Optimization of passive grooved micromixers based on genetic algorithm and graph theory

This paper proposes a novel approach for fluid topology optimization using genetic algorithm. In this study, the enhancement of mixing in the passive micromixers is considered. The efficient mixing is achieved by the grooves attached on the bottom of the microchannel and the optimal configuration of grooves is investigated. The grooves are represented based on the graph theory. The mixing performance is analyzed by a CFD solver and the exploration by genetic algorithm is assisted by the Kriging model to reduce the computational cost. The characteristics of the convex and the concave grooves are compared. To balance the global exploration and the reasonable computational cost, this paper investigates three cases with the convex grooves subject to constraint that differs in handling of design variables. In each case, genetic algorithm finds several local optima since the objective function is a multi-modal function, and these optima reveal the specific characteristic for efficient mixing. Moreover, this paper optimizes the micromixer with the concave grooves and reveals the different properties of the mixing. Finally, to guarantee the obtained solutions competitive, the sensitivity analysis is performed to the best solution in each case.