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Stochastic Modeling of the Permeability of Randomly Generated Porous Media via the Lattice Boltzmann Method and Probabilistic Collocation Method

机译:随机生成的多孔介质渗透率的随机建模:格子Boltzmann方法和概率配置方法

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摘要

The permeability of natural porous media, such as soils and rocks, usually possesses uncertainties due to the randomness and spatial variation of microscopic pore structures. It is of great importance to develop an effective methodology to obtain statistical properties of permeability for porous media. In this work, an efficient approach is developed by combining the sphere packing algorithm, lattice Boltzmann method (LBM), and probabilistic collocation method (PCM). The porous media are generated by sphere packings of a specified size distribution, and the isotropy and representative elementary volume are verified by statistical analyses. Fluid flow in the complex pore structures is numerically resolved by LBM, with the permeability calculated by Darcy's law. The uncertainty of permeability can be quantified by PCM with only several porosity samplings required at predetermined collocation points. In addition, the porosity-permeability relationships can be acquired efficiently. Numerical results indicate that, with the proposed approach, the computational efforts are reduced by more than two orders of magnitude compared to the Monte Carlo simulations.
机译:天然多孔介质(如土壤和岩石)的渗透性通常由于微观孔隙结构的随机性和空间变化而具有不确定性。开发一种有效的方法来获得多孔介质渗透率的统计特性非常重要。在这项工作中,通过组合球体填充算法,晶格玻尔兹曼方法(LBM)和概率配置方法(PCM),开发了一种有效的方法。多孔介质是由具有指定尺寸分布的球形填料产生的,各向同性和代表性元素体积通过统计分析得到验证。复杂孔隙结构中的流体流动由LBM数值解析,渗透率由达西定律计算。渗透率的不确定性可以通过PCM定量,只需在预定的搭配点上进行几次孔隙率采样即可。另外,可以有效地获得孔隙率-渗透率关系。数值结果表明,与蒙特卡洛模拟相比,所提方法可以将计算量减少两个数量级以上。

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