论文标题
流过孔径分级的膜孔网络
Flow through Pore-Size Graded Membrane Pore Networks
论文作者
论文摘要
孔径大小的梯度通常用于膜过滤器的设计中，以增加过滤器的寿命并确保更充分地使用初始膜孔体积。在这项工作中，我们在具有互连管状孔的内部网络的膜过滤器中施加了孔径大小的梯度。我们使用Hagen-Poiseuille框架与Advection Storewotwork通过液体和粒子通量的保护，并吸附为唯一的结垢机构，并通过守恒方程进行对流方程，并通过唯一的污染机制来建模流动和污垢传输。我们研究孔径梯度对诸如总滤液吞吐量等性能度量的影响，并在膜下游孔隙出口处累积的污染物浓度。在我们的建模假设的局限性中，我们发现有一个最佳的孔 - 拉迪乌斯梯度，该梯度可最大化过滤效率，而不是最大孔长度（影响孔网络结构的输入参数），并且具有较长特性孔长度的过滤效果更好。
Pore-size gradients are often used in the design of membrane filters to increase filter lifetime and ensure fuller use of the initial membrane pore volume. In this work, we impose pore-size gradients in the setting of a membrane filter with an internal network of interconnected tube-like pores. We model the flow and foulant transport through the filter using the Hagen-Poiseuille framework coupled with advection equations via conservation of fluid and particle flux, with adsorption as the sole fouling mechanism. We study the influence of pore-size gradient on performance measures such as total filtrate throughput and accumulated contaminant concentration at the membrane downstream pore outlets. Within the limitations of our modeling assumptions we find that there is an optimal pore-radius gradient that maximizes filter efficiency independent of maximum pore length (an input parameter that influences the structure of the pore network), and that filters with longer characteristic pore length perform better.
