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Non‑Gaussian Probability Distribution Characteristics and Extreme Wind Pressure on Long‑Span Roofs
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Jingkai XIE1, Xiongwei YANG2, Mingshui LI3, 4, Shubi DU3, 4
Journal of Vibration,Measurement and Diagnosis | 2025, 45(5) : 1019 - 1027
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Journal of Vibration,Measurement and Diagnosis | 2025, 45(5): 1019-1027
• PAPER •
Non‑Gaussian Probability Distribution Characteristics and Extreme Wind Pressure on Long‑Span Roofs
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Jingkai XIE1, Xiongwei YANG2, Mingshui LI3, 4, Shubi DU3, 4
Affiliations
  • 1.Guangzhou Metro Design & Research Institute Co.，Ltd.　Guangzhou，510010，China
  • 2.School of Urban Geology and Engineering，Hebei GEO University　Shijiazhuang，050031，China
  • 3.Research Center for Wind Engineering，Southwest Jiaotong University　Chengdu，610031，China
  • 4.Wind Engineering Key Laboratory of Sichuan Province　Chengdu，611756，China
Published: 2025-10-01 doi: 10.16450/j.cnki.issn.1004-6801.2025.05.022
Outline
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Wind tunnel pressure tests are conducted on a high-speed railway station roof to study the non-Gaussian characteristics and extreme wind pressure distribution on the long-span roof surface. First，the surface wind pressure is classified into Gaussian and non-Gaussian distributions. Then，the fitting effects of three different single probability distributions （Gumbel，Lognormal，and Weibull） and their corresponding combined distributions （double Gumbel，double Lognormal，and double Weibull） on the wind pressure time history of the roof surface are compared. The extreme wind pressures obtained from the combined probability distributions are compared with the estimates from the modified Hermite method. Finally，the extreme wind pressure distribution on the roof under all wind directions is presented. The results show that the combined probability distributions provide a better fit to the wind pressure time history than the single distributions. The extreme value estimates from each combined distribution at the same guarantee rate are more accurate than those from the single distribution. The combined distributions generally yield better estimates at the 99.90% guarantee rate compared to the modified Hermite method. The extreme wind pressure varies significantly with the wind direction，and under all wind directions，the minimum pressure coefficient reaches its lowest value at the middle of the roof edge side，reaching -5.9.

long-span roof  /  non-Gaussian characteristics  /  extreme wind pressure  /  combined probability distribution  /  extreme value estimation method
Jingkai XIE, Xiongwei YANG, Mingshui LI, Shubi DU. Non‑Gaussian Probability Distribution Characteristics and Extreme Wind Pressure on Long‑Span Roofs[J]. Journal of Vibration,Measurement and Diagnosis, 2025 , 45 (5) : 1019 -1027 . DOI: 10.16450/j.cnki.issn.1004-6801.2025.05.022
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Year 2025 volume 45 Issue 5
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Article Info
doi: 10.16450/j.cnki.issn.1004-6801.2025.05.022
  • Receive Date：2023-02-08
  • Online Date：2026-03-27
  • Published：2025-10-01
Article Data
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History
  • Received：2023-02-08
  • Revised：2023-06-10
Funding
Affiliations
    1.Guangzhou Metro Design & Research Institute Co.，Ltd.　Guangzhou，510010，China
    2.School of Urban Geology and Engineering，Hebei GEO University　Shijiazhuang，050031，China
    3.Research Center for Wind Engineering，Southwest Jiaotong University　Chengdu，610031，China
    4.Wind Engineering Key Laboratory of Sichuan Province　Chengdu，611756，China
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表12种不同金属材料的力学参数
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Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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