在多孔介质中弥合尺度：基于经典密度泛函理论的孔隙网络建模用于具有纳米受限相行为的流体传输
Bridging scales in porous media: cDFT-informed pore network modelling for fluid transport with nanoconfined phase behavior
AI总结：
本文提出一种多尺度过滤框架，结合孔隙网络建模和经典密度泛函理论，用于预测纳米受限相行为下的流体传输，研究孔隙结构和热力学条件对渗透率的影响。
摘要：
真实多尺度多孔介质中流体流动的模拟仍具挑战性，由于纳米尺度现象的复杂性和开发尺度提升方法的困难。本文介绍了一种基于准静态孔隙网络建模的多尺度过滤框架，结合毛细管凝结对纳米孔隙空间中孔隙阻塞的影响。为准确预测纳米受限中的毛细管凝结，我们应用经典密度泛函理论计算考虑毛细管滞后效应。被凝结物阻塞的孔隙被排除在流体流动之外，导致孔隙空间渗透率降低。我们的研究结果表明，所得渗透率强烈依赖于孔隙空间的几何结构，包括孔隙尺寸分布、喉部尺寸分布、样品尺寸以及样品的特定结构，以及热力学条件和过程，特别是压力增长或减少。总体而言，本文的研究为多尺度传输现象提供了有价值的见解，并促进了尺度提升技术的发展。
英文摘要：
The simulation of fluid flow in real, multiscale porous media remains challenging due to the complexity of nanoscale phenomena and the difficulty of developing upscaling methodologies. In this study, we introduce a multiscale filtration framework based on quasi-static Pore Network Modelling, incorporating the effects of pore blockage resulting from capillary condensation of fluid in the nanoporous space. To accurately predict capillary condensation in nanoconfinement, we apply classical Density Functional Theory calculations considering capillary hysteresis. The pores blocked by condensate are excluded from the fluid flow, resulting in a decrease in permeability of the porous space. Our findings demonstrate that the resulting permeability is strongly dependent on the geometry of the porous space, including pore size distribution, throat size distribution, sample size, and the particular structure of the sample, as well as thermodynamic conditions and processes, specifically pressure growth or decrease. Overall, the presented research contributes valuable insights into multiscale transport phenomena and facilitates the advancement of upscaling techniques.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
