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Inertial Particle Separation in Curved Networks: A Numerical Study
Chemical Engineering Science ( IF 4.7 ) Pub Date : 2018-06-01 , DOI: 10.1016/j.ces.2018.02.029
Ali Dinler , Inci Okumus

Abstract To rapidly separate and isolate specific-sized particles by inertial focusing from biological samples, microfluidic networks with curved branches have become subject of prototyping. However, determining the optimal channel dimensions for size-based separation is challenging due to the sophisticated fluid-particle interactions and high sensitivity of the inertial forces to the channel geometry. In the first part of the study, hydrodynamic forces acting upon the particle in the existence of the Dean vortices are modeled and simulated. Simulations are validated with available experimental data. Then, a series of computational experiments is run for various curvatures and cross-section sizes, and translocation of particles through curved branches is projected. Width of the focusing band is predicted for different-sized particles. Occurrences of a narrow (high-quality) focusing, dispersion of the particles (no focusing) and split of the focusing band are also determined. Nevertheless, a considerable pressure drop is expected due to the narrow and high curvature daughters of the considered network. A design rule is not available to resolve this problem and the Murray’s law is not valid for curved daughters. Therefore, in the second part of the study, an optimum design formulation for restraining the hydraulic resistance inside such networks is developed and tested. The proposed formulation can be practiced to predict the optimum length, curvature and aspect ratio of the daughter branches for such inertial separation networks.

中文翻译:

弯曲网络中的惯性粒子分离:数值研究

摘要 为了通过惯性聚焦从生物样品中快速分离和分离特定尺寸的粒子,具有弯曲分支的微流体网络已成为原型设计的主题。然而,由于复杂的流体-颗粒相互作用和惯性力对通道几何形状的高度敏感性,确定基于尺寸分离的最佳通道尺寸具有挑战性。在研究的第一部分,对存在迪安涡流时作用在粒子上的流体动力进行建模和模拟。模拟得到了可用的实验数据的验证。然后,针对各种曲率和横截面尺寸运行一系列计算实验,并预测粒子通过弯曲分支的易位。预测不同尺寸粒子的聚焦带宽度。还确定了窄(高质量)聚焦、粒子分散(无聚焦)和聚焦带​​分裂的发生。然而,由于所考虑网络的狭窄和高曲率子体,预计会有相当大的压降。没有可用的设计规则来解决这个问题,并且默里定律对弯曲的女儿无效。因此,在研究的第二部分,开发并测试了用于抑制此类网络内部水力阻力的最佳设计公式。可以实践所提出的公式来预测此类惯性分离网络的子分支的最佳长度、曲率和纵横比。由于所考虑网络的狭窄和高曲率子体,预计会有相当大的压降。没有可用的设计规则来解决这个问题,并且默里定律对弯曲的女儿无效。因此,在研究的第二部分,开发并测试了用于抑制此类网络内部水力阻力的最佳设计公式。可以实践所提出的公式来预测此类惯性分离网络的子分支的最佳长度、曲率和纵横比。由于所考虑网络的狭窄和高曲率子体,预计会有相当大的压降。没有可用的设计规则来解决这个问题,并且默里定律对弯曲的女儿无效。因此,在研究的第二部分,开发并测试了用于抑制此类网络内部水力阻力的最佳设计公式。可以实践所提出的公式来预测此类惯性分离网络的子分支的最佳长度、曲率和纵横比。开发并测试了一种用于抑制此类网络内部水力阻力的最佳设计公式。可以实践所提出的公式来预测此类惯性分离网络的子分支的最佳长度、曲率和纵横比。开发并测试了一种用于抑制此类网络内部水力阻力的最佳设计公式。可以实践所提出的公式来预测此类惯性分离网络的子分支的最佳长度、曲率和纵横比。
更新日期:2018-06-01
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