Matthias G. R. Faes

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 13

Top Topics

Reliability Analysis

Probability Function

Nelder Mead Simplex

Top Venues

Reliab. Eng. Syst. Saf.

Adv. Eng. Softw.

Publications

Lukás Novák, Marcos A. Valdebenito, Matthias G. R. Faes
On Fractional Moment Estimation from Polynomial Chaos Expansion. CoRR (2024)
Xiukai Yuan, Weiming Zheng, Chaofan Zhao, Marcos A. Valdebenito, Matthias G. R. Faes, Yiwei Dong
Line sampling for time-variant failure probability estimation using an adaptive combination approach. Reliab. Eng. Syst. Saf. 243 (2024)
Xiukai Yuan, Yugeng Qian, Jingqiang Chen, Matthias G. R. Faes, Marcos A. Valdebenito, Michael Beer
Global failure probability function estimation based on an adaptive strategy and combination algorithm. Reliab. Eng. Syst. Saf. 231 (2023)
Chao Dang, Pengfei Wei, Matthias G. R. Faes, Marcos A. Valdebenito, Michael Beer
Parallel adaptive Bayesian quadrature for rare event estimation. Reliab. Eng. Syst. Saf. 225 (2022)
Matthias G. R. Faes, Marcos A. Valdebenito, Xiukai Yuan, Pengfei Wei, Michael Beer
Augmented reliability analysis for estimating imprecise first excursion probabilities in stochastic linear dynamics. Adv. Eng. Softw. 155 (2021)
Xiukai Yuan, Matthias G. R. Faes, Shaolong Liu, Marcos A. Valdebenito, Michael Beer
Efficient imprecise reliability analysis using the Augmented Space Integral. Reliab. Eng. Syst. Saf. 210 (2021)
Xiukai Yuan, Shaolong Liu, Marcos A. Valdebenito, Matthias G. R. Faes, Danko J. Jerez, Hector A. Jensen, Michael Beer
Decoupled reliability-based optimization using Markov chain Monte Carlo in augmented space. Adv. Eng. Softw. (2021)
Lechang Yang, Pidong Wang, Wenhua Zhao, Chenxing Wang, Xiuli Wu, Matthias G. R. Faes
On investigation of the Bayesian anomaly in multiple imprecise dependent information aggregation for system reliability evaluation. Int. J. Intell. Syst. 36 (6) (2021)
Laura Bartsoen, Matthias G. R. Faes, Mariska Wesseling, Roel Wirix-Speetjens, David Moens, Ilse Jonkers, Jos Vander Sloten
Computationally Efficient Optimization Method to Quantify the Required Surgical Accuracy for a Ligament Balanced TKA. IEEE Trans. Biomed. Eng. 68 (11) (2021)
Matthias G. R. Faes, Ghosh Dastidar Sabyasachi, David Moens
Hybrid spatial uncertainty analysis for the estimation of imprecise failure probabilities in Laser Sintered PA-12 parts. Comput. Math. Appl. 78 (7) (2019)
Lars Bogaerts, Matthias G. R. Faes, David Moens
A fast inverse approach for the quantification of set-theoretical uncertainty. SSCI (2019)
Matteo Broggi, Matthias G. R. Faes, Edoardo Patelli, Yves Govers, David Moens, Michael Beer
Comparison of Bayesian and interval uncertainty quantification: Application to the AIRMOD test structure. SSCI (2017)
Matthias G. R. Faes, Wim Abbeloos, Frederik Vogeler, Hans Valkenaers, Kurt Coppens, Toon Goedemé, Eleonora Ferraris
Process Monitoring of Extrusion Based 3D Printing via Laser Scanning. CoRR (2016)