Manufacturing Technology 2020, 20(4):453-458 | DOI: 10.21062/mft.2020.072

Application of genetic algorithm methods for water turbine blade shape optimization

Martin Kantor¹, Milan Chalupa¹, Jiří Souček², Eva Bílková², Petr Nowak²

¹ Faculty of Mechanical Engineering, J. E. Purkyně University, Adress: Na Okraji 1001/7, Ústí nad Labem 400 01 Czech Republic

² Faculty of Civil Engineering, Czech Technical University in Prague, Adress: Thákurova 7, Praha 166 29 Czech Republic

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.

Keywords: low head Kaplan turbine, Optimization, CFD simulations, FEA simulations, 3D printing

Grants and funding:

The project of Innovative Design of Compact Unit of Kaplan Micro-Turbine TH04010140, the Technology Agency of the Czech Republic within the Epsilon Program.

Received: May 1, 2020; Revised: August 31, 2020; Accepted: September 24, 2020; Prepublished online: November 23, 2020; Published: December 8, 2020  Show citation