Epistemic uncertainty in reliability-based design optimization

Xiaotian Zhuang, Rong Pan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Reliability-based design optimization (RBDO) needs to take into account of both aleatory and epistemic uncertainties. It is critical to explore these uncertainty sources and evaluate their impacts on RBDO. This paper provides a comprehensive study of uncertainties, in which the uncertainty sources are listed, categorized and their impacts are discussed. Epistemic uncertainty is of our interest, which is due to lack of knowledge and can be reduced. We specifically discuss the epistemic uncertainties due to unknown constraint function and unknown random variable distribution. The strategies to address epistemic uncertainty are summarized. An I-beam case study is employed to illustrate the impact of epistemic un certainty on RBDO, in which a Kriging model is used to approximate the unknown true constraint function and the root-mean-square error (RMSE) parameter estimate is used to replace the unknown distribution parameters.

Original languageEnglish (US)
Title of host publicationProceedings - Annual Reliability and Maintainability Symposium
DOIs
StatePublished - 2012
Event2012 Annual Reliability and Maintainability Symposium, RAMS 2012 - Reno, NV, United States
Duration: Jan 23 2012Jan 26 2012

Other

Other2012 Annual Reliability and Maintainability Symposium, RAMS 2012
CountryUnited States
CityReno, NV
Period1/23/121/26/12

Fingerprint

Epistemic Uncertainty
Unknown
Uncertainty
Kriging
Mean square error
Random variable
Roots
Design optimization
Evaluate
Random variables
Estimate

Keywords

  • Epistemic Uncertainty
  • Reliability-Based Design Optimization

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Mathematics(all)
  • Computer Science Applications

Cite this

Zhuang, X., & Pan, R. (2012). Epistemic uncertainty in reliability-based design optimization. In Proceedings - Annual Reliability and Maintainability Symposium [6175496] https://doi.org/10.1109/RAMS.2012.6175496

Epistemic uncertainty in reliability-based design optimization. / Zhuang, Xiaotian; Pan, Rong.

Proceedings - Annual Reliability and Maintainability Symposium. 2012. 6175496.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhuang, X & Pan, R 2012, Epistemic uncertainty in reliability-based design optimization. in Proceedings - Annual Reliability and Maintainability Symposium., 6175496, 2012 Annual Reliability and Maintainability Symposium, RAMS 2012, Reno, NV, United States, 1/23/12. https://doi.org/10.1109/RAMS.2012.6175496
Zhuang X, Pan R. Epistemic uncertainty in reliability-based design optimization. In Proceedings - Annual Reliability and Maintainability Symposium. 2012. 6175496 https://doi.org/10.1109/RAMS.2012.6175496
Zhuang, Xiaotian ; Pan, Rong. / Epistemic uncertainty in reliability-based design optimization. Proceedings - Annual Reliability and Maintainability Symposium. 2012.
@inproceedings{44df07a9a94743d3b68c34e025f18e4e,
title = "Epistemic uncertainty in reliability-based design optimization",
abstract = "Reliability-based design optimization (RBDO) needs to take into account of both aleatory and epistemic uncertainties. It is critical to explore these uncertainty sources and evaluate their impacts on RBDO. This paper provides a comprehensive study of uncertainties, in which the uncertainty sources are listed, categorized and their impacts are discussed. Epistemic uncertainty is of our interest, which is due to lack of knowledge and can be reduced. We specifically discuss the epistemic uncertainties due to unknown constraint function and unknown random variable distribution. The strategies to address epistemic uncertainty are summarized. An I-beam case study is employed to illustrate the impact of epistemic un certainty on RBDO, in which a Kriging model is used to approximate the unknown true constraint function and the root-mean-square error (RMSE) parameter estimate is used to replace the unknown distribution parameters.",
keywords = "Epistemic Uncertainty, Reliability-Based Design Optimization",
author = "Xiaotian Zhuang and Rong Pan",
year = "2012",
doi = "10.1109/RAMS.2012.6175496",
language = "English (US)",
isbn = "9781457718496",
booktitle = "Proceedings - Annual Reliability and Maintainability Symposium",

}

TY - GEN

T1 - Epistemic uncertainty in reliability-based design optimization

AU - Zhuang, Xiaotian

AU - Pan, Rong

PY - 2012

Y1 - 2012

N2 - Reliability-based design optimization (RBDO) needs to take into account of both aleatory and epistemic uncertainties. It is critical to explore these uncertainty sources and evaluate their impacts on RBDO. This paper provides a comprehensive study of uncertainties, in which the uncertainty sources are listed, categorized and their impacts are discussed. Epistemic uncertainty is of our interest, which is due to lack of knowledge and can be reduced. We specifically discuss the epistemic uncertainties due to unknown constraint function and unknown random variable distribution. The strategies to address epistemic uncertainty are summarized. An I-beam case study is employed to illustrate the impact of epistemic un certainty on RBDO, in which a Kriging model is used to approximate the unknown true constraint function and the root-mean-square error (RMSE) parameter estimate is used to replace the unknown distribution parameters.

AB - Reliability-based design optimization (RBDO) needs to take into account of both aleatory and epistemic uncertainties. It is critical to explore these uncertainty sources and evaluate their impacts on RBDO. This paper provides a comprehensive study of uncertainties, in which the uncertainty sources are listed, categorized and their impacts are discussed. Epistemic uncertainty is of our interest, which is due to lack of knowledge and can be reduced. We specifically discuss the epistemic uncertainties due to unknown constraint function and unknown random variable distribution. The strategies to address epistemic uncertainty are summarized. An I-beam case study is employed to illustrate the impact of epistemic un certainty on RBDO, in which a Kriging model is used to approximate the unknown true constraint function and the root-mean-square error (RMSE) parameter estimate is used to replace the unknown distribution parameters.

KW - Epistemic Uncertainty

KW - Reliability-Based Design Optimization

UR - http://www.scopus.com/inward/record.url?scp=84860627965&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84860627965&partnerID=8YFLogxK

U2 - 10.1109/RAMS.2012.6175496

DO - 10.1109/RAMS.2012.6175496

M3 - Conference contribution

AN - SCOPUS:84860627965

SN - 9781457718496

BT - Proceedings - Annual Reliability and Maintainability Symposium

ER -