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  • Open Access


    Phase-Field Simulation of Sintering Process: A Review

    Ming Xue, Min Yi*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1165-1204, 2024, DOI:10.32604/cmes.2024.049367

    Abstract Sintering, a well-established technique in powder metallurgy, plays a critical role in the processing of high melting point materials. A comprehensive understanding of structural changes during the sintering process is essential for effective product assessment. The phase-field method stands out for its unique ability to simulate these structural transformations. Despite its widespread application, there is a notable absence of literature reviews focused on its usage in sintering simulations. Therefore, this paper addresses this gap by reviewing the latest advancements in phase-field sintering models, covering approaches based on energy, grand potential, and entropy increase. The characteristics More >

  • Open Access


    Oscillations of Rapid Fracture in Phase Field Modeling

    Jun Zeng1, Fucheng Tian1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09636

    Abstract Instability in dynamic fracture suppresses crack velocity from reaching theoretical limit predicted by the classical linear elastic fracture mechanics (LEFM). In thin systems, crack can accelerate to near the theoretical limiting velocity without micro-branching instability. A dynamic oscillatory instability is observed at such extreme crack speed. This sinusoidal oscillation was further found to be governed by intrinsic nonlinear scale. Using a dynamic phase-field model (PFM) with no attenuation of wave speed, we successfully reproduce the oscillations in the framework of non-linear deformation. The used PFM model based on Griffith's theory and derived from the nonconservative… More >

  • Open Access


    Uncovering the Intrinsic Deficiencies of Phase-Field Modeling for Dynamic Fracture

    Jiale Ji1,*, Mengnan Zhang1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09632

    Abstract The phase-field fracture (PFF) approach has achieved great triumphs in modeling quasi-static fracture. Nevertheless, its reliability in serving dynamic fractures still leaves something to be desired, such as the prediction of the limiting crack velocity. Using a pre-strained fracture configuration, we discovered a disturbing phenomenon that the crack limiting speed identified by the dynamic PFF model is not related to the specific material, which seriously deviates from the experimental observation. To ascertain the truth, we first ruled out the correlation between the limiting crack velocity on the phase-field characteristic scale and external loading. Afterward, by More >

  • Open Access


    Improved Staggered Algorithm for Phase-Field Brittle Fracture with the Local Arc-Length Method

    Zhijian Wu, Li Guo*, Jun Hong

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 611-636, 2023, DOI:10.32604/cmes.2022.020694

    Abstract The local arc-length method is employed to control the incremental loading procedure for phase-field brittle fracture modeling. An improved staggered algorithm with energy and damage iterative tolerance convergence criteria is developed based on the residuals of displacement and phase-field. The improved staggered solution scheme is implemented in the commercial software ABAQUS with user-defined element subroutines. The layered system of finite elements is utilized to solve the coupled elastic displacement and phase-field fracture problem. A one-element benchmark test compared with the analytical solution was conducted to validate the feasibility and accuracy of the developed method. Our More >

  • Open Access


    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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