Although the micro-channels of typical lab-on-a-chip micro-fluidic devices are connected to reservoirs, existing analyses of the flow physics within the micro-channels frequently ignore the end effects induced by these reservoirs. Accordingly, this study presents an analytical and numerical investigation into electro-osmotic flow (EOF) which takes into account the end effects associated with the inlets and outlets of the micro-channels. The results indicate that the EOF contractions and expansions which occur in the inlet and outlet regions, respectively, induce streamwise pressure gradients, which result in non-flat EOF velocity profiles within the micro-channel. Furthermore, it is proven theoretically that this pressure gradient eventually vanishes once the micro-channel becomes sufficiently long that the end effects no longer exert an influence on the flow. An empirical relation between the entrance length and Reynolds number is established via parametric studies.

Electroosmotic flow (EOF) in microchannels is restricted to low Reynolds number regimes. Since the inertial forces are extremely weak in such regimes, turbulent conditions do not readily develop. Therefore, species mixing occurs primarily via diffusion, with the result that extended mixing channels are generally required. The present study considers a T-shaped microchannel configuration with a mixing channel of width W=280 µm. Computational fluid dynamics simulations and experiments were performed to investigate the influence on the mixing efficiency of various geometrical parameters, including the side-channel width, the side-channel separation, and the number of side-channel pairs. The influence of different applied voltages is also considered. The numerical results reveal that the mixing efficiency can be enhanced to yield a fourfold improvement by incorporating two pairs of side channels into the mixing channel. It was also found that the mixing performance depends significantly upon the magnitudes of the applied voltages.

Computational fluid dynamics (CFD) allows the visualization and understanding of physics of flow associated with stent implantation. This study uses patient computed tomography (CT) images to investigate the relationship of pressure drop and air flow rate in the tracheal airway. Moreover, the cross-sectional areas of the patient airway were measured and the area stenosis ratios were calculated. The stenosis ratios were 75.64% and 38.08% without and with stent treatment, respectively. Simulation results show that at an air flow rate of 30 L/min, the pressure drops between the inlet and the outlet before and after central airway stent implantation for the inspiratory phase were 77.23 and 7.05 Pa, respectively. The improvement gain (IG) was 9.95. The IG increased with increasing air flow rate. At an air flow rate of 120 L/min, the value of IG was 11.68. A higher IG value indicates lower airway resistance after an airway stent implantation. The CFD numerical results demonstrate the feasibility of computing airway resistance based on CT images. In clinical practice, it is difficult to assess patients with severe airway obstruction using a symptoms score or a pulmonary function test due to their critical condition. The proposed noninvasive approach for determining airway obstruction severity is helpful for patients who are unable to do pulmonary function tests.

No abstract