Energy Reports (Nov 2023)
Uncertainty in the numerical prediction of the tangential velocity in axial turbines at part load operations: A parametric study
Abstract
Numerical simulations of axial hydraulic turbines away from the best efficiency point are challenging. Previous studies especially show difficulties predicting the tangential velocity at Part Load (PL) operating conditions, where the swirl is high, in comparison to experiments. This is a reoccurring problem, and it is essential to understand, as the high tangential velocity is a fundamental characteristic of the flow in hydraulic turbines and is directly related to the swirling flow stability and the turbine’s power output. The objective of this study is to numerically investigate and understand the origin of the tangential velocity deviation from experimental results by performing simulations with the finite volume method of an axial turbine operated at PL. A parametric study is performed to address the abovementioned. Specifically, the effects of the blade clearance, blade angle, flow rate, and different turbulence models are studied on this issue. Results are analyzed by comparing the predicted axial and tangential velocity profiles and torque to experimentally obtained values. Primarily the runner inter-blades flow is studied as there is a knowledge gap. In addition, the physical phenomena responsible for head losses are studied in detail. Results show that the model can predict the flow relatively well at optimal flow conditions with low swirl but has problems at part load; the tangential velocity between the runner blades is underestimated by ∼20%. The undervalued head losses are the root cause. They result in an overestimated torque and an underestimated tangential velocity as the runner extracts too much energy from the fluid. A small modeling error of 0.5° in the blade angle and a change of 3% in the flow rate significantly affect the tangential velocity and torque prediction. The studied parameters must be considered carefully when building a numerical model.