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Matthias G. R. Faes ORCID

Die folgende Bibliografie enthält alle in dieser Datenbank indizierten Veröffentlichungen, die mit diesem Namen als Autor, Herausgeber oder anderweitig Beitragenden verbunden sind.

  1. Zhao, Haodong / Zhou, Changcong / Chang, Qi / Shi, Haotian / Valdebenito, Marcos A. / Faes, Matthias G. R. (2024): Limit-State Function Sensitivity under Epistemic Uncertainty: A Convex Model Approach. In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 10, n. 4 (Dezember 2024).

    https://doi.org/10.1061/ajrua6.rueng-1393

  2. Manque, Nataly A. / Valdebenito, Marcos A. / Beaurepaire, Pierre / Moens, David / Faes, Matthias G. R. (2024): A reduced-order model approach for fuzzy fields analysis. In: Structural Safety, v. 111 (November 2024).

    https://doi.org/10.1016/j.strusafe.2024.102498

  3. Chang, Qi / Zhou, Changcong / Faes, Matthias G. R. / Valdebenito, Marcos A. (2024): Design Optimization with Variable Screening by Interval-Based Sensitivity Analysis. In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 10, n. 3 (September 2024).

    https://doi.org/10.1061/ajrua6.rueng-1266

  4. Ypsilantis, Konstantinos-Iason / Faes, Matthias G. R. / Lagaros, Nikos D. / Aage, Niels / Moens, David (2024): Robust topology and discrete fiber orientation optimization under principal material uncertainty. In: Computers & Structures, v. 300 (August 2024).

    https://doi.org/10.1016/j.compstruc.2024.107421

  5. Wang, Cao / Beer, Michael / Faes, Matthias G. R. / Feng, De-Cheng (2024): Resilience Assessment under Imprecise Probability. In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 10, n. 2 (Juni 2024).

    https://doi.org/10.1061/ajrua6.rueng-1244

  6. Acevedo, Cristóbal H. / Valdebenito, Marcos A. / González, Iván V. / Jensen, Hector A. / Faes, Matthias G. R. / Liu, Yong (2024): Control variates with splitting for aggregating results of Monte Carlo simulation and perturbation analysis. In: Structural Safety, v. 108 (Mai 2024).

    https://doi.org/10.1016/j.strusafe.2024.102445

  7. Abdollahi, Azam / Shahraki, Hossein / Faes, Matthias G. R. / Rashki, Mohsen (2024): Soft Monte Carlo Simulation for imprecise probability estimation: A dimension reduction-based approach. In: Structural Safety, v. 106 (Januar 2024).

    https://doi.org/10.1016/j.strusafe.2023.102391

  8. Valdebenito, Marcos A. / Yuan, Xiukai / Faes, Matthias G. R. (2023): Augmented first-order reliability method for estimating fuzzy failure probabilities. In: Structural Safety, v. 105 (November 2023).

    https://doi.org/10.1016/j.strusafe.2023.102380

  9. Dang, Chao / Valdebenito, Marcos A. / Faes, Matthias G. R. / Song, Jingwen / Wei, Pengfei / Beer, Michael (2023): Structural reliability analysis by line sampling: A Bayesian active learning treatment. In: Structural Safety, v. 104 (September 2023).

    https://doi.org/10.1016/j.strusafe.2023.102351

  10. Rashki, Mohsen / Faes, Matthias G. R. (2023): No-Free-Lunch Theorems for Reliability Analysis. In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 9, n. 3 (September 2023).

    https://doi.org/10.1061/ajrua6.rueng-1015

  11. Yuan, Xiukai / Valdebenito, Marcos A. / Zhang, Baoqiang / Faes, Matthias G. R. / Beer, Michael (2023): Efficient decoupling approach for reliability-based optimization based on augmented Line Sampling and combination algorithm. In: Computers & Structures, v. 280 (Mai 2023).

    https://doi.org/10.1016/j.compstruc.2023.107003

  12. Fina, Marc / Lauff, Celine / Faes, Matthias G. R. / Valdebenito, Marcos A. / Wagner, Werner / Freitag, Steffen (2023): Bounding imprecise failure probabilities in structural mechanics based on maximum standard deviation. In: Structural Safety, v. 101 (März 2023).

    https://doi.org/10.1016/j.strusafe.2022.102293

  13. van Mierlo, Conradus / Persoons, Augustin / Faes, Matthias G. R. / Moens, David (2023): Robust design optimisation under lack-of-knowledge uncertainty. In: Computers & Structures, v. 275 (Januar 2023).

    https://doi.org/10.1016/j.compstruc.2022.106910

  14. Dang, Chao / Valdebenito, Marcos A. / Faes, Matthias G. R. / Wei, Pengfei / Beer, Michael (2022): Structural reliability analysis: A Bayesian perspective. In: Structural Safety, v. 99 (November 2022).

    https://doi.org/10.1016/j.strusafe.2022.102259

  15. Dang, Chao / Wei, Pengfei / Faes, Matthias G. R. / Beer, Michael (2022): Bayesian probabilistic propagation of hybrid uncertainties: Estimation of response expectation function, its variable importance and bounds. In: Computers & Structures, v. 270 (Oktober 2022).

    https://doi.org/10.1016/j.compstruc.2022.106860

  16. Ypsilantis, Konstantinos-Iason / Faes, Matthias G. R. / Ivens, Jan / Lagaros, Nikos D. / Moens, David (2022): An approach for the concurrent homogenization-based microstructure type and topology optimization problem. In: Computers & Structures, v. 272 (November 2022).

    https://doi.org/10.1016/j.compstruc.2022.106859

  17. Ni, Peihua / Jerez, Danko J. / Fragkoulis, Vasileios C. / Faes, Matthias G. R. / Valdebenito, Marcos A. / Beer, Michael (2022): Operator Norm-Based Statistical Linearization to Bound the First Excursion Probability of Nonlinear Structures Subjected to Imprecise Stochastic Loading. In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 8, n. 1 (März 2022).

    https://doi.org/10.1061/ajrua6.0001217

  18. Faes, Matthias G. R. / Daub, Marco / Marelli, Stefano / Patelli, Edoardo / Beer, Michael (2021): Engineering analysis with probability boxes: A review on computational methods. In: Structural Safety, v. 93 (November 2021).

    https://doi.org/10.1016/j.strusafe.2021.102092

  19. Faes, Matthias G. R. / Valdebenito, Marcos A. / Moens, David / Beer, Michael (2020): Bounding the first excursion probability of linear structures subjected to imprecise stochastic loading. In: Computers & Structures, v. 239 (Oktober 2020).

    https://doi.org/10.1016/j.compstruc.2020.106320

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