A design optimization based on coupled solid–fluid analysis is investigated in this work to achieve specific flow rate through a peristaltic micropump. A micropump consisting of four pneumatically actuated nozzle/diffuser shaped moving actuators on the sidewalls is considered for numerical study. These actuators are used to create pressure difference in the four pump chambers, which in turn drives the fluid through the pump in one direction. Genetic algorithms along with artificial neural networks are used for optimizing the pump geometry and the actuation frequency. A simple example with moving walls is considered for validation by developing an exact analytical solution of Navier–Stokes equation and comparing it with numerical simulations. Possible applications of these pumps are in microelectronics cooling and drug delivery. Based on the results obtained from the fluid–structure interaction analysis, three optimized geometries result in flow rates which match the predicted flow rates with 95% accuracy. These geometries need further investigation for fabrication and manufacturing issues
