Optimum design for the Tesla micromixer

An optimal design for high mixing index and low-pressure drop in a two-dimensional Tesla-shaped micromixer with a laminar fluid flow regime was studied in the present work. The genetic algorithm is utilized for obtaining optimum structural design. The image processing method has been utilized to identify the edges of the micromixer to generate mesh configuration over the computational field. The governing equations of laminar fluid flow and additionally concentration equations are discretized and solved by the finite volume method. All generated micromixer structural configurations as a prototype by the genetic algorithm approach were evaluated individually. The best design was obtained by rotating central obstacles of the Tesla micromixer with an optimum value of mixing cost that is a function of two target parameters (i.e., mixing index at outlet and pressure drop of the passing fluid flow through the channel). It is observed that the obtained optimum design in the present study has a lower mixing cost. Therefore, a better performance was obtained than the original type of the Tesla micromixer in acceptable ranges of the passing fluid flow rates.

Automated summary

This study investigates the optimal design of a two-dimensional Tesla-shaped micromixer for high mixing index and low-pressure drop. The genetic algorithm is used to obtain the optimum structural design, and image processing is used to identify the micromixer edges and generate a mesh configuration. The governing equations of laminar fluid flow and concentration are discretized and solved using the finite volume method. The best design is achieved by rotating the central obstacles of the Tesla micromixer, resulting in a lower mixing cost and better performance than the original design.