4.7 Article

Prediction of non-linear mechanical behavior of shear deformed twill woven composites based on a multi-scale progressive damage model

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COMPOSITE STRUCTURES
卷 224, 期 -, 页码 -

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ELSEVIER SCI LTD
DOI: 10.1016/j.compstruct.2019.111019

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资金

  1. Industrial Strategic technology development program - Ministry of Trade, Industry & Energy (MI, Korea) [10076562]
  2. National Research Foundation of Korea (NRF) - Ministry of Education [2012R1A6A1029029, 2013M2A2A9043280, 2018R1D1A1A09083236]
  3. Hanyang University
  4. Hyundai Motors Co. Ltd.
  5. National Research Foundation of Korea [2018R1D1A1A09083236, 2013M2A2A9043280] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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In this paper, the non-linear mechanical behavior of shear deformed woven composite was predicted using a representative volume element (RVE) model based on multi-scale progressive failure analysis. The micro-scale RVE model, consisting of single fiber and a matrix, was employed to determine the stress amplification factor and distinguish the failure of each fiber and the matrix constituent. Then, a meso-scale RVE model of shear deformed twill woven composite was developed to predict non-linear behavior using micro-stress transferring with finite element simulation. Fiber yarn shapes were observed with respect to the shear angle of the twill fabric. Based on the observed yarn geometry, shear deformed twill composite was modeled by using the open source software TexGen. To prove validity of the proposed model, shear deformed twill woven composite was fabricated using a picture frame, followed by a vacuum assisted resin transfer molding process. Mechanical tests were conducted and the failure progress during the tests was observed to determine their failure analysis. As a result, a good correlation between the multi-scale progressive damage model and experimental results such as mechanical properties, the non-linear stress-strain curve, and failure modes were achieved.

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