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Some Applications of Computational Tools for R&D of Hydraulic Turbines Biraj Singh Thapa, Amod Panthee*, Hari Prasad Neopane Abstract— Design of hydraulic turbines involves several stages of iterative calculations. Furthermore, the selection of the turbine is unique to each site conditions. This makes the R&D of the hydraulic turbines a complicated and time consuming work. Recent advancements in computational tools and processors have added advantages to the R&D process of hydraulic turbines. These tools are able not only to compute solutions for the complex design equations but also provide the user friendly virtual environment for performance test and design optimization. A new program named as “Khoj” has been developed using Matlab for design optimization of Francis runners. The optimized design from the program can be further analyzed using CFD, CAD and FSI tools, which estimate the effect of design variables on performance of the turbine. For the project on failure analysis of Khimti runner, the true size runner model has been developed using SolidWorks. Stress and fatigue analysis of the runner has been attempted using CosmosWorks. Study of the general performance behavior of the Pelton runner and identification of the possible causes of failure of the Khimti runner at its operating conditions is under progress. This paper presents the experiences of use of computational tools for research and development of hydraulic turbines at Kathmandu University. The research methodology followed and the computational tools applied, with the recent results for design optimization of Francis runner, effects of operating conditions on sediment erosion and failure analysis of Pelton runner of Khimti Hydropower will be elaborated in-depth. Effectiveness and limitations of application of computational tools for R&D of hydraulic turbines will also be discussed. Index Terms— Computational tools, Design, Hydraulic turbines, CFD, SolidWorks,
I. INTRODUCTION
N
EPAL has a huge potential of hydro power. Most of the surface water in Nepal flows through four major river basins, Saptakoshi, Narayani, Karnali and Mahakali, extended Biraj Singh Thapa is a Graduate of Mechanical Engineering from Kathmandu University. Currently, he is working as a Full time Researcher in Turbine Testing Lab, Kathmandu University. (
[email protected]). Amod Panthee completed his Bacherlor’s degree in Mechanical Engineering from Kathmandu University. Currently, he is working as a Research Assistant on RenewableNepal Project at Turbine Testing Lab, Kathmandu University. (*correspondence email:
[email protected]). Hari Prasad Neopane, PhD. is Associate Professor at Department of Mechanical Engineering, School of Engineering, Kathmandu University. He works as a program coordinator on EnPe-Master Program in Planning and Operation of Energy Systems (MPPOES) at Department of Mechanical Engineering, Kathmandu University. (
[email protected]).
from east to the west. The total hydropower potential of Nepal at Q40 is about 53,000 MW [1] as shown in TABLE I. Despite, having the huge potential, Nepal is still lagging behind in power generation with total harvested capacity of 650 MW. TABLE I Hydraulic turbines TOTAL HYDROPOWER POTENTIAL are classified into Major Basins Potential (at Q40) different categories depending upon its Saptakoshi 17008.3 principle and range Narayani 17800.2 of operation [2]. Therefore, the Karnali 15661.16 selection of hydraulic Mahakali 2261.83 turbines varies depending upon the Total 52731.83 site criterions. The installation of hydropower plants despite having a huge potential becomes more complex with change in design for a slight variation in design inputs like Head (H) and Discharge (Q).
Moreover, Nepal is located on the lap of Himalayas. This increases the sediment concentration in the rivers of Nepal unlike other countries with igneous mountains. The river characterized with high sediment concentration is one of the problems in operation of hydraulic turbines erected at ROR type or storage type projects [3]. The sediment eroded Francis runner of Trishuli HEP is shown in Figure I. The design of hydraulic turbine is complex since it involves a long iterative process in design stage. And it is necessary to predict the behavior of hydraulic turbines Figure I: Sediment Eroded Francis Runner at various of Trishuli HEP conditions on real environment while designing. This makes the design of the hydraulic turbine more time consuming. But, the use of computational tools have added advantage in design of hydraulic turbines and the prediction of behavior at various
2 operating conditions and complex iterative process can be done in short period. II. CHALLENGES IN R&D OF HYDRAULIC TURBINES There are many challenges in research and development of hydraulic turbines. The challenges are seen from the initial design stage after the selection of suitable site for erection of hydropower station. It is followed by the selection of most efficient design from a list optimized design to work on real environment. The challenges continue during operation and post operation or maintenance stage of the hydraulic turbines. A. Design of Francis Runner The design of hydraulic turbines involves many assumptions. Initial assumptions during design of Francis turbine are infinite number of thin blades, streamlines are symmetric about the rotational axis and no frictional losses are present [4]. But it is difficult to achieve these conditions in real working conditions. The other assumptions based on the empirical relation to achieve the desired result with assumptions stated above are given in TABLE II [4]. TABLE II INITIAL DESIGN ASSUMPTIONS OF FRANCIS TURBINE
Outlet Peripheral Velocity (U2) 35 m/s – 43 m/s
Outlet Angle (β2) 180 - 220
The first step in design of a hydraulic turbine is to assume a streamline. The shape of the streamline is given by equation (1). The shape of the streamline changes with change in values of constants ‘a’ and ‘b’ assumed in the equation from a circle to an ellipse [5]. (1)
(2)
The remaining streamlines on a runner blade of the runner is obtained using the continuity equation (2) and the principles of geometry. The geometry of the streamlines is shown in Figure II where the constants have their usual meaning. All these assumptions and iterative processes make the design process a challenging task. ri,1 R1,2; Z1,2
Ri,2; Zi,2
R1,1; Z1,1
bi,1 Ri,1; Zi,1
Ri-1,1; Zi-1,1
Ri+1,1; Zi+1,1
Z R Figure II: Distribution of points along the streamline
B. Operation of a Hydraulic Turbine Hydraulic Turbines are operated at various conditions. It is a usual trend to design a hydraulic turbine at Best Efficiency Point (BEP). But, a hydraulic turbine is operated from part load to full load depending upon the energy requirement. The change in operation of hydraulic turbines at different operating conditions reduces the efficiency and life of the turbine. Apart from these, it also creates problem in operation and maintenance of the turbine unit [6]. Depending upon the site of operation, there is a variation in sediment concentration with different percentage composition of quartz and mica in rivers of Nepal [3]. So, if we have a list of optimized design for a specific site to be tested, it would be a problem to test with a physical model in the lab. The test becomes more costly and time consuming when tested on a physical model. Despite having a sound hydraulic design, a hydraulic turbine fails during operation. A typical case of such failure in Pelton runner of Khimti HEP is shown in Figure III. The reasons for Figure III: Root Crack in Pelton Runner failure of turbines during operation may be manufacturing defects, modes of operation which are steady state and transient state operation and maintenance procedure applied in the hydraulic turbines. During the operation of hydraulic turbines, the mode of operation changes from steady state to transient state upon variation in load. This produces vibrations and stress on power production unit which might cause a failure of A B the hydraulic turbines. When the load is transferred from point A to point B, shown in Figure IV: Pelton Bucket Figure IV, the stress developed in the runner varies which might cause the untimely failure of the runner when operated on a cycle [7]. C. Maintenance of Hydraulic Turbine The turbine components are passed through a series of heat treatment procedure during maintenance. The residual stress is induced when a large temperature difference has been created at different sections within the runner components [8]. Also, the improper cooling of the hydraulic turbines forms weld decay which is a combination of Carbon and Chromium [9], the ingredients of material used in manufacturing hydraulic turbines. This induces residual stress in turbine component and the immediate site of failure [7].
3 III. METHODOLOGY The Francis runner blade has been developed using general principles mentioned in Section II and literature [5] for “Design Optimization of Francis Runner” and “Effects of Operating Conditions on Sediment Erosion” using the Matlab program “Khoj” and CAD software. These files are exported to AnSys CFX for further analysis. A. Design Optimization of Francis Runner A range of optimization criterion has been set on outlet diameter, number of pole pairs in generator, reduced peripheral velocity at inlet, acceleration of flow through the runner, height of the runner and blade angle distribution [10]. Several optimized design is then developed using the optimization criterion. The comparison of the optimized design is done with the reference design by setting the erosion factor and erosion tendency as reference indicators. Erosion Tendency (3) is quantification of tendency of a specific design of the runner to be eroded in similar sediment conditions. Erosion Factor (4) is the ratio of erosion tendency of each new design with respect to reference design. ∑ ∑
m3/s3
(3)
-
(4)
B. Effects of Operating Conditions on Sediment Erosion The factors responsible for sediment erosion are particle mass, particle velocity, grain shape and size, concentration of particles and angle of attack at which the collision occurs between the particle and the surface of the runner blade. The empirical erosion model, Tabakoff erosion model (5), is used in analysis which incorporates the factors responsible for erosion to determine the erosion rate [6].
( Where,
) [
TABLE III ANALYSIS CONDITIONS ON COSMOSWORKS
Load 85630 N normal to the reference plane Uniform Distribution and Sequential Loading Restraint On 1 Face (at center) Description Study Property Solid Mesh Mesh Type 4 Points Jacobian Check 55709 No. of Elements
Force Distribution
The erosion factor for the reference design is set 1 and compared to the results obtained for optimized design.
[
C. Failure Analysis of Pelton Runner The 3D model of the Pelton Runner, shown in Figure V, has been developed using the orthographic projection of runner sections provided by Himal Power Limited using SolidWorks. The other model runner was developed Figure V: 3D Model of Pelton Runner for stress and fatigue of Khimti HEP analysis of the Pelton runner because of software limitation. The information on analysis conditions is tabulated in TABLE III.
(
IV. RESULTS A. Design Optimization of Francis Runner The optimized design developed within the defined range of operation is shown in Figure VII. The optimized design is then compared with the reference design, shown in Figure VI, of Jhimruk HEP in Nepal. The result of comparison between the reference and optimized design is shown in TABLE IV.
) ]
(5) (
)] ,
Vp
is
the
particle impact velocity, is the impact angle in radians between the particle path and the wall, is the angle of maximum erosion. , are the model constants and depend upon the particle and wall material combination. The blade profile is meshed with hexahedral element using Turbo-Grid. The analysis is done on two modes of operation, i.e. at best efficiency point with guide vane opening of 160 and at full load point with guide vane opening of 220. The sediment particles chosen for analysis are of spherical and non-spherical types. The boundary condition is set as uniform injection of sand particles of uniform diameter for both modes of operation [6].
Figure VI(a): Streamlines on Reference Design
Figure VI(b): Sediment Erosion on Reference Design
Figure VII(a): Streamline on Optimized Design
Figure VII(b): Sediment Erosion on Optimized Design
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TABLE IV COMPARISON OF EROSION FACTOR
Erosion Factor
Reference Design 1.0
Optimized Design 0.481
The design optimization result also showed that the sediment erosion is reduced significantly with increase in the runner height [10]. Erosion is also dependent upon the blade angle distribution. It was found that the erosion rate is reduced for the optimized design with blade shape 1 compared with the reference design of blade shape 3 [10] shown in Figure VIII.
This is due to the increase in flow turbulence and higher relative flow velocities at runner outlet. The increase in erosion rate is due to the presence of higher rotational motion which caused more separation of flow. The result suggests that the operating conditions of hydraulic turbines have significant effect on erosion of the turbine components. The analysis was repeated varying the concentration of sediments at two modes of operation. The results from the analysis is shown in Figure XI. It can be observed that with an increase in sediment concentration, the erosion rate density is increased for both modes of operation. It can be concluded from the result that the erosion rate in the runner blade is always higher when operated at full load than at best efficiency point [6].
Full Load
BEP
Figure VIII: Blade Angle Distribution
B. Effects of Operating Conditions on Sediment Erosion The effects of operating conditions on sediment erosion have been analyzed on Francis blade of Cahua Power Plant of Peru. The result showed that the erosion rate density is higher at full load operation point than operation at best efficiency point for both spherical and non-spherical sediments [6], shown in Figure IX and Figure X.
Figure XI: Variation of Relative Erosion Rate Density with mode of Operation C. Fault Analysis of Pelton Runner at Khimti HEP The model runner was analyzed using CosmosWorks addin in SolidWorks for stress and fatigue analysis. Figure XII shows the Factor of Safety (FOS) plot of the model runner. The result shows that the root area of the runner geometry is critical site for occurrence of failure [7]. The result justifies the occurrence of crack in the root of pelton bucket shown in Figure III.
Figure IX: Erosion due to Spherical Sediment (a) at BEP (b) at Full Load
Figure XII: FOS Analysis on a Model Runner
V. CONCLUSION Figure X: Erosion due to Non-Spherical Sediment (a) at BEP (b) at Full Load
The use of computational tools in R&D of hydraulic turbines helps in complex solving the complex mathematical equations reducing both cost and time. The advantage on
5 reduction of cost and time can be justified by the use of the real environment conditions for virtual testing in lab repeatedly for different test conditions, which might increase in cost and time if the problem has to be solved using the real physical model. In design of hydraulic turbines, it plays an important role offering flexibility while choosing different variables that accounts different design result. The effects due to change of each variable on design can be easily understood which helps in producing an efficient design. It also helps in finding the possible causes of failure of hydraulic turbines during initial design stage. The use of computational tools can be sometimes disadvantageous. The assumptions should be carefully taken to represent the real operating conditions. The results obtained are dependent upon the accuracy of the input data and assumptions. Therefore, it is necessary to verify the design outputs obtained from the computational tool using a physical model test at lab. Despite significant reduction in erosion factor of optimized design, Figure VII (a), streamlines in the optimized design are not uniform as in the reference design, Figure VI (a). This might cause reduction in efficiency of the significant design which should be verified with a physical model test at lab. The fault analysis of Pelton runner of Khimti HEP is at its initial research stage. Further works can be done on stress and fatigue analysis of the real model of runner. The effects due to the heat treatment procedure on the runner can be analyzed using appropriate assumptions with the aid of computational tools. The effect due to different modes of operation on the turbine component is another prospective area where computational tools can be used. REFERENCES [1] Jha, R. (2007), Total Run-of-River type Hydropower Potential in Nepal, Hydro Nepal. [2] Thapa, B. (2004), Sand Erosion in Hydraulic Machinery, PhD Thesis, Norwegian University of Science and Technology (NTNU). [3] Neopane, H. P. (2010), Sediment Erosion in Hydro Turbines, PhD thesis, Norwegian University of Science and Technology (NTNU).
[4] Brekke, H. (2001), Hydraulic Turbines: Design, Erection and Operation, Norwegian University of Science and Technology (NTNU). [5] Francke, H. H., et al. (2009), High Pressure Hydraulic Machinery, Water Power Laboratory, Norwegian University of Science and Technology (NTNU). [6] Neopane, H. P. (2011), Relationships between Operating Conditions of Turbines and Sediment Erosion, Proceedings in the International Conference of Hydro 2011.
[7] Panthee, A. (2011), Fault Analysis of Pelton Runner of Khimti Hydropower, Industrial Training Report, Turbine Testing Lab, Kathmandu University. [8] Kubota, T., & Tanaka, O. (2010). Fuji Electric Co., Ltd. Retrieved July 24, 2011, from Fuji Electric: http://www.fujielectric.com/company/tech_archives/pdf/3 0-04/FER-30-04-151-1984.pdf [9] Steel Casting Handbook, Supplement 7 Welding of High Alloy Casting (2004), Steel Founders Society of America. [10] Thapa, B. S., Eltvik, M., Gjøsæter, K., Dahlhaug, O. G. (2012), Design Optimization of Francis Runners for Sediment Handling, Proc. in Int. Conf. on Water Resources and Renewable Energy Development in Asia, Thailand. BIOGRAPHIES Biraj Singh Thapa is a graduate of Mechanical Engineering from Kathmandu University. Currently, he is working as a Full time Researcher in RenewableNepal Project at Turbine Testing Lab, School of Engineering, Kathmandu University. Amod Panthee completed his Bachelor Degree in Mechanical Engineering from Kathmandu University. Currently, he is working as a Research Assistant in RenewableNepal project at Turbine Testing Lab, School of Engineering, Kathmandu University. Hari Prasad Neopane completed his PhD from NTNU. He is Associate Professor at Department of Mechanical Engineering, School of Engineering, Kathmandu University. He works as a program coordinator on EnPe-Master Program in Planning and Operation of Energy Systems (MPPOES) at Department of Mechanical Engineering, Kathmandu University.
