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Estimating filtration coefficients for straining from percolation and random walk theories

机译:根据渗流和随机游走理论估算过滤系数

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In this paper, laboratory challenge tests are carried out under unfavorable attachment conditions, so that size exclusion or straining is the only particle capture mechanism. The experimental results show that far above the percolation threshold the filtration coefficients are not proportional to the fractional flow through the pores smaller than the particles, but to the power-law functions of them. The experimental penetration depths of particles can be over thousands of pores even if the particle sizes are comparable to the average pore size. This observation cannot be explained by the traditional size exclusion theory or the model of parallel tubes with mixing chambers, where the filtration coefficients are proportional to the flux through smaller pores, and the predicted penetration depths are much lower. A special capture mechanism is proposed, which makes it possible to explain the experimentally observed power Jaw dependencies of filtration coefficients and large penetration depths of particles. Such a capture mechanism is realized in a 2D pore network model with periodical boundaries with the random walk of particles on the percolation lattice. Geometries of infinite and finite clusters formed by pores of the sizes exceeding the particle size are analyzed with regard to the possibility for particle capture. Two power laws are proposed to describe the filtration coefficients close and far away from the percolation threshold of the lattice. They can be applied to match the filtration coefficients from the network model well while one of them is used to match the experimental results. The application of such a model may lead to more accurate inverse determination of the pore size distributions from the challenge tests.
机译:在本文中,实验室挑战性测试是在不利的附着条件下进行的,因此尺寸排阻或拉紧是唯一的颗粒捕获机制。实验结果表明,过滤系数远高于渗滤阈值,它与流过小于颗粒的孔的分数流量不成比例,而是与它们的幂律函数成比例。即使颗粒尺寸与平均孔径相当,颗粒的实验渗透深度也可以超过数千个孔。这种观察不能用传统的尺寸排阻理论或带有混合室的平行管模型来解释,在该模型中,过滤系数与通过较小孔的流量成正比,并且预测的渗透深度要低得多。提出了一种特殊的捕获机制,这使得可以解释实验观察到的过滤系数和大颗粒穿透深度的功率颚依赖性。这种捕获机制是在具有周期性边界的二维孔隙网络模型中实现的,渗流晶格上的颗粒随机游动。关于颗粒捕获的可能性,分析了由尺寸超过颗粒大小的孔形成的无限和有限簇的几何形状。提出了两个幂定律来描述与晶格的渗滤阈值接近和远离的过滤系数。它们可以用来很好地匹配网络模型中的过滤系数,而其中之一则可以用来匹配实验结果。这种模型的应用可能会导致从挑战测试中更准确地确定孔径分布。

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