Chaotic evolutionary algorithms for dynamic instability enhancement

The algorithm principle is presented based on a geometry optimization of aeroelastic energy harvester. Efficiency of this class of devices highly depends on oscillation amplitude caused by dynamic instability of the system, which is related to its geometry. Optimization was performed using a genetic algorithm (GA) that processes data from CFD calculations. This algorithm generated a random population of twenty-arm geometrical figures. Each geometry was subjected to a numerical experiment during which its movement in a fluid-filled channel were simulated and resultant force acting on body was calculated. The calculations were repeated for angular orientation of the object varying from 0 to 180 degrees, at 5 degrees step, in order to obtain a complete characteristic of aerodynamical forces acting on body related to its angular orientation. For each of the obtained functions, satisfaction of Den Hartog's criterion is examined, which is the basis for geometry evaluation. In order to accelerate the calculations, classical GA has been modified by substituting random crossover process by operation determined by chaotic process — in this case, a logistic map. The numerical calculations was carried by Method of Fundamental Solutions. (paper)