On the Influence of Fatigue Damage in Short-Fibre Reinforced Thermoplastic PBT GF30 on Its Residual Strength under High Strain Rates: An Approach towards Simulative Prediction

Witzgall C, Steck P, Wartzack S (2023)


Publication Type: Journal article

Publication year: 2023

Journal

Original Authors: Christian Witzgall, Patrick Steck, Sandro Wartzack

Book Volume: 7

Pages Range: 23

Issue: 1

DOI: 10.3390/jcs7010023

Abstract

Only by using accurate material data can precise simulation results be achieved. This principle also and especially applies in the field of crash simulation. However, in the simulation of short-fibre reinforced thermoplastics, material parameters are usually used that originate from the material testing of as-new samples. In order to get closer to the condition on the roads, where not only new vehicles are driving, the influence of service loads on the crashworthiness has to be investigated. This paper reports on studies of PBT GF30, a polybutylene terephthalate reinforced with 30% glass fibres, in which fatigue damage was induced in the material by cyclic loading. The residual strength was then determined in a high-speed experiment and compared with the strength of virgin samples. In order to enable the usability of the findings in the simulation, a modified failure criterion was implemented that takes the previous fatigue damage into account. The prediction quality of the simulation model was compared with the experimental findings and it can be concluded that there is good agreement.

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How to cite

APA:

Witzgall, C., Steck, P., & Wartzack, S. (2023). On the Influence of Fatigue Damage in Short-Fibre Reinforced Thermoplastic PBT GF30 on Its Residual Strength under High Strain Rates: An Approach towards Simulative Prediction. Journal of Composites Science, 7, 23. https://dx.doi.org/10.3390/jcs7010023

MLA:

Witzgall, Christian, Patrick Steck, and Sandro Wartzack. "On the Influence of Fatigue Damage in Short-Fibre Reinforced Thermoplastic PBT GF30 on Its Residual Strength under High Strain Rates: An Approach towards Simulative Prediction." Journal of Composites Science 7 (2023): 23.

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