AN OPTIMIZATION OF ANTI-ICING CHAMBER BASED ON POD AND KRIGING

Due to the small load and the limited energy supply ice accretion on the unmanned aerial vehicles (UAVs) has limited the UAVs flight in good weather conditions. To take advantage of the energy of the UAVs as the anti/de-icing energy source may improve the UAVs application. The engine exhaust has a potential as a hot air source used for the anti-icing system. The hot air anti-icing chamber is designed and optimized. The most critical in-flight icing conditions is identified and the basic hot air anti-icing chamber is designed. The location of the piccolo tube, the angle between the jet holes are set as the design variables. The optimized latin hypercubic sampling (OLHS) is utilized and the numerical simulations are conducted. The surrogate model is built based on the proper orthogonal decomposition (POD) and Kriging interpolation. The hot air anti-icing chamber is optimized with the genetic algorithm (GA). The methodology can greatly reduce the time cost of the optimization and successfully results in optimal configurations of the anti-icing chamber.