Special Section: Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis

Publikation: Beitrag in Fachzeitschrift › Editorial in Fachzeitschrift › Forschung › Peer-Review

Autoren

  • Matthias G.R. Faes
  • David Moens
  • Michael Beer
  • Hao Zhang
  • Kok-Kwang Phoon

Organisationseinheiten

Externe Organisationen

  • KU Leuven
  • The University of Liverpool
  • Tongji University
  • National University of Singapore
  • Universität Sydney
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Aufsatznummer020301
Seitenumfang2
FachzeitschriftASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Jahrgang7
Ausgabenummer2
Frühes Online-Datum19 März 2021
PublikationsstatusVeröffentlicht - Juni 2021

ASJC Scopus Sachgebiete

Zitieren

Special Section: Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis. / Faes, Matthias G.R.; Moens, David; Beer, Michael et al.
in: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, Jahrgang 7, Nr. 2, 020301, 06.2021.

Publikation: Beitrag in Fachzeitschrift › Editorial in Fachzeitschrift › Forschung › Peer-Review

Faes, MGR, Moens, D, Beer, M, Zhang, H & Phoon, K-K 2021, 'Special Section: Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis', ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, Jg. 7, Nr. 2, 020301. https://doi.org/10.1115/1.4050256
Faes, M. G. R., Moens, D., Beer, M., Zhang, H., & Phoon, K.-K. (2021). Special Section: Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 7(2), Artikel 020301. https://doi.org/10.1115/1.4050256
Faes MGR, Moens D, Beer M, Zhang H, Phoon KK. Special Section: Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering. 2021 Jun;7(2):020301. Epub 2021 Mär 19. doi: 10.1115/1.4050256
Faes, Matthias G.R. ; Moens, David ; Beer, Michael et al. / Special Section : Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis. in: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering. 2021 ; Jahrgang 7, Nr. 2.
Download
@article{9be58e283fdb4054bfd2945f67ca84f5,
title = "Special Section: Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis",
author = "Faes, {Matthias G.R.} and David Moens and Michael Beer and Hao Zhang and Kok-Kwang Phoon",
year = "2021",
month = jun,
doi = "10.1115/1.4050256",
language = "English",
volume = "7",
number = "2",

}

Download

TY - JOUR

T1 - Special Section

T2 - Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis

AU - Faes, Matthias G.R.

AU - Moens, David

AU - Beer, Michael

AU - Zhang, Hao

AU - Phoon, Kok-Kwang

PY - 2021/6

Y1 - 2021/6

UR - http://www.scopus.com/inward/record.url?scp=85103046766&partnerID=8YFLogxK

U2 - 10.1115/1.4050256

DO - 10.1115/1.4050256

M3 - Editorial in journal

AN - SCOPUS:85103046766

VL - 7

JO - ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering

JF - ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering

SN - 2332-9017

IS - 2

M1 - 020301

ER -

Von denselben Autoren

  1. Physics-informed neural network classification framework for reliability analysis

    Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review

  2. A novel directional simulation method for estimating failure possibility

    Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review

  3. Deep learning-driven interval uncertainty propagation for aeronautical structures: Adaptive combination of line sampling for imprecise time-variant reliability analysis

    Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review

  4. A sub-convex similarity-based model updating method considering multivariate uncertainties

    Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review

  5. Survival probability surfaces of hysteretic fractional order structures exposed to non-stationary code-compliant stochastic seismic excitation

    Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review