Details
| Original language | English |
|---|---|
| Article number | 105639 |
| Journal | Composites Part A: Applied Science and Manufacturing |
| Volume | 127 |
| Early online date | 21 Sept 2019 |
| Publication status | Published - Dec 2019 |
Abstract
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.
Keywords
- Braided composites, Kriging, Random fields, Stochastic modeling, Yarn distortion, Yarn waviness
ASJC Scopus subject areas
- Materials Science(all)
- Ceramics and Composites
- Engineering(all)
- Mechanics of Materials
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In: Composites Part A: Applied Science and Manufacturing, Vol. 127, 105639, 12.2019.
Research output: Contribution to journal › Article › Research › peer review
}
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 -