Optimization of Helical Microreactors by a Genetic Algorithm Technique

Micromixing in coiled microreactors is attained by a higher pressure drop and more pumping power. The optimum geometries of helically coiled microreactors were determined by multiobjective optimization based on a genetic algorithm (GA). The segregation index (X_s) values of the Villermaux/Dushman reaction were measured in twelve coiled microchannels. The effects of the geometries including curvature diameter and coil pitch on the mixing performance and pressure drop were investigated. The mixing performance of the microreactors and the pressure drop were considered as the GA objectives. The optimum geometries of the studied coiled microchannels with a trade-off between X_s and friction factors were obtained using GA-based multiobjective optimization.