Study on the joint distribution of air temperature, solar radiation, and wind speed in the complex mountainous bridge sites based on field measurement

Abstract In complex mountainous areas with high mountains and deep valleys, bridge sites are prone to strong winds, solar exposure, abrupt air temperature changes, and other extreme natural conditions, leading to more severe and complex environmental loads on bridge structures compared to plain areas. Current design specifications do not consider solar radiation when calculating uniform temperature, and the simple superposition of extreme air temperature and wind effects leads to an overestimation of combined loads since their extreme values rarely occur simultaneously. Therefore, a comprehensive study on the joint distribution of air temperature, solar radiation, and wind in complex mountainous areas is necessary. This study uses environmental parameter data from field measurements in complex mountainous bridge sites to establish joint distribution models of air temperature, solar radiation, and wind speed based on the Copula functions. The joint distribution models are used to calculate the joint values of air temperature, solar radiation, and wind speed actions under the different return periods, which are subsequently converted to extreme temperature action values for bridge structures. A reduction coefficient of temperature action is proposed to reflect the differences in temperature action values between univariate and multivariable return periods. This research offers a practical reference for determining temperature design loads for long-span bridges in complex mountainous areas.

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Publication Details

Journal
Stochastic Environmental Research and Risk Assessment
Published
2025-10-17
DOI
https://doi.org/10.1007/s00477-025-03114-w
Citations
1
Primary Topic
Smart Materials for Construction
Type
article
Field-Weighted Citation Impact
0.50

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article

Study on the joint distribution of air temperature, solar radiation, and wind speed in the complex mountainous bridge sites based on field measurement

Jinxiang Zhang, Mingjin Zhang, Xulei Jiang, Jingxi Qin et al.
1 citations
Stochastic Environmental Research and Risk Assessment
Smart Materials for Construction
0.50
article

Study on the joint distribution of air temperature, solar radiation, and wind speed in the complex mountainous bridge sites based on field measurement

Jinxiang Zhang, Mingjin Zhang, Xulei Jiang, Jingxi Qin, Yongle Li, Jiale Long
article en
1 citations

Abstract

Abstract In complex mountainous areas with high mountains and deep valleys, bridge sites are prone to strong winds, solar exposure, abrupt air temperature changes, and other extreme natural conditions, leading to more severe and complex environmental loads on bridge structures compared to plain areas. Current design specifications do not consider solar radiation when calculating uniform temperature, and the simple superposition of extreme air temperature and wind effects leads to an overestimation of combined loads since their extreme values rarely occur simultaneously. Therefore, a comprehensive study on the joint distribution of air temperature, solar radiation, and wind in complex mountainous areas is necessary. This study uses environmental parameter data from field measurements in complex mountainous bridge sites to establish joint distribution models of air temperature, solar radiation, and wind speed based on the Copula functions. The joint distribution models are used to calculate the joint values of air temperature, solar radiation, and wind speed actions under the different return periods, which are subsequently converted to extreme temperature action values for bridge structures. A reduction coefficient of temperature action is proposed to reflect the differences in temperature action values between univariate and multivariable return periods. This research offers a practical reference for determining temperature design loads for long-span bridges in complex mountainous areas.

Stochastic Environmental Research and Risk AssessmentVol. 39(12)
Hong Kong Polytechnic University (HK), Zhejiang Institute of Communications (CN), Southwest Jiaotong University (CN)
Natural Science Foundation of Sichuan Province
Openalex Percentile: Top 33%
Smart Materials for Construction
0.50
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