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Synthetic Porous Microstructures: Automatic Design, Simulation, and Permeability Analysis
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This study introduces an open-source computational framework for the generation and permeability evaluation of synthetic porous media. The proposed methodology integrates crystallographic and meshing tools to construct controlled microstructures with tunable porosity, facilitating seamless transitions from geometric modelling to computational domains for numerical simulations. The generated structures are analysed through fluid-structure interaction (FSI) simulations, leveraging the Entropically Damped Artificial Compressibility (EDAC) formulation in conjunction with the Discretization-Corrected Particle Strength Exchange (DC-PSE) method. A novel approach for the numerical estimation of the macroscopic permeability tensor is presented, employing a stochastic upscaling technique inspired by the volume averaging method. To validate the framework, we investigate the transition between creeping and non-Darcy flow regimes through parametric permeability studies, utilizing a one-dimensional approach for practical benchmarking. The results establish a foundation for experimental validation and provide insights into the customised design of porous structures for engineering and biomedical applications, offering a versatile tool for research in fluid transport and porous media mechanics.
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Cited by 1 Pith paper
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Physics-Guided Generative AI for Property-Targeted 3D Porous Media Design
Joint surrogate-guided refinement of a conditional latent diffusion model and pVAE decoder improves simulator-verified directional permeability control for 3D porous media versus pVAE and frozen-decoder diffusion baselines.
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