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Computational fluid dynamics (CFD) is becoming an increasingly reliable tool for the design of water turbines. Using different CFD codes, it is possible to find out and compare criteria for classifying runner blade geometry regarding the strengths of their characteristics. The final decision of runner geometry, with demanding energetic and cavitation characteristics, always remains for the design engineer. To reach the final result, the engineer has to compare the flow analysis results of a great number of different geometries. To replace a part of this work, an optimization algorithm has been developed. This optimization procedure helps to check many more geometries with less human work. In this paper, a multiobjective genetic algorithm for the design of axial runners is presented. For the flow analysis, the CFX-TASC flow code, with a standard k-ɛ turbulence model, has been used, because the code enables calculation within a rotating frame of reference. For design of the initial geometry, within the optimization procedure, a special program has been developed, which makes it possible to start the optimization procedure with a relatively high level of efficiency and transforms prescribed genetic parameters to the runner geometry.

The paper presents a prediction of vortex rope in a draft tube obtained by the numerical flow analysis. The main goal of the research was to numerically predict pressure pulsation amplitude versus different guide vanes openings and compare the results with experimental ones. Three turbulent models (SAS-SST, ω-RSM and LES) were used. Also the effect of different domain configurations, grid density and time step size on results was examined. At first analysis was done without cavitation, while later at one operating point the cavitation model was included.

A comparison between numerical simulations and measurements of a six-blade Kaplan turbine is presented in order to determine an appropriate numerical setup for accurate and reliable simulations of Kaplan turbines. Values of discharge, torque and losses obtained by different turbulence models are compared to each other and to the measurements. Steady state simulations with various turbulence models tend to predict large errors at full discharge rate, which are the result of underestimated torque on the shaft and overestimated flow energy losses in the draft tube. The results were slightly improved with the curvature correction (CC) and Kato-Launder (KL) limiter of turbulence production. Transient simulations were performed with shear-stress-transport (SST) turbulence model, the scale-adaptive-simulation (SAS) SST model, and with zonal large-eddy-simulation (ZLES). Details about turbulent structures in the draft tube are illustrated in order to explain the reasons for differences in flow energy losses obtained by different turbulence models. The effects of advection schemes and mesh refinement were tested. It was shown that all of the transient simulations considerably improved results at full discharge rate. The largest improvement was achieved with the SAS SST and the ZLES models in combination with the bounded central differential scheme. In addition, it was shown that the ZLES model produced accurate results at all operating points, with discrepancy lower than 1%.

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