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

Author:

Zhong Min12,Wang Chao2,Lin Minghui3,Lu Junyu3,Wang Xiangjun4

Affiliation:

1. School of Architecture and Engineering, Jiangsu Open University, Nanjing 210036, China

2. College of Civil Engineering, Hunan University, Changsha 410082, China

3. College of Civil Engineering, Hebei University of Architecture, Zhangjiakou 075000, China

4. College of Electrical Energy and Power Engineering, Yangzhou University, Yangzhou 225127, China

Abstract

In China’s mountainous coastal terrain, storms can badly damage low-rise buildings. At present, it is not clear how the relative position of buildings and mountains affects the surface of low-rise buildings. The study compared these results with the wind pressure distribution without the surrounding environment. The distribution of wind pressure in different hillside landforms is examined through a wind tunnel experiment, which is also compared with the distribution in an open environment. The study examined the fluctuating coefficient as the distance between the building and the hillside changed, specifically for wind blowing at a 0° angle. The investigation examined the power spectrum and wind pressure probability distribution while considering the proximity of the building to an adjacent hill. The findings indicated that 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 roof’s wind pressure coefficient fluctuated and gradually increased until it reached its peak, unaffected by the surroundings. The wind pressure on the leeward side exhibited Gaussian characteristics in its probability distribution.

Funder

Science Research Project of the Hebei Education Department

National Natural Science Foundation of China

Publisher

MDPI AG

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