Multiple-objective aerodynamic optimization design of a radial air turbine impeller

In this paper, a numerical optimization of a radial turbine impeller is developed, which combines popular techniques such as artificial neural networks, genetic algorithm, database and CFD analysis tools. Multi-objective aerodynamic optimization is performed by using software FINETM/Design 3D. The performance parameters in the terms of total-to-static efficiency, expansion ratio are defined as optimized objectives. The performance of the new impeller is compared to the original one at the design point as well as at off-design points with a significant performance improvement. The design method provided very good predictions leading to an efficiency increase of 8.01 percent and an expansion ratio increase of 2.76 percent. An analysis of the CFD results is also discussed within the original and the new impeller. The whole results indicate that the multi-objective aerodynamic optimization process can be used in practical terms.