An Investigation into the Distribution of Fluctuating Wind Pressure and Associated Probabilistic Characteristics of Low-Rise Buildings Impacted by the Gap between the Hillside and the Building
Abstract
:1. Introduction
2. Wind Tunnel Test Experiments
2.1. Full-Sized Physical Model
2.2. Experimental Operating Conditions
2.3. Testing the Simulation of Wind Patterns
2.3.1. Wind Profile of the Test Wind Farm
2.3.2. Turbulence Profile of Experimental Wind Field
2.4. Method of Analyzing Data
Mean Wind Pressure Coefficient
3. Fluctuating Wind Pressure’s Interference Effect
4. Examining the Fluctuating Coefficient under Different Wind Angles
5. Comparative Analysis of the Power Spectrum
6. Analysis of the Probability Law of Fluctuating Wind Pressure in Low-Rise Buildings
7. Analysis of Flow Field around Low-Rise Buildings Based on Numerical Simulation
7.1. Modeling and Solving Process
7.1.1. Determine the Calculation Basin
7.1.2. Grid Division
7.1.3. Setting of Boundary Conditions
- (1)
- Inlet boundary conditions
- (2)
- Outlet boundary condition: The free outflow boundary is selected, and the velocity gradient is 0 along the normal direction of the outlet boundary;
- (3)
- On the top and both sides of the basin: Symmetry boundary conditions are selected, which are equivalent to the free slip wall in viscous flow;
- (4)
- Building surface and ground: A no-slip wall condition is selected.
7.1.4. Turbulence Model Selection and Wall Treatment Method
7.1.5. Solution Method and Convergence Control
- (1)
- Selection of solution method
- (2)
- Convergence control
- (3)
- Setting of time step
7.2. Comparison between Wind Tunnel Test and Numerical Simulation
- (1)
- For the wind pressure distribution of the back wind surface of low-rise buildings, the numerical simulation results are different from the corresponding wind tunnel test results. This is mainly due to the influence of the tail flow on the wind pressure distribution on the back wind surface, and at the same time, because the geometric scale model is used in the test, it is impossible to fully reflect the response of the structure under the detailed wind load, so the average wind pressure coefficient is different from that obtained by the wind tunnel experiment and the numerical simulation.
- (2)
- For the wind pressure distribution on the side of the building, there is a certain trend of the average wind pressure coefficient due to the disturbance of the hillside and the generation of a vortex.
- (3)
- For the roof, the numerical simulation results are quite different from the corresponding wind tunnel test results, both with the distribution law and with the numerical value. The main manifestation is that the numerical simulation results do not show the effect of the separation of air flow at the roof ridge on the local wind pressure coefficient of the roof. For example, when there is no peripheral working condition, the air flow separates at the roof ridge of the windward roof, and the local wind pressure increases rapidly, forming a high negative pressure area. The wind tunnel test results describe this phenomenon well, but the numerical simulation results do not show this phenomenon. The main reason is that the turbulent flow predicted by the standard turbulent model using the separation zone of the top of the passive body is higher than that predicted by the high ground, and the turbulent kinetic energy generation term of the top of the passive body impacting the wind surface is higher than that estimated by the standard turbulent model, which leads to the inaccurate pressure distribution of the top wall of the building. Further improvement may be needed in specific applications.
7.3. Numerical Simulation Analysis of Distance Change between House and Hillside
8. Conclusions
- As the distance between the slope and the mountain increases, the fluctuating wind pressure coefficient continues to increase, and the contour lines of the wind pressure distribution are relatively denser compared to where there is a mountain. The maximum value of the fluctuating wind pressure coefficient is 0.22, which appears at the windward roof. The wind pressure coefficient on the building surface varies in a specific manner as the distance between the hillside and the building grows. The fluctuating coefficient on the windward side decreases first and then increases. The fluctuating coefficient on the left and right sides increases gradually. At infinity, the value decreases when there is no influence from the surrounding environment. The fluctuating coefficient of the roof increases gradually and reaches the maximum when there is no influence from the surrounding environment.
- Due to the existence of the mountain, the energy of the low-frequency band is weakened, and the energy of the high-frequency band is enhanced. This is mainly due to the suppression of the spatial large-scale vortex structure by the mountain, resulting in the weakening of the turbulence characteristics of the incoming wind and the increase in the small-scale vortex. With the increasing distance between the hillside and the building, the energy in the low-frequency band at the windward eaves decreases, and the energy in the high-frequency band increases gradually.
- The variation in the probability distribution of wind pressure at the middle measuring points in different regions under 0° wind direction was analyzed, and it was found that with the increase in the relative position between the hillside and the building, the probability distribution has Gaussian characteristics when the leeward side has no periphery under the three working conditions. In the middle of windward and leeward eaves, the distribution characteristics gradually changed from non-Gaussian characteristics to Gaussian characteristics.
- Due to the presence of the mountain, the airflow forms a vortex between the hillside and the low-rise building, thereby changing the flow field distribution of the low-rise building, especially the wind pressure distribution on the leeward side. As the relative position between the slope and the building increases, the influence of the vortex formed on the surface of low-rise buildings gradually weakens. Overall, the impact of the rear slope on the windward wall of the house is not significant. For other building surfaces, when the distance between the slope and the house is within a determinate range, as the distance between the slope and the house increases, the impact of the slope on the wind load on each surface of the low-rise building becomes smaller. When the distance between the slope and the house reaches a determinate value, the impact of the hillside can be ignored.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Model size | Length of the model | 187.5 mm |
Width of the model | 111.25 mm | |
Slope of the roof | 18.6° | |
Relative position of the mountain | Distance | 34.15 mm (S/H = 0.2) 68.30 mm (S/H = 0.4) 170.75 mm (S/H = 1.0) |
Mountain height Hm | 34.15 mm (Hm/H = 2) | |
Slope of the mountain, β | 60° | |
Terrain roughness, z0 | 0.12 | |
Sampling frequency of the wind pressure | 312.5 Hz | |
Tunnel velocity | 12 m/s | |
Geometric scale ratio | 1:40 |
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Zhong, M.; Wang, C.; Lin, M.; Lu, J.; Wang, X. An Investigation into the Distribution of Fluctuating Wind Pressure and Associated Probabilistic Characteristics of Low-Rise Buildings Impacted by the Gap between the Hillside and the Building. Buildings 2024, 14, 1435. https://doi.org/10.3390/buildings14051435
Zhong M, Wang C, Lin M, Lu J, Wang X. An Investigation into the Distribution of Fluctuating Wind Pressure and Associated Probabilistic Characteristics of Low-Rise Buildings Impacted by the Gap between the Hillside and the Building. Buildings. 2024; 14(5):1435. https://doi.org/10.3390/buildings14051435
Chicago/Turabian StyleZhong, Min, Chao Wang, Minghui Lin, Junyu Lu, and Xiangjun Wang. 2024. "An Investigation into the Distribution of Fluctuating Wind Pressure and Associated Probabilistic Characteristics of Low-Rise Buildings Impacted by the Gap between the Hillside and the Building" Buildings 14, no. 5: 1435. https://doi.org/10.3390/buildings14051435