Peak Factors for Non-Gaussian Load Effects Revisited

被引:158
|
作者
Kwon, Dae Kun [1 ]
Kareem, Ahsan [1 ]
机构
[1] Univ Notre Dame, Dept Civil Engn & Geol Sci, Notre Dame, IN 46556 USA
关键词
Peak factor; Non-Gaussian process; Wind pressure; Buildings; Low-rise; Wind loads; Probability density functions; Structural response; Structural safety; MATHEMATICAL-ANALYSIS; WIND; MODELS;
D O I
10.1061/(ASCE)ST.1943-541X.0000412
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The estimation of the extreme of non-Gaussian load effects for design applications has often been treated tacitly by invoking a conventional peak factor on the basis of Gaussian processes. This assumption breaks down when the loading process exhibits non-Gaussianity, in which a conventional peak factor yields relatively nonconservative estimates because of failure to include long tail regions inherent to non-Gaussian processes. To realistically capture the salient characteristics of non-Gaussian load effects and incorporate these in the estimates of their extremes, this study examines the peak factor for non-Gaussian processes, which can be used for estimating the expected value of the positive and negative extremes of non-Gaussian load effects. The efficacy of previously introduced analytical expressions for the peak factor of non-Gaussian processes on the basis of a moment-based Hermite model is evaluated and the variance of the estimates in standard deviation is derived. In addition, some improvements to the estimation of the peak factor and its standard deviation are discussed. Examples, including immediate applications to other areas, illustrate the effectiveness of this model-based peak factor approach. DOI: 10.1061/(ASCE)ST.1943-541X.0000412. (C) 2011 American Society of Civil Engineers.
引用
收藏
页码:1611 / 1619
页数:9
相关论文
共 50 条
  • [21] Peak factor estimation methods of non-gaussian wind pressures on a rectangular high-rise building
    Zhuang X.
    Dong X.
    Zheng Y.-M.
    Zhao X.
    Dong, Xin (dongxinseu@163.com), 1600, Tsinghua University (34): : 177 - 185and223
  • [22] Peak factor estimation of non-Gaussian wind pressures based on a novel piecewise Johnson transformation model
    Zhang, Haicheng
    Zhou, Qiang
    Li, Ming
    Li, Mingshui
    Xie, Jingkai
    JOURNAL OF BUILDING ENGINEERING, 2023, 78
  • [23] Estimation of Peak Factor of Non-Gaussian Wind Pressures by Improved Moment-Based Hermite Model
    Liu, Min
    Chen, Xinzhong
    Yang, Qingshan
    JOURNAL OF ENGINEERING MECHANICS, 2017, 143 (07)
  • [24] Closed-form solution of the peak factor of hardening non-Gaussian cross-wind response with limited time history samples
    Huang, Shuai
    Yang, Qingshan
    Guo, Kunpeng
    Qian, Zheng
    JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2024, 252
  • [25] An Analytic Approach to Probabilistic Load Flow Incorporating Correlation Between Non-Gaussian Random Variables
    Huang, Yu
    Xu, Qingshan
    Jiang, Xianqiang
    Yang, Yang
    Lin, Guang
    ELEKTRONIKA IR ELEKTROTECHNIKA, 2018, 24 (03) : 61 - 67
  • [26] Finite dimensional models for extremes of Gaussian and non-Gaussian processes
    Xu, Hui
    Grigoriu, Mircea D.
    PROBABILISTIC ENGINEERING MECHANICS, 2022, 68
  • [27] Spatial Prediction for Multivariate Non-Gaussian Data
    Liu, Xutong
    Chen, Feng
    Lu, Yen-Cheng
    Lu, Chang-Tien
    ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA, 2017, 11 (03)
  • [28] Statistics of Fourier modes in non-Gaussian fields
    Matsubara, Takahiko
    ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES, 2007, 170 (01) : 1 - 32
  • [29] Non-Gaussian diffusion in static disordered media
    Luo, Liang
    Yi, Ming
    PHYSICAL REVIEW E, 2018, 97 (04)
  • [30] Non-Gaussian Methods for Causal Structure Learning
    Shimizu, Shohei
    PREVENTION SCIENCE, 2019, 20 (03) : 431 - 441