Department of Environmental Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon, 22212, Republic of Korea.
Particle Technology Laboratory, Mechanical Engineering, University of Minnesota, 111 Church St., S.E., Minneapolis, 55455, USA.
Sci Rep. 2023 Apr 3;13(1):5449. doi: 10.1038/s41598-023-32765-4.
Computational fluid dynamics simulations of fibrous filters with 56 combinations of different fiber sizes, packing densities, face velocities, and thicknesses were conducted for developing models that predict pressure drops across nanofiber filters. The accuracy of the simulation method was confirmed by comparing the numerical pressure drops to the experimental data obtained for polyacrylonitrile electrospun nanofiber filters. In the simulations, an aerodynamic slip effect around the surface of the small nanofibers was considered. The results showed that, unlike in the case of conventional filtration theory, pressure drops across the thin layers of electrospun nanofiber filters are not proportional to the thickness. This might be a critical factor for obtaining precise pressure drops across the electrospun nanofiber filters with extremely thin layers. Finally, we derived the product of drag coefficient and Reynolds number as a function of packing density, Knudsen number, and ratio of thickness to fiber diameter to get the correlation equation for pressure drop prediction. The obtained equation predicted the pressure drops across the nanofiber filters with the maximum relative difference of less than 15%.
采用计算流体动力学方法，对具有 56 种不同纤维尺寸、堆积密度、迎面风速和厚度组合的纤维过滤器进行了模拟，旨在开发预测纳米纤维过滤器压降的模型。通过将数值压降与聚丙烯腈静电纺纳米纤维过滤器的实验数据进行比较，验证了模拟方法的准确性。在模拟中，考虑了小纤维表面的空气动力学滑移效应。结果表明，与传统过滤理论不同，静电纺纳米纤维过滤器薄层的压降与厚度不成比例。这可能是获得具有极薄层的静电纺纳米纤维过滤器精确压降的一个关键因素。最后，我们推导出阻力系数和雷诺数的乘积作为堆积密度、努森数和厚度与纤维直径比的函数，得到压降预测的关联式。得到的方程预测了纳米纤维过滤器的压降，最大相对误差小于 15%。
