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Wu Chunbing, Wang Jingxue, Ji Xiaodong, Jiang Qian, He Jianjun, Liang Yushi. Spatial and temporal statistical characteristics of air density and its influence on basic wind pressure: a case study of Shandong Province, eastern China[J]. Journal of Beijing Forestry University, 2021, 43(5): 99-107. DOI: 10.12171/j.1000-1522.20210064
Citation: Wu Chunbing, Wang Jingxue, Ji Xiaodong, Jiang Qian, He Jianjun, Liang Yushi. Spatial and temporal statistical characteristics of air density and its influence on basic wind pressure: a case study of Shandong Province, eastern China[J]. Journal of Beijing Forestry University, 2021, 43(5): 99-107. DOI: 10.12171/j.1000-1522.20210064

Spatial and temporal statistical characteristics of air density and its influence on basic wind pressure: a case study of Shandong Province, eastern China

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  • Received Date: February 22, 2021
  • Revised Date: April 07, 2021
  • Available Online: May 10, 2021
  • Published Date: May 26, 2021
  •   Objective  The determination of basic wind pressure is particularly important for evaluating the design value of wind load of resistance structures. Air density is one of the basic parameters for calculating basic wind pressure, and its value is affected by geomorphology and climate type. Therefore, it is of great significance for wind load assessment to study the spatio-temporal statistical characteristics of air density and its influence on basic wind pressure.
      Method  In this paper, based on the air temperature, air pressure and wind speed data of 123 meteorological stations in Shandong Province of eastern China from 2005 to 2017, the probability distribution characteristics of air density and its variation with cold and warm season and spatial distribution were calculated and analyzed. Combined with the design wind speed obtained from the statistical analysis of Gumbel distribution, the influence of air density on the basic wind pressure was discussed.
      Result  (1) The probability density function of air density in the whole season was bimodal. After distinguishing the cold and warm seasons, the fitting accuracy of the probability density function was improved with the probability density functions of Gamma, Weibull, Burr and GEV. The air density distribution functions of cold and warm seasons fit well with Weibull and Burr functions, respectively. (2) The air density decreasesd from the coast to the inland, and decreased with the increase of altitude. (3) In the low altitude plain areas, the wind pressure calculated by the average air density in the cold season was almost the same as that calculated by the fixed air density 1.25 kg/m3 and considering the effect of altitude on the air density, while in the high altitude area, the wind pressure calculated by the fixed air density of 1.25 kg/m3 was on the high side. (4) For the low altitude plain area of Shandong Province, the basic wind pressure calculated by selecting the extreme air density was about 10%−14% higher than that calculated by the fixed air density of 1.25 kg/m3 and considering the effect of altitude on the air density.
      Conclusion  In this study, through the statistics of space-time characteristics of air density and combined with the extreme wind speed, the influence of different air density on the basic wind pressure was discussed, which provides an important reference for the selection of air density in structural design.
  • [1]
    吴凤波, 冀骁文, 黄国庆, 等. 基于简化渐进破坏的低矮房屋围护结构风致易损性分析[J]. 建筑结构学报, 2021, 42(5):32−39.

    Wu F B, Ji X W, Huang G Q, et al. Wind-induced fragility analysis of low-rise building envelope based on simplified progressive damage[J]. Journal of Building Structures, 2021, 42(5): 32−39.
    [2]
    Yang Q S, Gao R, Bai F, et al. Damage to buildings and structures due to recent devastating wind hazards in East Asia[J]. Natural Hazards, 2018, 92(3): 1321−1353. doi: 10.1007/s11069-018-3253-8
    [3]
    中国工程建设标准化协会. 建筑结构荷载规范: GB 50009—2012[S]. 北京: 中国建筑工业出版社, 2012.

    China Association for Engineering Construction Standardization. Load code for the design of building structures: GB 50009−2012[S]. Beijing: China Architecture & Building Press, 2012.
    [4]
    Tosunoğlu F. Accurate estimation of T year extreme wind speeds by considering different model selection criterions and different parameter estimation methods[J]. Energy, 2018, 162: 813−824. doi: 10.1016/j.energy.2018.08.074
    [5]
    林立, 陈政清, 洪华生, 等. 基于广义统一概率图的东南沿海风速概率分布研究[J]. 湖南大学学报(自然科学版), 2019, 46(11):181−188.

    Lin L, Chen Z Q, Hong H S, et al. Analysis of wind speed distribution probability in southeastern coastal of China based on generalized unified probability plot[J]. Journal of Hunan University (Natural Sciences), 2019, 46(11): 181−188.
    [6]
    Jung C, Schindler D. Global comparison of the goodness-of-fit of wind speed distributions[J]. Energy Conversion & Management, 2017, 133: 216−234.
    [7]
    王庆, 马倩倩, 夏艳玲, 等. 最近50年来山东地区夏季降水的时空变化及其影响因素研究[J]. 地理科学, 2014, 34(2):220−228.

    Wang Q, Ma Q Q, Xia Y L, et al. Spatial-temporal variations and influential factors of summer precipitation in Shandong region during the last 50 years[J]. Scientia Geographica Sinica, 2014, 34(2): 220−228.
    [8]
    Jung C, Schindler D. The role of air density in wind energy assessment: a case study from Germany[J]. Energy, 2019, 171: 385−392. doi: 10.1016/j.energy.2019.01.041
    [9]
    Liang Y S, Ji X D, Wu C B, et al. Estimation of the influences of air density on wind energy assessment: a case study from China[J/OL]. Energy Conversion and Management, 2020, 224: 113371 [2020−09−10]. https://doi.org/10.1016/j.enconman.2020.113371.
    [10]
    He Y C, Lin H B, Fu J Y, et al. Dependence of wind load on air density for highrise buildings[J/OL]. Journal of Wind Engineering and Industrial Aerodynamics, 2021, 211: 104558 [2021−02−23]. https://doi.org/10.1016/j.jweia.2021.104558.
    [11]
    Stull R B. Meteorology for scientists and engineers [M]. 2nd ed. Pacific Grove: Brooks/Cole, 2000.
    [12]
    Manwell J F, Mcgowan J G, Rogers A L. Wind energy explained: theory, design and application[M]. Chichester: John Wiley & Sons, 2009.
    [13]
    Fisher R A. On the mathematical foundations of theoretical statistics[J]. Philosophical Transactions of the Royal Society A, 1922, 222(1): 309−368.
    [14]
    Jung C, Schindler D, Laible J, et al. Introducing a system of wind speed distributions for modeling properties of wind speed regimes around the world[J]. Energy Conversion & Management, 2017, 144: 181−192.
    [15]
    Kang D, Ko K, Huh J. Determination of extreme wind values using the Gumbel distribution[J]. Energy, 2015, 86: 51−58. doi: 10.1016/j.energy.2015.03.126
    [16]
    Feng S, Wang Y, Xie Z. Estimating extreme wind pressure for long-span roofs: sample independence considerations[J/OL]. Journal of Wind Engineering and Industrial Aerodynamics, 2020, 205: 104341 [2020−08−31]. https://doi.org/10.1016/j.jweia.2020.104341.
    [17]
    Lu D, Song L, Yu Y. New sequences with continued fraction towards Euler’s constant[J]. Applied Mathematics & Computation, 2015, 259: 12−20.
    [18]
    罗颖. 极值理论及其在结构风荷载和响应上的应用[D]. 成都: 西南交通大学, 2018.

    Luo Y. Extreme value theory and its application on wind load and response of structure[D]. Chengdu: Southwest Jiaotong University, 2018.
    [19]
    李裕奇, 刘海燕, 赵联文. 非参数统计方法[M]. 成都: 西南交通大学出版社, 2010.

    Li Y Q, Liu H Y, Zhao L W. Non-parametric statistical methods[M]. Chengdu: Southwest Jiaotong University Press, 2010.
    [20]
    Zha J L, Wu J, Zhao D, et al. Changes of the probabilities in different ranges of near-surface wind speed in China during the period for 1970–2011[J]. Journal of Wind Engineering & Industrial Aerodynamics, 2017, 169: 156−167.
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