A novel artificial dual-phase microstructure generator based on topology optimization

Hou, Yuliang;Sapanathan, Thaneshan;Dumon, Alexandre;Culière, Pierre;Rachik, Mohamed
(2016) Computational Materials Science — Vol. 123, p. 188-200 (2016)

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Authors
  • Hou, Yuliang
    Author
  • Sapanathan, Thaneshanorcid-logoUCLouvain
    Author
  • Dumon, Alexandre
    Author
  • Culière, Pierre
    Author
  • Rachik, Mohamed
    Author
Abstract
The mechanical properties of dual-phase (DP) steel are mostly derived from its microstructure, e.g., volume fraction, size, distribution and morphology of each constituent phase. An artificial microstructure generator with an enhanced novel phase assignment algorithm based on material topology optimization is proposed to investigate the mechanical properties of DP steel. With this algorithm, phase assignment process is performed on a modified Voronoï tessellation to achieve the targeted representative volume element (RVE) with a good convergence. This method also includes a proper orthogonal decomposition (POD) reduction of flow curves (snapshots) to identify the optimal controlling parameters for DP steel. This numerical method significantly improves the representation of the generated RVE with low computational cost. The proposed method is verified using a DP590 steel which indicates a good agreement with experimental material behavior and RVE predictions based on real microstructures. Predictions of plastic strain patterns including shear bands using the artificial microstructure closely resemble the actual material behavior under similar loading conditions. Robustness of this approach provides a new dimension for RVE development based on artificial microstructure which can effectively be implemented in material characterization.
Affiliations
  • Université de Technologie de CompiègneLaboratoire Roberval

Citations

Hou, Y., Sapanathan, T., Dumon, A., Culière, P., & Rachik, M. (2016). A novel artificial dual-phase microstructure generator based on topology optimization. Computational Materials Science, 123, 188-200. https://doi.org/10.1016/j.commatsci.2016.06.020 (Original work published 2016)