Stochastic optimisation based control of boundary layer transition

Abstract

Abstract Suction is one of the most promising techniques for delaying the transition from laminar to turbulent flow and hence reducing the drag force acting on an aircraft. However, in order to achieve an overall reduction in energy consumption and thereby operating costs, it is necessary to apply the suction in an efficient if not optimal manner. An investigation is conducted into the use of distributed surface suction with multiple suction panels where the suction distribution is optimised to satisfy a desired objective. Cost functions based on minimising the suction effort while maintaining transition in a fixed position and minimising the total energy consumption of the system are employed. Evolutionary methods, genetic algorithms (GA) and simulated annealing (SA), are used to perform the optimisation. These methods were successful in cases in which gradient based search techniques fail. Physically sensible suction distributions were produced. In general, better behaviour was found with the GA than with SA, which was prone to premature convergence.