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Ability of a pore network model to predict fluid flow and drag in saturated granular materials

机译:孔网络模型能够预测流体流动和饱和颗粒材料的拖动

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The local flow field and seepage induced drag obtained from Pore Network Models (PNM) is compared to Immersed Boundary Method (IBM) simulations, for a range of linear graded and bimodal samples. PNM were generated using a weighted Delaunay Tessellation (DT), along with the Modified Delaunay Tessellation (MDT) which considers the merging of tetrahedral Delaunay cells. Two local conductivity models are compared in simulating fluid flow in the PNM. The local pressure field was very accurately captured, while the local flux (flow rate) exhibited more scatter and sensitivity to the choice of the local conductance model. PNM based on the MDT clearly provided a better correlation with the IBM. There was close similarity in the network shortest paths, indicating that the PNM captures dominant flow channels. Comparison of streamline profiles demonstrated that local pressure drops coincided with the pore constrictions. A rigorous validation was undertaken for the drag force calculated from the PNM by comparing with analytical solutions for ordered array of spheres. This method was subsequently applied to all samples, and the calculated force was compared with the IBM data. Linear graded samples were able to calculate the force with reasonable accuracy, while the bimodal samples exhibited slightly more scatter.
机译:将从孔网络模型(PNM)获得的局部流场和渗流引起的阻力与浸没的边界法(IBM)模拟进行比较,用于一系列线性分级和双峰样本。使用加权Delaunay曲面细胞化(DT)产生PNM,以及考虑四面体Delaunay细胞的合并的改性Delaunay曲面细胞(MDT)。将两种局部电导率模型进行比较在PNM中模拟流体流动。局部压力场非常精确地捕获,而局部通量(流量)对局部电导模型的选择表现出更多的散射和敏感性。基于MDT的PNM清楚地提供了与IBM更好的相关性。网络最短路径中存在密切相似性,表明PNM捕获了主流流动通道。流线线简档的比较证明局部压降与孔隙收缩一致。通过与有序球体阵列的分析解决方案进行比较,对从PNM计算的阻力进行严格的验证。随后将该方法应用于所有样品,并将计算的力与IBM数据进行比较。线性分级样品能够以合理的精度计算力,而双峰样品略有散布。

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