Experimental Investigations of Carbon Fiber Reinforced Polymer Composites and Their Constituents to Determine Their Elastic Material Properties and Complementary Inhomogeneous Experiments with Local Strain Considerations
E. Penner, I. Caylak, R. Mahnken, Fibers and Polymers (2023).

Effects on Process Forces of Individual Milling Tool Edges Depending on the Cutting Angle and Cutting Speed When Milling Cfrp
R. Clemens, E. Barth, E. Uhlmann, Y. Zhan, I. Caylak, R. Mahnken, SSRN Electronic Journal (2022).

A polymorphic uncertainty model for the curing process of transversely fiber-reinforced plastics
E. Penner, I. Caylak, R. Mahnken, Mathematics and Mechanics of Complex Systems 10 (2022) 21–50.

An uncertainty model for the curing process of transversely fiber reinforced plastics
E. Penner, I. Caylak, R. Mahnken, PAMM (2021).

A deep learning driven uncertain fullfield homogenization method
A. Henkes, I. Caylak, R. Mahnken, PAMM (2021).

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.