Linear Moments-Based Monte Carlo Simulation for Reliability Analysis With Unknown Probability DistributionsSource: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2024:;volume( 010 ):;issue: 002::page 21103-1DOI: 10.1115/1.4064702Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Within the realm of structural reliability analysis, the uncertainties tied to resistance and loads are conventionally embodied as random variables possessing established cumulative distribution functions (CDFs). Nevertheless, real-world scenarios often involve cases where the CDFs of random variables are unknown, necessitating the probabilistic traits of these variables solely through statistical moments. In this study, for the purpose of integrating random variables characterized by an unknown CDF into the framework of Monte Carlo simulation (MCS), a linear moments (L-moments)-based method is proposed. The random variables marked by an unknown CDF are rendered as a straightforward function of a standard normal random variable, and the formulation of this function is determined by utilizing the L-moments, which are typically attainable from the statistical data of the random variables. By employing the proposed approach, the generation of random numbers associated with variables with unknown CDFs becomes a straightforward process, utilizing those derived from a standard normal random variable constructed by using Box-Muller transform. A selection of illustrative examples is presented, in which the efficacy of the technique is scrutinized. This examination reveals that despite its simplicity, the method demonstrates a level of precision that qualifies it for incorporating random variables characterized by unspecified CDFs within the framework of MCS for purposes of structural reliability analysis.
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contributor author | Zhang, Long-Wen | |
contributor author | Zhao, Yan-Gang | |
date accessioned | 2024-04-24T22:45:11Z | |
date available | 2024-04-24T22:45:11Z | |
date copyright | 3/7/2024 12:00:00 AM | |
date issued | 2024 | |
identifier issn | 2332-9017 | |
identifier other | risk_010_02_021103.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4295811 | |
description abstract | Within the realm of structural reliability analysis, the uncertainties tied to resistance and loads are conventionally embodied as random variables possessing established cumulative distribution functions (CDFs). Nevertheless, real-world scenarios often involve cases where the CDFs of random variables are unknown, necessitating the probabilistic traits of these variables solely through statistical moments. In this study, for the purpose of integrating random variables characterized by an unknown CDF into the framework of Monte Carlo simulation (MCS), a linear moments (L-moments)-based method is proposed. The random variables marked by an unknown CDF are rendered as a straightforward function of a standard normal random variable, and the formulation of this function is determined by utilizing the L-moments, which are typically attainable from the statistical data of the random variables. By employing the proposed approach, the generation of random numbers associated with variables with unknown CDFs becomes a straightforward process, utilizing those derived from a standard normal random variable constructed by using Box-Muller transform. A selection of illustrative examples is presented, in which the efficacy of the technique is scrutinized. This examination reveals that despite its simplicity, the method demonstrates a level of precision that qualifies it for incorporating random variables characterized by unspecified CDFs within the framework of MCS for purposes of structural reliability analysis. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Linear Moments-Based Monte Carlo Simulation for Reliability Analysis With Unknown Probability Distributions | |
type | Journal Paper | |
journal volume | 10 | |
journal issue | 2 | |
journal title | ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg | |
identifier doi | 10.1115/1.4064702 | |
journal fristpage | 21103-1 | |
journal lastpage | 21103-11 | |
page | 11 | |
tree | ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2024:;volume( 010 ):;issue: 002 | |
contenttype | Fulltext |