Computational Methods for Predicting A Pico-Hydro CrossFlow Turbine Performance
Keywords:
computational, pico-hydro, cross-flow turbine, 6-DoF, preloadAbstract
Usually, to find out the maximum performance of a turbine, an experimental test is carried out using the loading (preload) variations method. The high proportion of torque (?) and runner rotation velocity (U) is an indication of maximum turbine performance. However, if there is mistaken in the shape of geometry it takes more time and funds. The correct solution is a prediction using the computational fluid dynamics (CFD) method. This study proposes the method to predict the maximum conditions of pico-hydro cross-flow turbines by comparing the preload acting on runners by CFD method. So, if something goes wrong in the design can be corrected immediately. The preloads variation in this study consists of 0 N·m, 30 N·m, 45 N·m, and 60 N·m with the head condition of 1 meter and mass flow of 10.5 kg/s. The CFD method with six-degree of freedom (6-DoF) was selected because the rotational turbine is one of the computational results not as boundary conditions. The turbulence model k-? standard has been used to predict the turbulent flow. Based on results, transient data (torque and runner rotational velocity) obtained from computing is similar to testing, which fluctuates and becomes steady. Furthermore, the used 45 N·m preload has more stable and had higher efficiency than the other. The turbine with 45 N·m preload produced 60.07% efficiency. This indicates that the turbine that is designed will work optimally at 45 N·m preload. Thus, CFD method with 6-DoF feature proposed to predict a pico-hydro cross-flow turbine performance can be an alternative before the turbine is manufactured to be tested or implemented.