For the presented thesis a genetic algorithm optimization framework was developed that allowed for several kinematic evolutions towards different objectives on an oscillating panel in forward motion. The genetic algorithm proved to be a robust tool in finding optimal solutions in an unknown and highly non-linear solution space. The optimization framework was applicable to computational models and the experimental pitching panel apparatus, designed and constructed for this work. Multiple optimizations for different design functions were carried out, yielding enticing developments for the characteristic flow parameters.
The genetic algorithm optimization framework was implemented with Matlab and tested on a potential flow theory model. This provided a quick and accessible development environment for the software. Once the framework was implemented and tested on the model, a pitching panel apparatus was designed and built for a pump-driven water channel facility.