OPTIMIZATION OF AXIAL HYDRAULIC TURBINES RUNNER BLADES USING HYDRODYNAMIC SIMULATION TECHNIQUES

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Scientific Bulletin of the Politehnica University of Timisoara Transactions on Mechanics Special issue The 6 th International Conference on Hydraulic Machinery and Hydrodynamics Timisoara, Romania, October 21-22, 2004 OPTIMIZATION OF AXIAL HYDRAULIC TURBINES RUNNER BLADES USING HYDRODYNAMIC SIMULATION TECHNIQUES Corina BUŞEA, Eng.* Research, Development and Design Direction Sigrid JIANU, Dr.eng Research, Development and Design Direction *Corresponding author: Calea Caransebeşului nr. 16, 320168, Reşiţa, Romania Tel.: (+40) 255 231742, Fax: (+40) 255 230560, Email: dcdp@cs.ro ABSTRACT The paper shows some aspects regarding the K20 type axial hydraulic turbine runner optimization, using the finite element analysis software CFX BladeGen, starting with runner hydrodynamic design, materialization of geometric model and CAD-CFD interfaces. Mathematical modeling technology application in turbomachinery design is a powerful tool for equipment optimization from the design phase, shortening the realization cycle. KEYWORDS Kaplan turbine, runner optimisation, hydrodynamic design, geometric model, finite element analysis. NOMENCLATURE a 0 [mm] opening of wicket gates n [rpm] rotational speed n s [rpm] specific speed n 11 [rpm] unitary speed H [m] head Q [m 3 /s] discharge Q 11 [m 3 /s] unitary discharge η [%] efficiency ϕ [ 0 ] angular position of runner blades g [m/s 2 ] gravity k [m 2 /s 2 ] turbulent kinetic energy Subscripts and Superscripts s specific 11 unitary opt optimum ABBREVIATIONS CFD computational fluid dynamics CAD computer aided design 1. INTRODUCTION The axial turbines are generally the most suitable type for low-head and medium-head installations where large variations of flow and head are encountered. The axial turbines were designed and made till today in a wide range of dimensions and powers. Although, because of physic phenomena complexity that appears in function, there is no unitary conception method of those types of hydraulic machines that could give results without a big amount of experimental researches on models. High development of information technology made possible the computation of three-dimensional flows in hydraulic turbines using the finite element analysis software. The advantages of using the modern CFD methods are: quick results; low costs unlike the experimental researches on the turbine models; possibility of some significant parameters study. But the results obtained using CFD methods may be affected by errors. In order to apply these techniques in hydrodynamic real time design of turbine models the computed results should be compared to experimentally obtained values. 2. THE KAPLAN TURBINE MODEL In the event of Kaplan turbines modernization, it turns out that the runner has a great importance in efficiency of hydraulic energy transformation process and also in losses generation process. Therefore the most complexes studies and researches are made on the runner blades, respective on blade components generally. The runner hydrodynamic design must be made in the existing hydraulic layout (figure 1), on the power 67

plant data (initial data or modified data as result of hydro energetic potential reevaluation or because of some hydro technical works). The model submitted to optimisation using CAD modelling and CFD analysis is a Kaplan turbine model K20, having 4 runner blades, 16 wicket gates and 12 stay vanes, polygonal spiral case and deep draft tube. Figure 1. Hydraulic layout The specific speed for the two variants was set at n s = 520 rpm, and the unitary parameters were calculated with the relations: n Q 3 7 11 = 9, 725 n s 4 8 7 11 = 8,933 10 n s The runner hydrodynamic design was accomplish using the design software HIDRO made in Turbo Basic language, that use the conform representation theory. This software is made from seven main modules and twenty-four routines, containing 5200 program lines. The initial dimensioning of runner blades variants was accomplished using the calculus module Runner dimensioning.xls. Several runner blades variants were obtained and from them were selected two variants with the next parameters: H opt = 16,54129 m Q opt = 28,85133 m 3 /s n 11opt. = 141,8701 rpm Q 11opt. = 1,13501 m 3 /s D 1 = 2,5 m ν = 0,408 n = 230,8 rpm z r = 4 palettes n s = 520 rpm The profiles parameters variations are shown in Figure 3, respective Figure 4 in function of calculus radiuses including the hub and the shroud. Figure 2. Kaplan turbine model in the test rig Technical specifications for the hydraulic turbine: Minimum head H min 10,1 m Maximum head H max 23,8 m Net head H c 18 m Flow Q c 35,1 m 3 /s Rated output 5.662,5 kw Nominal speed n 230,8 rpm Specific speed n s [CP] 546 rpm 3. RUNNER HYDRODYNAMIC DESIGN A very important problem in runner blades hydrodynamic design is the selection of optimal specific speed, respectively the calculus of n 11, Q 11, H and Q parameters. Figure 3. Parameters variation for the K1 runner blades variant At the present day, the theoretical methods for the computation and design of hydrofoil cascades are imposed. These methods are based on the geometry determination of profile disposed in the network, when knowing the asymptotic velocity before and after the runner, the velocity distribution and the profile geometrical parameters (d/l; f/l; x d /l; x f /l). U.C.M. Reşiţa - S.A. Research Department developed a method of mathematical modeling for these hydrodynamical problems starting with the hypothesis of axial symmetric potential motion, that impose the 68

Figure 5. Cylindrical sections Figure 4. Parameters variation for the K2 runner blades variant singularity theory and the conform representation. This hydrodynamic design method use the theory developed by prof. O. Popa for hydrofoil cascade dimensioning based on conform representation. Reducing the three-dimensional axial symmetric movement in the axial turbines to a bi-dimensional movement, it was determined: - the turbine principale dimensions; - the cinematic and angular asymptotic elements; - the geometric parameters variation of the hydrodynamic profile and installation angle. With these data, the conform representation allow the profile network dimensioning that offer the necessary elements for energetic and cavitational characteristics calculus. After the hydrodynamic design of the two runner blades it was obtained the cylindrical sections points for the runner blade and the cavitational coefficient for the design point. 3. TRIDIMENSIONAL MODELING OF RUNNER BLADES AND WICKET GATE BLADES USING CAD SOFTWARE Runner blades CAD modeling it was accomplish using Bentley Microstation software. The main elements of the runner are the runner blades, defined by a number of sections, designed in hydrodynamical manner. Using CAD software leads to 3D geometric models of the machine components. Angular position of the runner blades was selected at ϕ =0, and the opening of wicket gates at a 0 = 36 mm. The runner blade of an axial turbine is usual defined by a number of 3 to 6 cylindrical sections, at different radiuses. These cylindrical sections are obtained from rolling on the different radius cylinders the plane profiles designed previously (Figure 5). The blade surface, thus obtained, it was extended in radial direction for the intersection with the spherical surfaces that define the real blade. Figure 6. Intersections with hub and shroud surfaces The microturbine wicket gate is cylindrical and the blades are asymmetric. For CAD modeling of the wicket gate blade it was used the two profiles that define the ends of the blade. In Figure 7 it s shown the surfaces obtained for the wicket gate blades, and in Figure 8 the intersections with the hub and the shroud surfaces. In order to apply CFX software, a correct import of information from CAD to CFX program must be realized. The used interface is IGES format. It allows obtaining of complex geometry and import of nongeometric features. Figure 7. Wicket gate blade 69

Figure 8. Intersections with hub and shroud surfaces 4. CFX ANALYSIS CFX-BladeGen and CFX-BladeGenPlus are interactive instruments for turbomachinery designing and quick analysis. The user can redesign existing blades or create new blade designs, and rapidly evaluate the performance of the component. To import data the following steps has been performed: gather data and identify usage; verify meridional curves and meridional orientation; verify blade curves and identify blade ends; transfer the data to a BladeGen model. In Figure 8 it s shown the BladeGen model created by selecting the Ang/Thk Blade Document for the runner blade, and in Figure 9 for the wicket gate. Figure 8. The BladeGen model for the runner blades variant K1. Figure 9. The BladeGen model for the wicket gates blades. After accomplish these steps, the module Blade GenPlus was started. The module CFX-BladeGenPlus provides a 3D viscous evaluation. This module has been used to evaluate the efficiency of the turbine runner. The first step was to specify the basic machine type and units. The next step was to set up the automatic creation of the unstructured grid around the blade. The CFD technology uses finite element grid. The grid type selection is essential for more accurate results. Usually, for a singular component analysis it is used monobloc grid and for a component assembly it is used multibloc grid. CFX BladeGenPlus uses monobloc finite element grid. For a correct simulation it must calibrate the finite element grid. In that sense, the existing runner of K20 model was analyzed with CFD technology for the same data (ϕ =0, and the opening of wicket gates at a 0 = 36 mm). The obtained efficiency from CFX BladeGenPlus simulation was compared with the real efficiency obtained from experiments, refining the grid until the simulated efficiency is comparative to measured efficiency η = 0.887. The settings in this panel were: refinement factor: 1 inflation layers: 3 node count: 13355 The grid image of K20 existing blade it s shown in figure 10. Fluid properties were selected from predefined values for water, and the fluid model it was set to turbulent viscosity model. 70

Calculated Results - η = 88,29% for K1 variant - η = 89,53% for K2 variant We noticed that for the K2 variant with 89,53% efficiency, the relative pressure values are higher than K1 variant. Figure 10. Grid image for K20 existing blade The operating conditions for the runner were selected as follows: run specification: massflow exit; rotation rate: n = 626.741 rpm; inlet total pressure: Ptotal = 0.49398 bar; mass flow rate: Q = 582.824 kg/s; wall roughness height: 0.0008 mm inlet swirl angle, loaded from a previous analysis of wicket gate: 58.631. After the 3D viscous evaluation of the component the results are generated automatically and the final report shows the influence of the different parameters to the runner efficiency. Relative velocity and pressure distribution for the two analysed variants are shown in figure 11 and 12. 5. CONCLUSIONS Using the CFD simulation on the computer, the response time is very short and the modification can be investigated in a short time. Prediction of energetic characteristics by means of modern CFD techniques is possible with certain accuracy. The computation errors for a Kaplan turbine model efficiency obtained by comparison of computed results to in the testing facility measured values depend on several aspects: - Used CFD programme (rapid screening tool or detailed analysis software) - Distance: computed operating point - optimum - Optimisation of software application Independent to used flow-modeling method, final validation of results always should by realize by comparison to experimental test results. Fluid simulation techniques do not replace experimental tests in precise test stands, but they reduce their volume and costs by decreasing the number of blade variants that will be realized. ACKNOWLEDGMENTS The authors acknowledge the support of UCM Reşiţa S.A. for realising extensive experimental testing and detailed computation and ANSYS Incorporated for continuous and professional support in implementation of CFX computation techniques. Figure 11. Relative velocity and pressure distribution for K1 variant Figure 12. Relative velocity and pressure distribution for K2 variant 71

REFERENCES 1. Anton, I. (1979) Turbine hidraulice, Facla Publishing, Timişoara, 2. Anton, I., Ancuşa, V., Resiga, R. (2001) Numerical simulation for fluid dynamics and magnetic liquids, Orizonturi Universitare Publishing, Timişoara 3. Casey, M. (2001), Quality and trust in CFD Proceedings of the CFX User Conference, Berchtesgaden 4. Jianu, S., Hău, A., Iavornic, C., Tudora, O. (2002), First results obtained using CFX software for prediction of energetic behaviour of Kaplan turbine runner, Proceedings of the CFX User Conference, Strasbourg 5. Schilling, R., Fernandez, A., Aschenbrenner, Th., Riedel, N., Bader, R., (1996) Echtzeitmethode zum Entwurf von Beschaufelungen Moeglichkeiten und Grenzen, Proceedings of Pump Congress, Karlsruhe 72