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Matthias G. R. Faes ORCID

The following bibliography contains all publications indexed in this database that are linked with this name as either author, editor or any other kind of contributor.

  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 (December 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 (June 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 (May 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 (January 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 (May 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 (March 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 (January 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 (October 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 (March 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 (October 2020).

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

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