{"language":[{"iso":"eng"}],"publisher":"MDPI AG","article_number":"318","date_updated":"2026-02-02T08:41:26Z","type":"journal_article","author":[{"id":"105344","first_name":"Johannes","last_name":"Gerritzen","full_name":"Gerritzen, Johannes","orcid":"0000-0002-0169-8602"},{"first_name":"Andreas","last_name":"Hornig","full_name":"Hornig, Andreas"},{"full_name":"Gröger, Benjamin","last_name":"Gröger","first_name":"Benjamin"},{"full_name":"Gude, Maik","last_name":"Gude","first_name":"Maik"}],"citation":{"apa":"Gerritzen, J., Hornig, A., Gröger, B., &#38; Gude, M. (2022). A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters. <i>Journal of Composites Science</i>, <i>6</i>(10), Article 318. <a href=\"https://doi.org/10.3390/jcs6100318\">https://doi.org/10.3390/jcs6100318</a>","ama":"Gerritzen J, Hornig A, Gröger B, Gude M. A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters. <i>Journal of Composites Science</i>. 2022;6(10). doi:<a href=\"https://doi.org/10.3390/jcs6100318\">10.3390/jcs6100318</a>","mla":"Gerritzen, Johannes, et al. “A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters.” <i>Journal of Composites Science</i>, vol. 6, no. 10, 318, MDPI AG, 2022, doi:<a href=\"https://doi.org/10.3390/jcs6100318\">10.3390/jcs6100318</a>.","ieee":"J. Gerritzen, A. Hornig, B. Gröger, and M. Gude, “A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters,” <i>Journal of Composites Science</i>, vol. 6, no. 10, Art. no. 318, 2022, doi: <a href=\"https://doi.org/10.3390/jcs6100318\">10.3390/jcs6100318</a>.","chicago":"Gerritzen, Johannes, Andreas Hornig, Benjamin Gröger, and Maik Gude. “A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters.” <i>Journal of Composites Science</i> 6, no. 10 (2022). <a href=\"https://doi.org/10.3390/jcs6100318\">https://doi.org/10.3390/jcs6100318</a>.","bibtex":"@article{Gerritzen_Hornig_Gröger_Gude_2022, title={A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters}, volume={6}, DOI={<a href=\"https://doi.org/10.3390/jcs6100318\">10.3390/jcs6100318</a>}, number={10318}, journal={Journal of Composites Science}, publisher={MDPI AG}, author={Gerritzen, Johannes and Hornig, Andreas and Gröger, Benjamin and Gude, Maik}, year={2022} }","short":"J. Gerritzen, A. Hornig, B. Gröger, M. Gude, Journal of Composites Science 6 (2022)."},"title":"A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters","issue":"10","volume":6,"status":"public","date_created":"2026-02-02T08:41:00Z","abstract":[{"lang":"eng","text":"<jats:p>The 3D shear deformation and failure behaviour of a glass fibre reinforced polypropylene in a shear strain rate range of γ˙=2.2×10−4 to 3.4 1s is investigated. An Iosipescu testing setup on a servo-hydraulic high speed testing unit is used to experimentally characterise the in-plane and out-of-plane behaviour utilising three specimen configurations (12-, 13- and 31-direction). The experimental procedure as well as the testing results are presented and discussed. The measured shear stress–shear strain relations indicate a highly nonlinear behaviour and a distinct rate dependency. Two methods are investigated to derive according material characteristics: a classical engineering approach based on moduli and strengths and a data driven approach based on the curve progression. In all cases a Johnson–Cook based formulation is used to describe rate dependency. The analysis methodologies as well as the derived model parameters are described and discussed in detail. It is shown that a phenomenologically enhanced regression can be used to obtain material characteristics for a generalising constitutive model based on the data driven approach.</jats:p>"}],"intvolume":"         6","_id":"63829","doi":"10.3390/jcs6100318","publication":"Journal of Composites Science","year":"2022","publication_identifier":{"issn":["2504-477X"]},"user_id":"105344","publication_status":"published"}