Fig 1.
Research framework.
Fig 2.
Annual wind direction and velocity analysis program.
Table 1.
Results of wind direction and wind velocity analysis within the baseThis study focuses on the Tanji Dormitory District at the junction of Industrial East Street and Shengli North Road in Qiaodong District, Zhangjiakou City, as shown in Fig 3. The area contains eight existing six-storey residential buildings, each with a height of 24 m, arranged in a row-type layout. A narrow tube-like space is formed between the buildings, and when the dominant monsoon wind flows through this gap, the local wind velocity increases dramatically due to the Venturi Effect [37]. Prolonged exposure to strong winds can cause discomfort such as breathlessness, headaches, and joint pain, which greatly inconveniences residents’ movement and outdoor activities.
Fig 3.
Study of the current state of the buildings and environment within the site.
Fig 4.
Portable weather station.
Fig 5.
Measurement points in the TanJi Dormitory Community.
Fig 6.
Procedures for regional wind environment analysis.
Fig 7.
Calculation of the simulation area.
Table 2.
Details of grid division for simulation schemes.
Fig 8.
Grid convergence plot.
Table 3.
Grid convergence evaluation indicators.
Table 4.
Wind environment evaluation indicators.
Table 5.
Input conditions calculated with Rayman.
Fig 9.
Calculation of human thermal sensation and wind velocity in Rayman.
Table 6.
Percentage of wind velocity in May.
Table 7.
Percentage of wind conditions in May.
Table 8.
Result of grid convergence.
Fig 10.
Comparison of wind velocity and direction between experiment and simulation.
Table 9.
Comparison of wind velocity between experiment and simulation.
Fig 11.
Initial computational modeling and and simulation results.
Table 10.
Analysis of indicators for evaluating the simulation results in the horizontal direction of the initial model of the community.
Fig 12.
Horizontal wall modules scheme and simulation results.
Fig 13.
Comparison of horizontal wind comfort zones for wall models.
Table 11.
Analysis of evaluation indicators for horizontally oriented wall module programs.
Fig 14.
Vertical wall modules scheme and simulation results.
Fig 15.
Comparison of Vertical wind comfort zones for wall models.
Fig 16.
Horizontal enclosed spatial modules scheme and simulation results.
Table 12.
Analysis of evaluation indicators for horizontally oriented enclosed spatial modules programs.
Fig 17.
Comparison of horizontal wind comfort zones for enclosed spatial modules.
Fig 18.
Horizontal vegetated landscape modules scheme and simulation results.
Fig 19.
Comparison of horizontal wind comfort zones for vegetated landscape modules.
Table 13.
Analysis of evaluation indicators for horizontally oriented vegetated landscape modules programs.
Fig 20.
Vertical vegetated landscape modules scheme and simulation results.
Fig 21.
Comparison of vertical wind comfort zones for vegetated landscape modules.
Fig 22.
Community transformation program model and simulation results.
Table 14.
Analysis of indicators for evaluating the wind environment in a modified communityTo assess the effectiveness of the design under varying wind velocities in the study area, the standard deviation of the prevailing wind velocity in May was calculated as σ = 3.17. Comparative analyses of the design performance were conducted under wind velocity fluctuations of ±0.5σ, ± 1σ, ± 1.5σ, and ±2σ, respectively. The results are shown inTable 15.
Table 15.
Analysis of indicators for evaluating the wind environment in a modified community.