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空气密度时空统计特性及对基本风压的影响

吴春冰 王京学 冀晓东 姜谦 何建军 梁羽石

吴春冰, 王京学, 冀晓东, 姜谦, 何建军, 梁羽石. 空气密度时空统计特性及对基本风压的影响——以山东省为例[J]. 北京林业大学学报, 2021, 43(5): 99-107. doi: 10.12171/j.1000-1522.20210064
引用本文: 吴春冰, 王京学, 冀晓东, 姜谦, 何建军, 梁羽石. 空气密度时空统计特性及对基本风压的影响——以山东省为例[J]. 北京林业大学学报, 2021, 43(5): 99-107. doi: 10.12171/j.1000-1522.20210064
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

空气密度时空统计特性及对基本风压的影响

——以山东省为例

doi: 10.12171/j.1000-1522.20210064
基金项目: 国家自然科学基金项目(31570708),国家水体污染控制与治理科技重大专项子课题二(2017ZX07101002-002)
详细信息
    作者简介:

    吴春冰。主要研究方向:结构抗风。Email:761065458@qq.com 地址:100083 北京市海淀区清华东路35号北京林业大学水土保持学院

    责任作者:

    冀晓东,教授,博士生导师。主要研究方向:结构抗风。Email:jixiaodong@bjfu.edu.cn 地址:同上

  • 中图分类号: S716;TU14

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

  • 摘要:   目的  基本风压的确定对评估结构抗风中风荷载设计值尤为重要。空气密度是计算基本风压的基本参数之一,其取值受地貌和气候类型的影响存在一定的差异性。因此,研究空气密度时空统计特性及对基本风压的影响对风荷载评估具有重要意义。  方法  该文基于山东省123个气象站2005—2017年的气温、气压和风速资料,计算并统计分析空气密度的概率分布特性、随冷暖季及空间分布变化规律,并结合由Gumbel分布统计分析得到的设计风速,探讨了空气密度对基本风压的影响。  结果  (1)全季空气密度的概率密度函数呈双峰型,区分冷暖季后与Gamma、Weibull、Burr及GEV概率密度函数拟合精度有所提升,冷、暖季空气密度分布函数分别与Weibull、Burr函数拟合较好;(2)空气密度由沿海向内陆地区逐渐减小,随海拔高度增加而减小;(3)在低海拔平原地区,冷季平均空气密度计算下的风压与固定空气密度1.25 kg/m3、考虑海拔对空气密度影响下的风压相差不大,在高海拔地区,固定空气密度1.25 kg/m3计算下的风压偏大;(4)对于山东低海拔平原地区,选取极值空气密度计算得到的基本风压较固定空气密度1.25 kg/m3、考虑海拔对空气密度影响的风压值大10% ~ 14%左右。  结论  该研究通过统计空气密度时空特性,并结合极值风速,探讨了不同空气密度对基本风压的影响,为结构设计中空气密度的选取提供重要参考。

     

  • 图  1  山东省123个气象站位置及海拔分布

    Figure  1.  Location and altitude distribution of 123 meteorological stations in Shandong Province

    图  2  青岛站空气密度概率密度函数

    冷季指12月—次年5月,暖季指6—11月。下同。The cold season is from December to May of the following year, and the warm season is from June to November. Same as below.

    Figure  2.  Probability density function of air density in Qingdao Station

    图  3  山东省123个气象站空气密度概率密度函数与理论概率密度函数拟合精度

    R2为全季决定系数,RL 2为冷季决定系数,RN 2为暖季决定系数。Q1为上四分位数,Q3为下四位数,四分位距IQR = Q3 − Q1,异常值为小于Q1 − 1.5IQR或大于Q3 + 1.5IQR。R2 is determination coefficient of whole season, RL 2 is determination coefficient of cold season, and RN 2 is determination coefficient of warm season. Q1 is the upper quartile, Q3 is the lower quartile, interquartile range IQR = Q3 − Q1, and the outlier is less than Q1 − 1.5IQR or greater than Q3 + 1.5IQR.

    Figure  3.  Fitting accuracy of air density probability density function and theoretical probability density function at 123 meteorological stations in Shandong Province

    图  4  山东省空气密度均值空间分布

         ●青岛站;■济南站;▲泰山站。●Qingdao Station;■ Jinan Station;▲Taishan Station.

    Figure  4.  Spatial distribution of mean air density in Shandong Province

    图  5  泰山站月最大风速累积概率分布函数

    Figure  5.  Cumulative probability function of monthly maximum wind speed in Taishan Station

    图  6  泰山站月最大风速概率密度函数

    Figure  6.  Probability density function of monthly maximum wind speed in Taishan Station

    图  7  不同空气密度下基本风压差值百分比空间分布

         ▲代表泰山站。▲ represents Taishan Station.

    Figure  7.  Percentage spatial distribution of basic wind pressure differences

    表  1  4种常用概率密度函数

    Table  1.   Four types of commonly used probability density functions

    名称 Name参数 Parameter概率密度函数公式 Probability density function equation
    伽马 Gamma 2 ${{f}_{\rm{G}}}\left( x;\alpha ,k \right){=}\dfrac{{{\alpha }^{k}}}{\varGamma \left( k \right)}{{x}^{k-1}}\exp \left( -\alpha x \right)$
    威布尔 Weibull 2 ${f_{\rm{W}}}\left( {x;\alpha ,k} \right){\rm{ = }}\dfrac{k}{\alpha }{\left( {\dfrac{x}{\alpha }} \right)^{k - 1}}\exp \left[ { - {{\left( {\dfrac{x}{\alpha }} \right)}^k}} \right]$
    伯尔 Burr 3 ${f_{\rm{B}}}\left( {x;\alpha ,k,h} \right){\rm{ = }}\dfrac{{hk{{\left( {\dfrac{x}{\alpha }} \right)}^{h - 1}}}}{{\alpha {{\left[ {1 + {{\left( {\dfrac{x}{\alpha }} \right)}^h}} \right]}^{k + 1}}}}$
    广义极值 Generalized extreme value (GEV) 3 ${f_{{\rm{GEV}}}}\left( {x;\alpha ,k,\mu } \right){\rm{ = }}\dfrac{1}{\alpha }{\left[ {1 - \dfrac{k}{\alpha }\left( {x - \mu } \right)} \right]^{\frac{1}{k} - 1}}\exp \left\{ { - \left[ {1 - \dfrac{k}{\alpha }{{\left( {x - \mu } \right)}^{\frac{1}{k}}}} \right]} \right\}$
    注:α为尺度参数;k为形状参数;μ为位置参数;h为第二形状参数;Γ()为伽马函数。Notes: α is scale parameter; k is shape parameter; μ is position parameter; h is second shape parameter; Γ() is Gamma function.
    下载: 导出CSV

    表  2  不同城市空气密度分布范围和均值

    Table  2.   Distribution ranges and mean values of air density in different cities

    气象站
    Meteorological
    station
    海陆位置
    Land and sea
    position
    海拔
    Altitude/m
    项目
    Item
    空气密度 Air density/(kg·m−3)
    全季
    Whole season
    冷季
    Cold season
    暖季
    Warm season
    青岛 Qingdao 沿海 Coastal area 76 分布范围 Distribution range 1.096 ~ 1.376 1.130 ~ 1.376 1.096 ~ 1.318
    均值 Mean 1.218 1.251 1.186
    济南 Jinan 内陆 Inland 51.6 分布范围 Distribution range 1.077 ~ 1.377 1.090 ~ 1.377 1.077 ~ 1.323
    均值 Mean 1.199 1.229 1.169
    泰山 Taishan 内陆 Inland 1 533.7 分布范围 Distribution range 0.962 ~ 1.189 0.965 ~ 1.189 0.962 ~ 1.148
    均值 Mean 1.048 1.070 1.026
    下载: 导出CSV

    表  3  3个典型气象站拟合检验结果及重现期为10年、50年、100年的设计风速

    Table  3.   Fitting test results and design wind speed with recurrence periods of10, 50 and 100 years at three typical meteorological stations

    气象站
    Meteorological
    station
    基于月最大风速下Gumbel分布参数
    Gumbel distribution parameters based on
    monthly maximum wind speed
    K-S检验结果
    K-S test result
    不同重现期的设计风速
    Design wind speed in different
    return period/(m·s−1)
    μα10 a50 a100 a
    青岛 Qingdao10.851.660.8418.7121.4522.61
    济南 Jinan 8.111.580.4415.5918.2019.30
    泰山 Taishan16.132.180.4726.4530.0531.58
    下载: 导出CSV

    表  4  3个典型气象站基本风压取值

    Table  4.   Basic wind pressure values of three typical meteorological stations kPa

    气象站
    Meteorological station
    WGWelWLWJW0
    青岛 Qingdao0.2880.2850.2880.3170.600
    济南 Jinan0.2070.2040.2040.2280.450
    泰山 Taishan0.5650.4840.4830.5370.850
    注:WGWelWLWJW0分别为固定空气密度下、考虑海拔影响下、冷季空气密度下、极值空气密度下、《建筑结构荷载规范》[3]中的基本风压取值。 Notes: WG, Wel, WL, WJ, W0 are the basic wind pressure under fixed air density, considering the influence of altitude, under the air density in the cold season, extreme air density, and from the Load Code for the Design of Building Structures[3], respectively.
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-02-23
  • 修回日期:  2021-04-08
  • 网络出版日期:  2021-05-14
  • 刊出日期:  2021-05-27

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