Matthias G.R. Faes

About Matthias G.R. Faes

Matthias G.R. Faes, With an exceptional h-index of 22 and a recent h-index of 21 (since 2020), a distinguished researcher at Katholieke Universiteit Leuven, specializes in the field of Imprecise Probabilities, Reliability Engineering, Interval Analysis.

His recent articles reflect a diverse array of research interests and contributions to the field:

Operator norm-based determination of failure probability of nonlinear oscillators with fractional derivative elements subject to imprecise stationary Gaussian loads

Structural reliability analysis with extremely small failure probabilities: A quasi-Bayesian active learning method

Soft Monte Carlo Simulation for imprecise probability estimation: A dimension reduction-based approach

Novel Grey-Box Modelling Techniques for Resistance Spot Welding

Certified interval model updating using scenario optimization

Partially Bayesian active learning cubature for structural reliability analysis with extremely small failure probabilities

Resilience Assessment under Imprecise Probability

On Fractional Moment Estimation from Polynomial Chaos Expansion

Matthias G.R. Faes Information

University

Position

- Department of Mechanical Engineering; Research Foundation Flanders (FWO)

Citations(all)

1845

Citations(since 2020)

1598

Cited By

753

hIndex(all)

22

hIndex(since 2020)

21

i10Index(all)

38

i10Index(since 2020)

37

Email

University Profile Page

Google Scholar

Matthias G.R. Faes Skills & Research Interests

Imprecise Probabilities

Reliability Engineering

Interval Analysis

Top articles of Matthias G.R. Faes

Title

Journal

Author(s)

Publication Date

Operator norm-based determination of failure probability of nonlinear oscillators with fractional derivative elements subject to imprecise stationary Gaussian loads

Mechanical Systems and Signal Processing

DJ Jerez

VC Fragkoulis

Peihua Ni

IP Mitseas

Marcos A Valdebenito

...

2024/2/15

Structural reliability analysis with extremely small failure probabilities: A quasi-Bayesian active learning method

Probabilistic Engineering Mechanics

Chao Dang

Alice Cicirello

Marcos A Valdebenito

Matthias GR Faes

Pengfei Wei

...

2024/4/1

Soft Monte Carlo Simulation for imprecise probability estimation: A dimension reduction-based approach

Structural Safety

Azam Abdollahi

Hossein Shahraki

Matthias GR Faes

Mohsen Rashki

2024/1/1

Novel Grey-Box Modelling Techniques for Resistance Spot Welding

Lars Bogaerts

Miriam Beatrice Dodt

Augustin Persoons

Matthias Faes

Patrick Van Rymenant

...

2024/3/26

Certified interval model updating using scenario optimization

Robin Callens

David Moens

Matthias Faes

2024

Partially Bayesian active learning cubature for structural reliability analysis with extremely small failure probabilities

Computer Methods in Applied Mechanics and Engineering

Chao Dang

Matthias GR Faes

Marcos A Valdebenito

Pengfei Wei

Michael Beer

2024/3/15

Resilience Assessment under Imprecise Probability

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

Cao Wang

Michael Beer

Matthias GR Faes

De-Cheng Feng

2024/6/1

On Fractional Moment Estimation from Polynomial Chaos Expansion

arXiv preprint arXiv:2403.01948

Lukáš Novák

Marcos Valdebenito

Matthias Faes

2024/3/4

Control variates with splitting for aggregating results of Monte Carlo simulation and perturbation analysis

Structural Safety

Cristóbal H Acevedo

Marcos A Valdebenito

Iván V González

Héctor A Jensen

Matthias GR Faes

...

2024/5/1

Line sampling for time-variant failure probability estimation using an adaptive combination approach

Reliability Engineering & System Safety

Xiukai Yuan

Weiming Zheng

Chaofan Zhao

Marcos A Valdebenito

Matthias GR Faes

...

2024/3/1

A meta-heuristic approach for reliability-based design optimization of shell-and-tube heat exchangers

Applied Thermal Engineering

Jafar Jafari-Asl

Oscar D Lara Montaño

Seyedali Mirjalili

Matthias GR Faes

2024/4/15

Robust topology optimization for fiber-reinforced composites under material uncertainty

Computer Methods in Applied Mechanics and Engineering

Sheng Chu

Mi Xiao

Liang Gao

Yan Zhang

Jinhao Zhang

2021/10/1

Structural reliability analysis by line sampling: A Bayesian active learning treatment

Structural Safety

Chao Dang

Marcos A Valdebenito

Matthias GR Faes

Jingwen Song

Pengfei Wei

...

2023/9/1

Effect of uncertainty of material parameters on stress triaxiality and Lode angle in finite elasto-plasticity—A variance-based global sensitivity analysis

Advances in Industrial and Manufacturing Engineering

M Böddecker

MGR Faes

A Menzel

MA Valdebenito

2023/11/1

Robust design optimisation under lack-of-knowledge uncertainty

Computers & Structures

Conradus van Mierlo

Augustin Persoons

Matthias GR Faes

David Moens

2023/1/15

Efficient decoupling approach for reliability-based optimization based on augmented Line Sampling and combination algorithm

Computers & Structures

Xiukai Yuan

Marcos A Valdebenito

Baoqiang Zhang

Matthias GR Faes

Michael Beer

2023/5/1

A self-learning Digital Twin for Process Control of fast processes under Uncertainty

Uncecomp 2023 Proceedings

Miriam Beatrice Dodt

Augustin Persoons

Matthias GR Faes

David Moens

2023/6/12

No-free-lunch theorems for reliability analysis

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

Mohsen Rashki

Matthias GR Faes

2023/9/1

Augmented first-order reliability method for estimating fuzzy failure probabilities

Structural Safety

Marcos A Valdebenito

Xiukai Yuan

Matthias GR Faes

2023/11/1

INTERVAL FIELD METHODS WITH LOCAL GRADIENT CONTROL

Computers and Structures

Conradus Van Mierlo

Matthias GR Faes

David Moens

RRP Callens

2023/1/15

See List of Professors in Matthias G.R. Faes University(Katholieke Universiteit Leuven)

Co-Authors

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