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  • Open Access

    PROCEEDINGS

    Series-Parallel Machine Learning-Generated Five-Site Water Models for Ice Ih and Liquid: TIP5P-BG and TIP5P-BGT

    Jian Wang1,*, Haitao Hei1, Yonggang Zheng1, Hongwu Zhang1, Hongfei Ye1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.010916

    Abstract Icing is a ubiquitous phenomenon in nature and widely observed in the micro/nanoconfinement, e.g., two-dimensional ice growth on Au surface, nanoconfinement-induced phase change, nanodroplet freezing on surface, etc. These complicated and abstruse processes and behaviours demand deep understanding from the microscale level by the aid of molecular dynamics (MD) simulation [1]. However, it is still a great challenge to accurately describe the ice and liquid water simultaneously with the present water models [1,2]. In response to this, we propose a series-parallel machine learning (ML) approach consisting of classification back-propagation neural network (BPNN), parallel regression BPNNs… More >

  • Open Access

    PROCEEDINGS

    A Four-Site Water Model for Liquid and Supercooled Water Based on Machine Learning: TIP4P-BGWT

    Jian Wang1,*, Yonggang Zheng1, Hongwu Zhang1, Hongfei Ye1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.09761

    Abstract Water is the most ubiquitous fluid in nature and widely exists in the micro/nanoconfinement of leafstalks, shale, bones, etc. The complex relation of the properties and behaviours of water to the temperature, pressure and confinement size enhances the difficulty in the accurate simulation, such as the supercooled state of pure water below the freezing point. As a powerful tool, molecular dynamics simulation is adequate for investigating the relevant properties and behaviours. However, accurately calculating the physical properties of liquid and supercooled water is quite challenging by molecular simulations owing to limited model parameters. Machine learning… More >

  • Open Access

    ARTICLE

    LIQUID WATER DYNAMIC BEHAVIORS IN THE GDL AND GC OF PEMFCS USING LATTICE BOLTZMANN METHOD

    Li Chen, Hui-Bao Luan, Wen-Quan Tao*

    Frontiers in Heat and Mass Transfer, Vol.1, No.2, pp. 1-11, 2010, DOI:10.5098/hmt.v1.2.3002

    Abstract Multi-phase lattice Boltzmann method is applied to investigate liquid water transport in th GDL and GC. The liquid water transport processes in the GDL, near the GDL-GC interfaces and in the GC are discussed. The effects of channel land on liquid water dynamic behaviors and distribution in the GDL and GC are investigated. It is found that channel land covers the GDL-GC interface where liquid water reaches changes the water distribution near the GDL-GC interface and in the GC. While channel land is apart from the GDL-GC interface where liquid water reaches changes the effects More >

  • Open Access

    ARTICLE

    A Unified Approach to Numerical Modeling of Fully and Partially Saturated Porous Materials by Considering Air Dissolved in Water

    D. Gawin1, L. Sanavia2

    CMES-Computer Modeling in Engineering & Sciences, Vol.53, No.3, pp. 255-302, 2009, DOI:10.3970/cmes.2009.053.255

    Abstract This paper presents a unified mathematical approach to model the hydro-thermo-mechanical behavior of saturated and partially saturated porous media by considering the effects of air dissolved in liquid water. The model equations are discretized by means of the Finite Element method. A correspondingly updated code is used to analyze two examples; the first one is the well known Liakopoulos test, i.e. the drainage of liquid water from a 1m column of sand, which is used to validate numerically the model here developed. As second example, a biaxial compression test of undrained dense sands where cavitation More >

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