Numerical and experimental investigation of 3D unsteady flow fields of a low head axial flow turbine under different blade number

Abstract

Low-head axial flow turbines (LHAFT) are important turbomachines suitable for converting low-head water (potential energy) into mechanical (kinetic) or electrical energy. The performance characteristics of this kind of turbine are an essential aspect of its design and operational life cycle. Nevertheless, pressure fluctuations within the turbine affect its operational reliability. Hence its fluctuation characteristics cannot be overlooked due to its influence on vibration, noise, and severity of performance. It is essential to investigate the zones associated with high unsteadiness and turbulence. Furthermore, blade number and variation in flow rate are other important, influential factors on the level of pressure fluctuations. Given the above, numerical and experimental investigation of pressure fluctuation intensities within the flow channels of the LHAFT model under different blade numbers was carried out in this study. The results posit that the pulsating pressure coefficient decreases gradually from the inflow to the guide vane but increases at the runner, then falls as the flow progresses in the outlet pipe. At the runner, the flow experienced the most irregular flow patterns in the turbine. All three runner cases were operated with nine guide vanes, but after one complete revolution, blade numbers z = 2, 3, and 4 revealed regular pressure fluctuations, respectively, in the stationary part (guide vane, inlet and outlet pipes). Regardless of the case study, nine (9) regular peaks and valleys of pressure pulses matching the number of vanes on the static vane were recorded in the runner flow passage. The flow interaction between the static vane and runner is responsible for the pressure fluctuation, which influences the turbine’s vibration and noise. The obtained results would be an essential reference to noise and vibration analytical studies in turbines to optimize them for improved operational reliability.