Sensitivity analysis in reliability-based lifetime performance prediction using simulation

Jun g Sik Kong, Dan M. Frangopol

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

The time-varying performance of deteriorating materials and structures can be simulated using probabilistic methods. The propagation of performance uncertainties is affected by the characteristics of input random variables. In general, the number of samples and/or their quality do not satisfy the rigorous statistical constraints required to obtain reliable probability distributions. This deficiency encountered at the beginning of assessment process can be alleviated later by investigating the importance of variables through variability and sensitivity analyses. These analyses help the identification of significant variables in a quantitative way. In this paper, evaluation of the time-varying performance of deteriorating materials and its effect on structures measured by the reliability index profile is addressed based on three aspects: (1) acquisition of statistical characteristics of input random variables from imperfect samples; (2) model-based simulation; and (3) evaluation of variability and sensitivity measures of the nondeterministic performance model. Examples are presented to illustrate these aspects. Journal of Materials in Civil Engineering

Original languageEnglish
Pages (from-to)296-306
Number of pages11
JournalJournal of Materials in Civil Engineering
Volume17
Issue number3
DOIs
Publication statusPublished - 2005 May 1

Fingerprint

Sensitivity analysis
Random variables
Civil engineering
Probability distributions
Uncertainty

Keywords

  • Deterioration
  • Probability
  • Sensitivity analysis
  • Simulation
  • Structural materials

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Materials Science(all)

Cite this

Sensitivity analysis in reliability-based lifetime performance prediction using simulation. / Kong, Jun g Sik; Frangopol, Dan M.

In: Journal of Materials in Civil Engineering, Vol. 17, No. 3, 01.05.2005, p. 296-306.

Research output: Contribution to journalArticle

@article{6981ade496744cabac1044803ec4bec8,
title = "Sensitivity analysis in reliability-based lifetime performance prediction using simulation",
abstract = "The time-varying performance of deteriorating materials and structures can be simulated using probabilistic methods. The propagation of performance uncertainties is affected by the characteristics of input random variables. In general, the number of samples and/or their quality do not satisfy the rigorous statistical constraints required to obtain reliable probability distributions. This deficiency encountered at the beginning of assessment process can be alleviated later by investigating the importance of variables through variability and sensitivity analyses. These analyses help the identification of significant variables in a quantitative way. In this paper, evaluation of the time-varying performance of deteriorating materials and its effect on structures measured by the reliability index profile is addressed based on three aspects: (1) acquisition of statistical characteristics of input random variables from imperfect samples; (2) model-based simulation; and (3) evaluation of variability and sensitivity measures of the nondeterministic performance model. Examples are presented to illustrate these aspects. Journal of Materials in Civil Engineering",
keywords = "Deterioration, Probability, Sensitivity analysis, Simulation, Structural materials",
author = "Kong, {Jun g Sik} and Frangopol, {Dan M.}",
year = "2005",
month = "5",
day = "1",
doi = "10.1061/(ASCE)0899-1561(2005)17:3(296)",
language = "English",
volume = "17",
pages = "296--306",
journal = "Journal of Materials in Civil Engineering",
issn = "0899-1561",
publisher = "American Society of Civil Engineers (ASCE)",
number = "3",

}

TY - JOUR

T1 - Sensitivity analysis in reliability-based lifetime performance prediction using simulation

AU - Kong, Jun g Sik

AU - Frangopol, Dan M.

PY - 2005/5/1

Y1 - 2005/5/1

N2 - The time-varying performance of deteriorating materials and structures can be simulated using probabilistic methods. The propagation of performance uncertainties is affected by the characteristics of input random variables. In general, the number of samples and/or their quality do not satisfy the rigorous statistical constraints required to obtain reliable probability distributions. This deficiency encountered at the beginning of assessment process can be alleviated later by investigating the importance of variables through variability and sensitivity analyses. These analyses help the identification of significant variables in a quantitative way. In this paper, evaluation of the time-varying performance of deteriorating materials and its effect on structures measured by the reliability index profile is addressed based on three aspects: (1) acquisition of statistical characteristics of input random variables from imperfect samples; (2) model-based simulation; and (3) evaluation of variability and sensitivity measures of the nondeterministic performance model. Examples are presented to illustrate these aspects. Journal of Materials in Civil Engineering

AB - The time-varying performance of deteriorating materials and structures can be simulated using probabilistic methods. The propagation of performance uncertainties is affected by the characteristics of input random variables. In general, the number of samples and/or their quality do not satisfy the rigorous statistical constraints required to obtain reliable probability distributions. This deficiency encountered at the beginning of assessment process can be alleviated later by investigating the importance of variables through variability and sensitivity analyses. These analyses help the identification of significant variables in a quantitative way. In this paper, evaluation of the time-varying performance of deteriorating materials and its effect on structures measured by the reliability index profile is addressed based on three aspects: (1) acquisition of statistical characteristics of input random variables from imperfect samples; (2) model-based simulation; and (3) evaluation of variability and sensitivity measures of the nondeterministic performance model. Examples are presented to illustrate these aspects. Journal of Materials in Civil Engineering

KW - Deterioration

KW - Probability

KW - Sensitivity analysis

KW - Simulation

KW - Structural materials

UR - http://www.scopus.com/inward/record.url?scp=20444437934&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=20444437934&partnerID=8YFLogxK

U2 - 10.1061/(ASCE)0899-1561(2005)17:3(296)

DO - 10.1061/(ASCE)0899-1561(2005)17:3(296)

M3 - Article

VL - 17

SP - 296

EP - 306

JO - Journal of Materials in Civil Engineering

JF - Journal of Materials in Civil Engineering

SN - 0899-1561

IS - 3

ER -