A concurrent three-scale scheme FE-SCA 2 for the nonlinear mechanical behavior of braided composites
Computer Methods in Applied Mechanics and Engineering, ISSN: 0045-7825, Vol: 393, Page: 114827
2022
- 18Citations
- 14Captures
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Article Description
An efficient and accurate multiscale modeling for the mechanical behavior of braided composites with complex microstructure is an outstanding challenge in the mechanics of composite materials. In this work, a concurrent three-scale scheme FE-SCA 2 is proposed for predicting the macroscopic nonlinear behavior of braided composites associated with the microscopic plastic and damage of the constituents, where FE and SCA are short for finite element method and self-consistent clustering analysis, respectively. In this concurrent scheme, the macroscale behavior of the braided composites is handled by FE analysis, and the microscale and mesoscale behavior of the constituents are handled by SCA simultaneously with the data-driven clustering discretization. To demonstrate the accuracy and efficiency of the proposed scheme, we first predict the asymmetric anisotropic yield and failure surfaces for braided composites and then analyze the nonlinear behavior of a braided composite plate under bending. The computational results are compared with FE method results and experimental data from the literature, with good agreement in cases where such data is available. It is shown that the microscale, mesoscale, and macroscale nonlinear behavior of braided composites can be captured simultaneously using the proposed FE-SCA 2, which would be difficult to be characterized by experimental methods. The proposed multiscale method could be applied for composite structures with various properties of micro-structures and constituents to expedite the design and structural optimization.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0045782522001451; http://dx.doi.org/10.1016/j.cma.2022.114827; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85126903519&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0045782522001451; https://dx.doi.org/10.1016/j.cma.2022.114827
Elsevier BV
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