| description abstract | The Tesla valve is a passivetype check valve used for flow control in microor minichannel systems for a variety of applications. Although the design and effectiveness of a singular Tesla valve is somewhat well understood, the effects of using multiple, identically shaped Tesla valves in series—forming a multistaged Tesla valve (MSTV)—have not been well documented in the open literature. Therefore, using highperformance computing (HPC) and threedimensional (3D) computational fluid dynamics (CFD), the effectiveness of an MSTV using Tesla valves with preoptimized designs was quantified in terms of diodicity for laminar flow conditions. The number of Tesla valves/stages (up to 20), valvetovalve distance (up to 3.375 hydraulic diameters), and Reynolds number (up to 200) was varied to determine their effect on MSTV diodicity. Results clearly indicate that the MSTV provides for a significantly higher diodicity than a single Tesla valve and that this difference increases with Reynolds number. Minimizing the distance between adjacent Tesla valves can significantly increase the MSTV diodicity, however, for very low Reynolds number (Re < 50), the MSTV diodicity is almost independent of valvetovalve distance and number of valves used. In general, more Tesla valves are required to maximize the MSTV diodicity as the Reynolds number increases. Using datafitting procedures, a correlation for predicting the MSTV diodicity was developed and shown to be in a powerlaw form. It is further concluded that 3D CFD more accurately simulates the flow within the Tesla valve over a wider range of Reynolds numbers than 2D simulations that are more commonly reported in the literature. This is supported by demonstrating secondary flow patterns in the Tesla valve outlet that become stronger as Reynolds number increases. Plots of the pressure and velocity fields in various MSTVs are provided to fully document the complex physics of the flow field. | |
