Fuzzy and stochastic approach applied to rubber like materials
E. Penner, I. Caylak, R. Mahnken, A. Dridger, Safety and Reliability (2021) 1–19.

A deep learning driven pseudospectral PCE based FFT homogenization algorithm for complex microstructures
A. Henkes, I. Caylak, R. Mahnken, Computer Methods in Applied Mechanics and Engineering (2021).

Mean-field and full-field homogenization with polymorphic uncertain geometry and material parameters
I. Caylak, E. Penner, R. Mahnken, Computer Methods in Applied Mechanics and Engineering (2020).

A possibilistic finite element method for sparse data
A. Dridger, I. Caylak, R. Mahnken, E. Penner, Safety and Reliability (2019) 58–82.

Optimization with constraints considering polymorphic uncertainties
M. Mäck, I. Caylak, P. Edler, S. Freitag, M. Hanss, R. Mahnken, G. Meschke, E. Penner, GAMM-Mitteilungen (2019).

A polynomial chaos expanded hybrid fuzzy-stochastic model for transversely fiber reinforced plastics
E. Penner, I. Caylak, A. Dridger, R. Mahnken, Mathematics and Mechanics of Complex Systems (2019) 99–129.

A fuzzy uncertainty model for analytical and numerical homogenization of transversely fiber reinforced plastics
I. Caylak, E. Penner, R. Mahnken, PAMM (2019).

On the connection between possibility theory and probability box theory in structural mechanics
A. Dridger, I. Caylak, R. Mahnken, E. Penner, in: 13th World Congress in Computational Mechanics , 2018.

Stochastic hyperelastic modeling considering dependency of material parameters
I. Caylak, E. Penner, A. Dridger, R. Mahnken, Computational Mechanics (2018) 1273–1285.

A fuzzystochastic model for transversely fiber reinforced plastics
I. Caylak, E. Penner, A. Dridger, R. Mahnken, PAMM (2018).

Possibilistic and stochastic analysis using for rubberlike materials
E. Penner, I. Caylak, A. Dridger, R. Mahnken, PAMM (2018).

A multivariate stochastic material model with correlated material parameters
E. Penner, I. Caylak, R. Mahnken, PAMM (2018) 67–68.

MULTIDIMENSIONAL STOCHASTIC MATERIAL MODELING AT LARGE DEFORMATIONS CONSIDERING PARAMETER CORRELATIONS
E. Penner, I. Caylak, R. Mahnken, in: Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2017), 2017.

A Stochastic Finite Element Method with a Deviatoric-volumetric Split for the Stochastic Linear Isotropic Elasticity Tensor
R. Mahnken, I. Caylak, A. Dridger, A Stochastic Finite Element Method with a Deviatoric-Volumetric Split for the Stochastic Linear Isotropic Elasticity Tensor (2016).

PC expansion for material parameters using artificial data and statistical methods
I. Caylak, N. Nörenberg, R. Mahnken, PAMM (2016) 191–192.

A linear elastic Fuzzy Finite Element Method with two fuzzy input parameters
A. Dridger, I. Caylak, R. Mahnken, PAMM (2016) 667–668.

SFEM for rubber-like materials at large deformations
E. Penner, I. Caylak, N. Nörenberg, R. Mahnken, PAMM (2016) 675–676.

Uncertainty quantification for linear elastic bodies with two fluctuating input parameters
A. Dridger, I. Caylak, R. Mahnken, PAMM (2015) 551–552.

Non-linear Stochastic Finite Element
I. Caylak, A. Dridger, R. Mahnken, PAMM (2015) 179–180.

Experimental Investigation of PC-Films Using Optical Measurements
C. Dammann, I. Caylak, R. Mahnken, International Polymer Processing (2014) 260–271.