The Tesla valve is a passive-type check valve used for flow control/rectification in a variety of micro/mini-channel systems. Previous studies have focused on its optimal design and effectiveness (i.e. diodicity) for the low-Reynolds number regime (Re < 500). Using three-dimensional (3D) CFD, multiple, identically-shaped Tesla valves arranged in-series, i.e.: a Tesla “tree” or multi-staged Tesla valve (MSTV), were investigated. Fully-developed flow at the inlet and complete-laminar conditions throughout the entire valve structure were imposed on all numerical simulations. The number of Tesla valves, valve-to-valve distance and Reynolds number were varied to determine their effect on MSTV diodicity. The individual Tesla valves within each MSTV possessed pre-optimized design parameters as reported from the literature. Results clearly indicate that the MSTV can provide for a significantly higher diodicity than a single Tesla valve and that this MSTV diodicity increases with Reynolds number. Minimizing the distance between adjacent Tesla valves can significantly increase the MSTV diodicity and, for very low Reynolds number (Re < 50), the MSTV diodicity is near-independent of valve-to-valve distance and number of valves used. In general, more Tesla valves are required to maximize the MSTV diodicity as the Reynolds number increases. The current investigation also demonstrates that 3D numerical simulations more accurately predict the diodicity of a single Tesla valve over a wider range of Reynolds numbers.
- Fluids Engineering Division
A Numerical Investigation of Multi-Staged Tesla Valves
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Thompson, SM, Walters, DK, Paudel, BJ, & Jamal, T. "A Numerical Investigation of Multi-Staged Tesla Valves." Proceedings of the ASME 2013 Fluids Engineering Division Summer Meeting. Volume 1A, Symposia: Advances in Fluids Engineering Education; Advances in Numerical Modeling for Turbomachinery Flow Optimization; Applications in CFD; Bio-Inspired Fluid Mechanics; CFD Verification and Validation; Development and Applications of Immersed Boundary Methods; DNS, LES, and Hybrid RANS/LES Methods. Incline Village, Nevada, USA. July 7–11, 2013. V01AT03A012. ASME. https://doi.org/10.1115/FEDSM2013-16269
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