Takip et
Matthias G.R. Faes
Matthias G.R. Faes
Diğer adlarMatthias Faes, M. Faes
Full Professor at TU Dortmund - Chair for Reliability Engineering
tu-dortmund.de üzerinde doğrulanmış e-posta adresine sahip - Ana Sayfa
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
Recent trends in the modeling and quantification of non-probabilistic uncertainty
M Faes, D Moens
Archives of Computational Methods in Engineering 27, 633-671, 2020
2252020
Influence of inter-layer cooling time on the quasi-static properties of ABS components produced via fused deposition modelling
M Faes, E Ferraris, D Moens
Procedia Cirp 42, 748-753, 2016
1652016
Extrusion-based 3D printing of ceramic components
M Faes, H Valkenaers, F Vogeler, J Vleugels, E Ferraris
Procedia Cirp 28, 76-81, 2015
1642015
Engineering analysis with probability boxes: A review on computational methods
MGR Faes, M Daub, S Marelli, E Patelli, M Beer
Structural Safety 93, 102092, 2021
1262021
Extrusion-based additive manufacturing of ZrO2 using photoinitiated polymerization
M Faes, J Vleugels, F Vogeler, E Ferraris
CIRP Journal of Manufacturing Science and Technology 14, 28-34, 2016
1222016
Process monitoring of extrusion based 3D printing via laser scanning
M Faes, W Abbeloos, F Vogeler, H Valkenaers, K Coppens, T Goedemé, ...
arXiv preprint arXiv:1612.02219, 2016
982016
On the influence of inter-layer time and energy density on selected critical-to-quality properties of PA12 parts produced via laser sintering
M Pavan, M Faes, D Strobbe, B Van Hooreweder, T Craeghs, D Moens, ...
Polymer testing 61, 386-395, 2017
912017
A multivariate interval approach for inverse uncertainty quantification with limited experimental data
M Faes, M Broggi, E Patelli, Y Govers, J Mottershead, M Beer, D Moens
Mechanical Systems and Signal Processing 118, 534-548, 2019
832019
Identification and quantification of multivariate interval uncertainty in finite element models
M Faes, J Cerneels, D Vandepitte, D Moens
Computer Methods in applied mechanics and engineering 315, 896-920, 2017
612017
Identification and quantification of spatial interval uncertainty in numerical models
M Faes, D Moens
Computers & Structures 192, 16-33, 2017
572017
Bounding the first excursion probability of linear structures subjected to imprecise stochastic loading
MGR Faes, MA Valdebenito, D Moens, M Beer
Computers & Structures 239, 106320, 2020
562020
Parallel adaptive Bayesian quadrature for rare event estimation
C Dang, P Wei, MGR Faes, MA Valdebenito, M Beer
Reliability Engineering & System Safety 225, 108621, 2022
532022
Structural reliability analysis: A Bayesian perspective
C Dang, MA Valdebenito, MGR Faes, P Wei, M Beer
Structural Safety 99, 102259, 2022
512022
Operator norm theory as an efficient tool to propagate hybrid uncertainties and calculate imprecise probabilities
MGR Faes, MA Valdebenito, D Moens, M Beer
Mechanical Systems and Signal Processing 152, 107482, 2021
492021
Fully decoupled reliability-based design optimization of structural systems subject to uncertain loads
MGR Faes, MA Valdebenito
Computer Methods in Applied Mechanics and Engineering 371, 113313, 2020
462020
Multivariate dependent interval finite element analysis via convex hull pair constructions and the extended transformation method
M Faes, D Moens
Computer Methods in Applied Mechanics and Engineering 347, 85-102, 2019
462019
Imprecise random field analysis with parametrized kernel functions
M Faes, D Moens
Mechanical Systems and Signal Processing 134, 106334, 2019
422019
An efficient importance sampling approach for reliability analysis of time-variant structures subject to time-dependent stochastic load
X Yuan, S Liu, M Faes, MA Valdebenito, M Beer
Mechanical Systems and Signal Processing 159, 107699, 2021
402021
Elucidating appealing features of differentiable auto-correlation functions: A study on the modified exponential kernel
MGR Faes, M Broggi, PD Spanos, M Beer
Probabilistic Engineering Mechanics 69, 103269, 2022
352022
On auto‐and cross‐interdependence in interval field finite element analysis
M Faes, D Moens
International Journal for Numerical Methods in Engineering 121 (9), 2033-2050, 2020
332020
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