Turbine stage design aided by artificial intelligence methods

We propose a general, efficient system for designing turbine cascades and stages in real 3D-flow conditions. The presented algorithms involve application of evolutionary algorithms, as well as Artificial Neural Networks. Results of the design process are shown to be highly optimised in terms of efficiency, whereas computation time is reduced by several orders of magnitude in comparison to methods relying on Computational Fluid Dynamics calculations.