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  • Open Access

    PROCEEDINGS

    A Phase-Field Framework for Modeling Cohesive Fracture and Multiple Crack Evolutions in Fiber-Reinforced Composites

    Liang Wang1,*, Haibo Su1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09107

    Abstract This work proposes a novel multi-phase-field formulation to characterize the distinct damage mechanisms and quasi-brittle fracture behaviors in FRC. The phase field driving forces for each failure mechanisms are first defined based on an anisotropic energy split scheme. Then, the PF degradation functions pertinent to each failure mode are properly defined with corresponding material fracture quantities, which enables the derivation of embedded Hashin failure criteria for fiber- and matrix failures respectively. Furthermore, the material damaged stiffness is redefined within the anisotropic CDM framework, and a linear CZM is mathematically derived for each of the typical More >

  • Open Access

    ABSTRACT

    Data Assimilation for Grain Growth Prediction via Multi-Phase-Field Models

    Hiromichi Nagao1,2,*, Shin-ichi Ito1,2, Tadashi Kasuya3, Junya Inoue4,3

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.2, pp. 127-127, 2019, DOI:10.32604/icces.2019.05384

    Abstract Data assimilation (DA) is a computational technique to integrate numerical simulation models and observational/experimental data based on Bayesian statistics. DA is accepted as an essential methodology for the modern weather forecasting, and is applied to various fields of science including structural materials science. We propose a DA methodology to evaluate unobservable parameters involved in multi-phase-field models with the aim of accurately predicting the observed grain growth, such as in metals and alloys. This approach integrates models and a set of observational image data of grain structures. Since the set of image data is not a… More >

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