5	−0.9	1.4
	1#	−0.2	0.3	0.5
C-C section	11#	−3.8	−2.6	1.2
	7#	−0.6	−1.1	0.5
	4#	−1.5	−2.4	0.9
	2#	−3.5	−3.7	0.2

Table 5. Differential pressure before and after buildings in winter in Arcadia.

		South Wind Pressure (Pa)	North Wind Pressure (Pa)	Wind Pressure Difference (Pa)
A-A section	8#	−1.9	−0.1	1.8
	5#	−1.1	−1.2	0.1
	0#	−3.4	−0.3	3.1
B-B section	9#	−3.3	−1	4.3
	6#	−1.1	0.2	1.3
	3#	0.6	0.3	0.3
	1#	0.2	1.9	1.7
C-C section	11#	−3.2	−0.5	2.7
	7#	−3.1	−1.8	1.3
	4#	−4.5	−0.3	4.2
	2#	−3.7	4.2	7.9

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Fang, H.; Ji, X.; Wang, J.; Lu, J.; Yang, M.; Li, J.; Duan, Z. Numerical Simulation and Optimization of Outdoor Wind Environment in High-Rise Buildings Zone of Xuzhou City. Buildings 2025, 15, 264. https://doi.org/10.3390/buildings15020264

AMA Style

Fang H, Ji X, Wang J, Lu J, Yang M, Li J, Duan Z. Numerical Simulation and Optimization of Outdoor Wind Environment in High-Rise Buildings Zone of Xuzhou City. Buildings. 2025; 15(2):264. https://doi.org/10.3390/buildings15020264

Chicago/Turabian Style

Fang, Huanhuan, Xiang Ji, Jiuxin Wang, Jijun Lu, Mengcheng Yang, Jiajun Li, and Zhongcheng Duan. 2025. "Numerical Simulation and Optimization of Outdoor Wind Environment in High-Rise Buildings Zone of Xuzhou City" Buildings 15, no. 2: 264. https://doi.org/10.3390/buildings15020264

APA Style

Fang, H., Ji, X., Wang, J., Lu, J., Yang, M., Li, J., & Duan, Z. (2025). Numerical Simulation and Optimization of Outdoor Wind Environment in High-Rise Buildings Zone of Xuzhou City. Buildings, 15(2), 264. https://doi.org/10.3390/buildings15020264

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