Predictive multiscale modeling for Unidirectional Carbon Fiber Reinforced Polymers

Gao, Jiaying; Shakoor, Modesar; Domel, Gino; Merzkirch, Matthias; Zhou, Guowei; Zeng, Danielle; Su, Xuming; Liu, Wing Kam

doi:10.1016/j.compscitech.2019.107922

Predictive multiscale modeling for Unidirectional Carbon Fiber Reinforced Polymers

Journal Article · Tue Dec 31 23:00:00 EST 2019 · Composites Science and Technology

DOI:https://doi.org/10.1016/j.compscitech.2019.107922· OSTI ID:1799256

Gao, Jiaying ^[1]; Shakoor, Modesar ^[2]; Domel, Gino ^[3]; Merzkirch, Matthias ^[4]; Zhou, Guowei ^[5]; Zeng, Danielle ^[5]; Su, Xuming ^[5]; Liu, Wing Kam ^[2]

Northwestern Univ., Evanston, IL (United States); OSTI
Northwestern Univ., Evanston, IL (United States)
Univ. of Notre Dame, IN (United States)
National Inst. of Standards and Technology (NIST), Gaithersburg, MD (United States)
Ford Motor Company, Dearborn, MI (United States)

This paper presents a predictive multiscale modeling scheme for Unidirectional (UD) Carbon Fiber Reinforced Polymers (CFRP). A bottom-up modeling procedure is discussed for predicting the performance of UD structures. UD material responses are computed from high fidelity Representative Volume Elements (RVEs). A data-driven Reduced Order Modeling approach compresses RVEs into Reduced Order Models so material responses can be computed in a concurrent fashion along with the structural level simulation. The approach presented in this paper is validated against experimental data and is believed to provide design guidance for future fiber reinforced polymers development.

View Accepted Manuscript (DOE)

Research Organization:: Ford Motor Company, Detroit, MI (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: EE0006867

OSTI ID:: 1799256

Alternate ID(s):: OSTI ID: 1575973

Journal Information:: Composites Science and Technology, Journal Name: Composites Science and Technology Journal Issue: C Vol. 186; ISSN 0266-3538

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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36 MATERIALS SCIENCE
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