Mean maximum values of non-normal distributions for different time periods

被引:0
|
作者
Ghasemi S.H. [1 ]
Nowak A.S. [2 ]
机构
[1] Department of Civil Engineering, Islamic Azad University, Qazvin Branch, Qazvin
[2] Department of Civil Engineering, Auburn University, Auburn, AL
关键词
Mean Maximum Value; Non-Normal Distribution; Probability Distribution Function; Reliability Analysis; Weigh In Motion Copyright © 2016 Inderscience Enterprises Ltd;
D O I
10.1504/IJRS.2016.078381
中图分类号
学科分类号
摘要
To perform the reliability analysis for structures, it is necessary to determine the statistical parameters of loads and resistance. However, these statistical parameters are time-dependent variables; therefore, Mean Maximum Value (MMV) should be properly deliberated. If distributions of the load and resistance behave as normal distributions, by taking advantage of normal probability paper, MMV can be estimated using extrapolation of the Cumulative Distribution Function (CDF). However, there are many phenomena in nature in which the CDFs are not normally distributed. Furthermore, the upper/bottom tails of the distributions of the load and resistance do not necessarily behave as normal distributions. Therefore, in order to determine the statistical parameters for non-normal distribution, there is a need to propose a different methodology to analytically compute MMV for non-normal distributions. The main contribution of this paper is to derive a mathematical formula for elaboration of the time-dependent MMV for non-normal distributions. Accordingly, for engineering application, this paper introduces MMV factor, fmm, which represents the required safety margin for MMV at the intended time period for load/resistance. Eventually, as a practical example standpoint in structural engineering domain, MMV and fmm for weigh in motion data are determined.
引用
收藏
页码:99 / 109
页数:10
相关论文
共 50 条
  • [21] Evaluation of normal versus non-normal grain size distributions
    Vander Voort G.F.
    Pakhomova O.
    Kazakov A.
    Materials Performance and Characterization, 2016, 5 (05)
  • [22] What's normal anyway? Normal and non-normal distributions in psychiatry
    Sara, Grant
    ACTA NEUROPSYCHIATRICA, 2010, 22 (06): : 305 - 310
  • [23] Convergence of Known Distributions to Limiting Normal or Non-normal Distributions: An Elementary Ratio Technique
    Bagui, Subhash
    Mehra, K. L.
    AMERICAN STATISTICIAN, 2017, 71 (03): : 265 - 271
  • [24] ORDER STATISTICS FROM A CLASS OF NON-NORMAL DISTRIBUTIONS
    SUBRAHMA.K
    BIOMETRIKA, 1969, 56 (02) : 415 - &
  • [25] Benefit Transfer Equivalence Tests with Non-normal Distributions
    Robert J. Johnston
    Joshua M. Duke
    Environmental and Resource Economics, 2008, 41 : 1 - 23
  • [26] Estimation of a Modified Capability Index for Non-Normal Distributions
    Pearn, W. L.
    Tai, Y. T.
    Wang, H. T.
    JOURNAL OF TESTING AND EVALUATION, 2016, 44 (05) : 1998 - 2009
  • [27] Benefit transfer equivalence tests with non-normal distributions
    Johnston, Robert J.
    Duke, Joshua M.
    ENVIRONMENTAL & RESOURCE ECONOMICS, 2008, 41 (01): : 1 - 23
  • [28] Transition from normal to non-normal distributions of an electromagnetic field in a disordered time-varying cavity
    Zhou, Bo
    Feng, Xinsong
    Guo, Xianmin
    Gao, Fei
    Chen, Hongsheng
    Wang, Zuojia
    PHYSICAL REVIEW A, 2024, 110 (06)
  • [29] LM tests in the presence of non-normal error distributions
    Furno, M
    ECONOMETRIC THEORY, 2000, 16 (02) : 249 - 261
  • [30] ORDER STATISTICS FORM A CLASS OF NON-NORMAL DISTRIBUTIONS
    SUBRAHMA.K
    ANNALS OF MATHEMATICAL STATISTICS, 1968, 39 (05): : 1795 - &