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    Rights statement: This is the author’s version of a work that was accepted for publication in Composites Science and Technology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Composites Science and Technology, 218, 2022 DOI: 10.1016/j.compscitech.2021.109122

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A new two-step modeling strategy for random micro-fiber reinforced composites with consideration of primary pores

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Article number109122
<mark>Journal publication date</mark>8/02/2022
<mark>Journal</mark>Composites Science and Technology
Volume218
Number of pages19
Publication StatusPublished
Early online date25/11/21
<mark>Original language</mark>English

Abstract

This paper presents a novel procedure to evaluate mechanical properties of random micro-fiber reinforced composites with consideration of primary pores. To this end, micro-CT experiment is conducted first to detect micro-scale morphology of the constituent materials, including size of pores and arrangement of fibers, etc. On this basis, a two-step modeling strategy with consideration of primary pores is proposed. In the first step, the equivalent mechanical properties of the pore defects and the micro-fibers are determined by the 3D parametric finite volume directly averaging micromechanics (FVDAM), by which an equivalent ellipsoidal reinforcing phase composed of fibers and pores is constructed. In the second step, the equivalent pores and fibers are embedded into matrix materials to build an RVE of the composite to calculate the elastic modulus of the composite. In addition, the 3D parametric FVDAM is further extended to simulate plastic deformation of PEEK matrix under quasi-static tensile loading. The results obtained from the proposed two-step modeling strategy have a good agreement with the results from experiments.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Composites Science and Technology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Composites Science and Technology, 218, 2022 DOI: 10.1016/j.compscitech.2021.109122