Multiscale pore‐network reconstruction of a fine‐textured heterogeneous soil

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-06-05 DOI:10.1002/vzj2.20354
E. Pontedeiro, M. V. van Genuchten, William Godoy, M. G. Ramirez, Carlos M. P. Vaz, Silvio Crestana, Maira C. O. Lima, Paulo Couto, Jian Su
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Abstract

Digital samples offer many opportunities to study subsurface fluid flow and contaminant transport processes. The pore size distribution of especially fine‐textured porous media often covers many orders of magnitude in the length scale, which makes accurate microCT scanning and modeling of the underlying processes difficult. When a single‐resolution image is not capable of capturing all relevant details of a sample, one should scan the sample, or selected parts of it, at different resolutions. Combining multiple resolutions into one single sample for subsequent pore‐scale modeling is generally not possible due to limitations in computer memory and speed, thus making it necessary to create a simpler sample containing relevant information from the parent networks. We imaged four samples using different resolutions to capture the multiscale heterogeneity of a fine‐textured soil and combined them into one overall digital sample based on the original pore networks. The parent networks were characterized using their geometrical properties, correlations between these properties, and connectivity functions describing the network topologies. Our approach creates stochastic networks of arbitrary size with the same flow properties as the parent network. The method, implemented using the PoreStudio pore network model, repeatedly integrates information at two subsequent scales, with the resulting digital sample having the same hydraulic properties as the original samples. The procedure leads to more useful three‐dimensional digital models, facilitating basic analyses of underlying pore size distributions. Porosity calculations were compared with direct measurements, while those for the hydraulic conductivity were compared with estimates based on the particle size distribution and nearby field data.
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细粒度异质土壤的多尺度孔隙网络重建
数字样本为研究地下流体流动和污染物迁移过程提供了许多机会。特别是质地细密的多孔介质,其孔径分布在长度尺度上往往覆盖许多数量级,这就给精确的 microCT 扫描和底层过程建模带来了困难。当单一分辨率图像无法捕捉到样品的所有相关细节时,就需要用不同分辨率扫描样品或样品的选定部分。由于计算机内存和速度的限制,通常不可能将多个分辨率的图像合并成一个单一样本,以进行后续的孔隙尺度建模,因此有必要创建一个包含母网络相关信息的更简单样本。我们使用不同分辨率对四个样本进行了成像,以捕捉细粒度土壤的多尺度异质性,并根据原始孔隙网络将它们合并为一个整体数字样本。我们利用母体网络的几何特性、这些特性之间的相关性以及描述网络拓扑结构的连通性函数对其进行了表征。我们的方法可以创建任意大小的随机网络,其流动特性与母网络相同。该方法利用 PoreStudio 孔隙网络模型实现,在随后的两个尺度上重复整合信息,得到的数字样本具有与原始样本相同的水力特性。该程序可生成更有用的三维数字模型,有助于对潜在孔隙大小分布进行基本分析。孔隙率计算结果与直接测量结果进行了比较,而水力传导率计算结果则与根据粒度分布和附近实地数据估算的结果进行了比较。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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