PT Journal
AU Kantor, M
   Chalupa, M
   Soucek, J
   Bilkova, E
   Nowak, P
TI Application of genetic algorithm methods for water turbine blade shape optimization
SO Manufacturing Technology Journal
PY 2020
BP 453
EP 458
VL 20
IS 4
DI 10.21062/mft.2020.072
DE low head Kaplan turbine; Optimization; CFD simulations; FEA simulations; 3D printing
AB The use of modern production techniques such as 3D printing brings new requirements for shaping ma-chine parts. In the case of the production of the runner blades of Kaplan micro-turbine using 3D printing technology from plastic, the emphasis is on the mechanical properties of the blade and hydraulic proper-ties of the entire turbine. Achieving the required parameters is conditioned by finding a suitable shape of the runner. Therefore the design, virtual testing, optimization and evaluation process is automated. The paper describes the whole process where virtual testing of hydraulic parameters is performed by CFD simulations, and the methods of genetic algorithms are used for optimization. Selected final geometrical shapes of the blade are subjected to a more detailed analysis of hydraulic parameters in the wider oper-ating range and also to the strength analysis.
ER