TY - JOUR

T1 - Stochastic modeling techniques for textile yarn distortion and waviness with 1D random fields

AU - Balokas, Georgios

AU - Kriegesmann, Benedikt

AU - Czichon, Steffen

AU - Rolfes, Raimund

N1 - Funding information: This work was implemented within the framework of the research project ”FULLCOMP: Fully Integrated Analysis, Design, Manufacturing and Health-Monitoring of Composite Structures”. and has received funding from the European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 642121. The provided financial support is gratefully acknowledged by the authors.

PY - 2019/12

Y1 - 2019/12

N2 - Within the concept of simulation approaches for manufacturing-induced imperfections of composite structures, this work proposes modeling frameworks for the consideration of stochastic deviations concerning the yarns of textile composite materials. The random distortion of a yarn's cross-section, is addressed by flexible 1D Fourier-based random fields, with the potential to be calibated from measurements of the deviations from the nominal yarn shape and their statistical characteristics. Furthermore, a Kriging-based modeling approach is presented, able to randomize any nominal yarn path in short or long range problems, considering data for the correlation and variance in a straightforward manner. The effects of defects due to stochastic yarn distortion and waviness, are investigated by simulating a forward uncertainty propagation problem of a triaxially braided composite material. The response variability concerning stiffness and strength for different uncertainty levels is highlighted, while several comments are offered regarding numerical issues and potential surrogate modeling techniques.

AB - Within the concept of simulation approaches for manufacturing-induced imperfections of composite structures, this work proposes modeling frameworks for the consideration of stochastic deviations concerning the yarns of textile composite materials. The random distortion of a yarn's cross-section, is addressed by flexible 1D Fourier-based random fields, with the potential to be calibated from measurements of the deviations from the nominal yarn shape and their statistical characteristics. Furthermore, a Kriging-based modeling approach is presented, able to randomize any nominal yarn path in short or long range problems, considering data for the correlation and variance in a straightforward manner. The effects of defects due to stochastic yarn distortion and waviness, are investigated by simulating a forward uncertainty propagation problem of a triaxially braided composite material. The response variability concerning stiffness and strength for different uncertainty levels is highlighted, while several comments are offered regarding numerical issues and potential surrogate modeling techniques.

KW - Braided composites

KW - Kriging

KW - Random fields

KW - Stochastic modeling

KW - Yarn distortion

KW - Yarn waviness

UR - http://www.scopus.com/inward/record.url?scp=85073115196&partnerID=8YFLogxK

U2 - 10.1016/j.compositesa.2019.105639

DO - 10.1016/j.compositesa.2019.105639

M3 - Article

AN - SCOPUS:85073115196

VL - 127

JO - Composites Part A: Applied Science and Manufacturing

JF - Composites Part A: Applied Science and Manufacturing

SN - 1359-835X

M1 - 105639

ER -