1. Introduction
Kaplan hydroturbines are widely used in hydropower plants because of their high efficiency over a wide range of operating conditions. A propeller-type turbine is suitable when the load on the turbine remains constant. For a Kaplan turbine’s design and operation, tip clearance, which is formed by the rotating runner blades and the stationary runner chamber [
1,
2], is essential.
Because of the clearance gap between the blade tips and turbine casing of axial turbomachinery rotor blades, tip leakage flows are expected. In both compressors and turbines, the tip region flow tends to include a pressure-driven, oblique leakage flow from the pressure side to the suction side of the blade, and the roll-up of a tip vortex in the corner bounded by the casing and the blade on the suction side. Leakage flows then cause efficiency loss because of the increase in tip clearance in Kaplan turbines [
3]. Most previous studies [
4,
5,
6,
7,
8] that investigate tip vortex loci were performed concerning gas turbines or compressors and the aim to reduce accompanying losses. Cojocaru [
9] investigated the influence of anticavitation lip profile on the intensity of cavitation erosion in Kaplan turbines, while Hutton et al. investigated component losses in Kaplan turbines and improved a scaling technique for model tests [
10]. Moreover, there is only a limited number of studies that investigate tip clearance in propeller turbines, both by numerical simulations and by experimental measurements [
11,
12]. Roussopoulos and Monkewitz [
3] applied particle image velocimetry (PIV) to study the tip vortex and cavitation performance caused by the tip clearance of Kaplan turbines, while Nilsson and Davidson [
13] studied tip clearance losses using computational fluid dynamics (CFD) simulations, wherein they found that a tip clearance of 0.25 mm could reduce the efficiency of a Kaplan water turbine with a runner diameter of 0.5 m by about 0.5%. On the other hand, Gehrer et al. [
14] examined the cavitation caused by the tip clearance of a Kaplan turbine by simulation in the runner blade optimization based on an evolutionary algorithm, and Bodkhe [
15] studied the experimental analysis of Kaplan turbines at different operating load conditions. With this, this study shifts the focus on tip clearance losses in Kaplan turbines.
An unsteady state analysis of hydroturbines can be useful in predicting and analyzing the instability caused by the unsteady flow field and in developing mitigating techniques to minimize the effects of these phenomena [
16]. Wang et al. [
17] investigated the characteristic frequencies in the unsteady hydraulic behavior of a hydraulic turbine experimentally wherein their results showed that the pressure fluctuation in a draft tube is stronger than that in the upstream flow passage. A more recent study by Su et al. [
18] investigated the chaotic dynamic characteristics of pressure fluctuation signals in hydroturbines, and their results revealed that the main energy pressure fluctuations in a draft tube are located at low-frequency regions. Also recently, Glowacz [
19] investigated the fault diagnosis of a single-phase induction motor based on acoustic signals and then proposed a signal processing method for early fault diagnosis of electrical and mechanical faults of rotating machines. Glowacz [
20] also analyzed acoustic-based fault diagnoses of commutator motors wherein acoustic signals were found to be in the range of 88.4–94.6%. Fei [
21] performed a fault diagnosis method of bearing by utilizing lifting wavelet transform (LWT)—self-adaptive phase space reconstruction (SPSR)—singular value decomposition (SVD) based relevance vector machine (RVM) with the binary gravitational search algorithm. The results demonstrated that the method could achieve higher diagnostic accuracy for bearing. Caesarenda et al. [
22] investigated on empirical study of feature extraction methods for the application of low-speed slew bearing monitoring was performed. With this, extensive literature exists on the CFD method of flow simulation of hydraulic turbines. Wu et al. [
23] studied prototype and model Kaplan turbines and pressure fluctuation through numerical simulations, and their results revealed that pressure fluctuation in the draft tube suddenly raises both the model and prototype turbines. Rivetti et al. [
24] also studied pressure pulsation in Kaplan turbines and obtained good results, while Drtina et al. [
25] studied hydraulic turbines (i.e., Pelton, Francis, and axial turbines), both computational and experimental, and demonstrated that the CFD method is effective in simulating the flow field in fluid machinery. Furthermore, other studies have investigated the validation of the CFD method in the dynamic behaviors of water turbines [
12,
26].
At present, the conventional methods for monitoring the stability of the fluid machinery include pressure fluctuation, acoustic, output, and other inspections. In the running monitoring, the pressure fluctuation is the major focus to identify the operating conditions. To extract the characteristics of fluctuated signals, mathematical tools like the fast Fourier transformation (FFT) analysis is often utilized, wherein the signals’ features in the time domain, frequency domain, or amplitude can be obtained. Such methods are significantly helpful for the working stability and state inspection of hydroturbines [
27,
28]. Therefore, the unsteady pressure fluctuations characteristics in the tip leakage flow play an important role in load instabilities.
With this, this study focuses on the investigation of the tip clearance flow of a Kaplan turbine through numerical simulations. Furthermore, unsteady three-dimensional turbulent flow throughout the full domain of a Kaplan turbine was investigated through simulations, and the pressure pulsation in the runner and generator (hub) was predicted and analyzed using the FFT analysis.
4. Conclusions
This study was based on the steady and unsteady flow analyses with varying tip gaps between the runner and the discharge ring of the Kaplan turbine through a computerized flow analysis. For numerical analysis, three-dimensional modeling of the existing Kaplan turbine was performed from the drawing and scanning shape data. The performance analysis of the existing turbine was accomplished by changing the runner vane opening from −4° to 25° and the guide vane opening from 23.5° to 72.0°. The computed results were compared with the experimental data provided by the manufacturer to verify the validity of the simulation. The performance of the standard tip gap (1.75 mm) and that of an abnormal tip gap (6 mm) of the Kaplan turbines were also compared. It was confirmed that the output of the turbine decreased when the interval was generated. In the comparison of the results, in both cases, the flow rate of case 2 was 1.46% less than of the conventional turbine, and the output difference was a maximum of 81 kW. In the case of efficiency, the difference between both cases was only 4.59% within the rated range. The internal flow field and the turbulent kinetic energy distribution was also observed and found that unsteady flow occurred as the gap became higher than usual, and pressure fluctuation and period were confirmed at the peripheral part of the vane. Through the FFT analysis, it was confirmed that the vibration caused by the flow instability of the runner vane was transmitted to the generator. To reduce the dynamic vibration effect of the turbine, the tip gap of the machine should be minimized. Therefore, repairing the runner and discharge ring gap within the normal range should be considered because this flow may cause severe vibrations to the runner. The study notes that the simulation results did not consider the bearing and mechanical loss of the turbine that occurred in the machine. The thrust bearing, shaft seals, and guide bearings into the model could be a great interest for further research combined with the FFT analysis.