2019 Volume 12 Issue 4 Pages 400-417
Many consider the Pelton turbine a mature technology, nevertheless the advent of Computational Fluid Dynamics (CFD) in recent decades has been a key driver in the continued design development. Impulse turbine casings play a very important role and experience dictates that the efficiency of a Pelton turbine is closely dependent on the success of keeping vagrant spray water away from the turbine runner and the water jet. Despite this overarching purpose, there is no standard design guidelines and casing styles vary from manufacturer to manufacturer, often incorporating a considerable number of shrouds and baffles to direct the flow of water into the tailrace with minimal interference with the aforementioned. The present work incorporates the Reynolds-averaged Navier Stokes (RANS) k-ɛ turbulence model and a two-phase Volume of Fluid (VOF) model, using the ANSYS® FLUENT® code to simulate the casing flow in a 2-jet horizontal axis Pelton turbine. The results of the simulation of two casing configurations are compared against flow visualisations and measurements obtained from a model established at the National Technical University of Athens. Further investigations were carried out in order to compare the absolute difference between the numerical runner efficiency and the experimental efficiency. In doing so, the various losses that occur during operation of the turbine can be appraised and a prediction of casing losses can be made. Firstly, the mechanical losses of the test rig are estimated to determine the experimental hydraulic efficiency. Following this, the numerical efficiency of the runner can then be ascertained by considering the upstream pipework losses and the aforementioned runner simulations, which are combined with previously published results of the 3D velocity profiles obtained from simulating the injectors. The results indicate that out of all of the experimental cases tested, in the best case scenario the casing losses can be approximated to be negligible and in the worst case scenario ≈3%.
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