Impellermodeling_省略_UGNX_KFandFluent_王凌云.pdf

J. Cent. South Univ. (2012) 19: 34303434 DOI: 10.1007/s11771-012-1425-3 Impeller modeling and analysis based on UG NX/KF and Fluent WANG Ling-yun(王凌云) 1, HUANG Hong-hui(黄红辉)1, Rae W. West 2 1. Department of Manufacturing Engineering and Technology, Shanghai University of Engineering Science, Shanghai 200437, China; 2. College of Engineering, University of Nevada -Las Vegas, Las Vegas, Nevada 89154, USA Central South University Press and Springer-Verlag Berlin Heidelberg 2012 Abstract: Parametric modeling of the impeller which drove a small wind device was built by knowledge fusion technology. NACA2410 airfoil blade was created by KF language. Using technology of UG/KF secondary development for the automatic modeling of wind turbine blade, the program can read in the airfoil data files automatically and the impeller model entity can be generated automatically. In order to modify the model, the aerodynamic characteristics of the impeller were analyzed for getting aerodynamic parameters by Fluent. The maximum force torch and best parameters of impeller were calculated. A physical prototype impeller was manufactured and the correctness of the design was verified, and the error of force torch between simulation and experimental results is about 10%. Parameterization design of the impeller model greatly improves the efficiency of modeling and flexibility of the CAD system. Key words: knowledge fusion; airfoil wind turbine blade; parametric design; CAD/CAE Foundation item: Project(gjd-09041) supported by the Natural Science Foundation of Shanghai Municipal Education Commission, China Received date: 20120215; Accepted date: 20120705 Corresponding author: WANG Ling-yun, Professor, PhD; Tel: +862165421020; E-mail: Wanglyun16 1 Introduction From the perspective of product design and development, CAD technology has gone through three major stages: drawing-based, feature-based, process- based, and is going through the fourth phase: the knowledge-based 1. Feature-based 3D CAD technology established a parameter-driven model and the overall design of the follow-up can be a variety of processing, analysis and NC programming; Process-based CAD technology allows product data to interactively transform amongst the conceptual design, structural design, detail design, and process design etc, to support integration and parallel design and processing work. However, these CAD systems are unable to achieve the reuse of knowledge resources. The domain design principles, successful design cases, expert knowledge, and experience cannot be put into the final product models. Designers may make repeat mistakes when they do a lot of duplicate work. The artificial selection of standard series design still involves a large amount of work, and artificial intelligence method is applied less in design. GUO and YANG 2 built a blurry inference mechanism for turbine impeller standard model base with the combination of knowledge and CAD software by knowledge fusion (KF) method. LIU et al 3 developed an automatic 3D modeling program based on the UG secondary development technology, which improved the modeling efficiency. Design process is the process of modification. The purpose of parametric design is flexible design changes in accordance with product intent, so ease of modification is of utmost importance. For this impeller to go through multiple CAE experimental analysis and modification in order to complete the design products, parametric design can reduce the processing time before the CAE analysis in this work. Using UG/KF with Fluent modeling, the artificial intelligence technology can be introduced to the parameters for optimal design of the impeller. 2 Knowledge-based parametric design Parametric design is a kind of modeling method of design based on features, full size constraint, all data related, and dimension driven modification 46. A set of parameters were used to represent the relationship between the size of the values and the constraints on the basic structure of the design object. Its core is size parameter driven. The parametric design of the model greatly improved the efficiency of modeling and the flexibility of the CAD system. Knowledge-based parametric design is the fusion of reasoning and J. Cent. South Univ. (2012) 19: 34303434 3431 calculations into the design. By applying engineering design knowledge to the product design, establishing the intrinsic link between the design variables, and by using engineering design rules to constrain parameters, trends and scope of variation in parametric process, the design is verified directly driven by the design knowledge, to achieve a common drive of product design process by parameter and knowledge. It is a better solution for shortcomings of traditional parametric design. UG/KF is a knowledge-based parametric design technology integrated in the UG system. Users can develop applications to control UG engineering of objects through rules beyond a simple geometric model and be able to construct a fully reusable knowledge base 7. In this work, design rules and other professional knowledge and experience are directly built into the product model through UG/KF technology, promoting the parametric modeling of the product to a new level. The objects established through KF language and the objects created by UG system are identical, so the rules or knowledge can be described as three-dimensional geometric shapes with the UG system. UG/KF technology uses a rule description language. UG/KF language is an object-oriented language and it is built on the basis of Intent language 810. Users can use a general text editor to browse and modify KBE programs, so engineering knowledge can be updated, added and maintained at any time. UG/KF uses these “rules” to represent different geometric parameters and the relationship of engineering properties of the products. Because the language is declarative, there is no rule sequence. The UG/KF system automatically determines the order of the executions based on rules to the relationship. It uses these rules to calculate the engineering parameters of the product to drive the final geometry. In addition, this language can access external knowledge sources, such as a database or spreadsheet, and provides analysis and optimization modules with other applications such as module interfaces. 3 Impeller parametric designs Impeller parametric modeling flow is shown in Fig. 1. Blades and aerodynamic modeling and analysis are the focuses of this work. One difficulty of establishing the intelligent impeller model is to determine the airfoil curve. The general method is the use of splines. This impeller intelligent design system built by UG/KF simplifies the process of building blades. Blade series are usually composed of airfoil series: common airfoil series such as the NACA44xx series, NACA644xx series, and NACA230xx series aviation airfoils, and specialized wing series such as the United States SERI airfoil series and NREL airfoil series, Denmark R2A series airfoil and Sweden FFA2w series airfoil family depending on the selected airfoil design needs 1112. In this work, using NACA2410, the creation process of blades is as follows: 1) Create 2410.dat files, and store airfoil data, 2) Use spline functions to generate airfoil curves, 3) Build blade airfoil contour curves, and 4) Output user-defined features. Fig. 1 Impeller design process Section curve is drawn by NURBS cubic splines. The NURBS function has a strict mathematical basis. The NURBS curve has good geometric properties, such as geometric invariance, symmetry, convexity, and variation reduction, which are very suitable for the geometric description of space curves. It is widely used in the CAD/CAPP/CAM and other fields of modern mechanical design and processing 13. The k-th NURBS curve is defined as 1 1 0 1 0 0 d( ) ( )d( ), , ( ) L k k i ii L k ni iikL k L k ki ii i N t tB tttt N t d (1) where ),( iiii zyxd, is called the de Boor points of the curve )(td; i also is known as the power factor; ( ) t n B tis the Bernstein basis function; ( ) t i Ntis the B-spline basis functions. Airfoil surface uses NURBS curves on parametric modeling in three ways. The second method (fit) spline is accurate and simple, and will not damage the integrity of the original data. Spatial coordinate data are obtained after transformation of the original data. Points of each cross-section data are put into a *.dat file and imported to UG in discrete points by fitting the data, then we can get an accurate closed curve and part of the section curve of the spatial location. J. Cent. South Univ. (2012) 19: 34303434 3432 The height and diameter of impeller hub and the diameter of impeller are basically given in Table 1. After determining the setting angle of the blade, the specific section of the three-dimensional coordinates of each blade can be determined according to selected baseline wing types of basic geometric parameters 14. The source data can be provided for generating the blade entities by using these three-dimensional coordinates. Table 1 Impeller geometry parameters Parameter Value Setting angle/() 30, 35, 40, 62 Number of blades 5 Impeller diameter/mm 250 Hub diameter/mm 40 Hub high/mm 40 Using UG/KF secondary development technology for the automatic modeling of the program for wind turbine blade development, the program can automatically read the airfoil data files, and automatically generate entities with great value in engineering. The following DFA program is a creation of three dimensional model for the blade: #! NX/KF 4.0 DefClass: creat_spl (ug_base_part); # For the airfoil data read program (String parameter) text_file: “E:CreatBlade2410.dat“; (list) pt_data: $a openFile(text_file:; read); $b readSimpleDataFile($a); closeFile($a); $b; ; (integer) num_pts: length(pt_data:); (list) pts1: loop for $ii from num_pts: to 1 by -1; for $p is nth($ii, pt_data:); collect point(first($p), second($p), third($p); ; #the curve constructed: (Child) spl: Class, ug_spline_thru; Degree, 3; Periodic?, FALSE; Points, pts1: ; #coordinate transformation: Defun: RotateVector( Vector, $base, Number, $angle, # setting angle Vector, $Axis ) . Vector; Impeller creating result is presented in Fig. 2. Fig. 2 Impeller entity model 4 Impeller aerodynamic characteristics analysis By solving the unsteady equations, the turbulent flow field around the airfoil and aerodynamic parameters are obtained. As the flow rate is low, assuming the surrounding flow is incompressible flow, the flow of universal equations is S t V (2) When solving the variable =1, U, V, kT, the general equation (2) represents the continuity equation, the x and y directional momentum equation, the turbulent kinetic energy equation respectively; is the fluid density; V = ui + vj is the flow velocity vector; is the generalized diffusion coefficient; S is a generalized source term. Based on the pressure correction algorithm SIMPLE method, the flow equation (2) is solved by numerical method, the turbulent model which is a S-A turbulence model, unsteady constants using two order implicit scheme, convection, and diffusion using two order upwind scheme and two order central scheme 15. There are several models that deal with the problem of rotating machinery flows in FLUENT software: the rotating coordinate system model (RRF), coordinate multi-reference frame (MRF) model, the mixing plane model (MP) and sliding mesh model (SM). This wind turbine model uses the MRF model because it includes the rotation of the moving boundary and stationary static boundary. When 3D entity model is established, it is introduced into Fluent Flowizard analysis software as a x_t format file. The finite element mesh is automatically topologically simplified by using the Fluent software. After the basic parameters of initial conditions (wind speed is 8 m/s) are set, iterative processes will be done. After convergence is assured, a series of characteristic J. Cent. South Univ. (2012) 19: 34303434 3433 coefficients of impeller graphics will be obtained. Partial enlargement of the impeller grid is shown in Fig. 3. Impeller wall mesh size is 4 mm. The grid spacing can be controlled in the flow field by the side of the grid size definition. The grid size can be reduced in some dramatic changes in physical properties such as the impeller surface and the tip clearance, while at less important flow fields such as import and export segments, the mesh size can be defined slightly larger. Actually, a total of about 280 000 grids are generated. Upon examination, the quality of the mesh meets the computing requirements. Fig. 3 Enlarged view of impeller grid The velocity vector is shown in Fig. 4. The impeller rotational force of the flow channel results in the injection of the velocity along the rotation tangent of the rotation center axis in impeller exit flow field due to the rotation of impeller. The outlet flow line is not vertical backward parallel with the central axis. The flow field interception of different radii was got on downstream cross-section of the exports for reviewing. There are rears of the flow field speed behind the hub, until out of the hub. Also, outside the R = 20 mm region, there will be obvious speed. In addition, in the flow field near impeller top, also at the R = 125 mm, there will be backflow of fluid and here the liquid flow is more complicated and no consistent. Fig. 4 Chart of impeller velocity vector In order to search for the best setting angle, the angle 30, 35, 40 and 62 are respectively input into fast modeling and simulated again. Pressure and torque results are available through the Report-Force parameters, as listed in Table 2. Table 2 Impeller simulation data Blade number Setting angle/() Pressure difference/Pa Force(X-C)/N Torque/ (Nm) 30 0.270 1.600 0.062 35 0.255 1.520 0.070 40 0.326 1.877 0.070 5 62 0.128 0.660 0.047 6 40 0.219 1.238 0.075 7 40 0.382 2.230 0.090 9 40 0.283 1.524 0.105 From Table 2, it can be seen that when the blade number is five, the impellers maximum degree of torque in the installation angle is between 35 and 40. If the maximum torque is used as a design goal, then a few points can be calculated to find the best setting angle. The physical photo of the wind device is shown in Fig. 5. The practice has been proven: the design of the simulation calculation of the impeller has a large start torque and high efficiency, fully meeting the requirements. Blades 6, 7, 9 at setting angle of 40 are also calculated as a reference. Fig. 5 Wind physical device 5 Analysis of impeller torque calculation error Numerical simulation has the advantages of repeatability. Error between the numerical simulation and experimental results of the impeller torque is about 10% in this case, as shown in Fig. 6, the error may be as follows: J. Cent. South Univ. (2012) 19: 34303434 3434 Fig. 6 Calculated and experimental values of impeller torque 1) Physical model: The computational model does not consider the impact of the wind around the framework of and the rib plate, and the difference between the calculation model and the test model will lead to the difference of the calculated results. But computed torque and test torque value is consistent with the trend. 2) Mathematical model: In this work, the MRF model to deal with the problem of rotating machinery flows is an assumption of steady-state flow field calculation model, unsteady components in the design conditions in this flow field is small and this approximation is more reasonable. Therefore, the calculated values are in good agreement with experimental values of the design conditions. But in non-rated conditions, the leaf boundary layer separation occurs due to the strong non-stable ingredients in the flow field. Mutual collision occurs between the leaf boundary layer and fluid in the duct wall, then the error is larger. This may be the reasons for the difference of the non-design flow conditions and test values in performance curves. 6 Conclusions 1) According to the geometric relationship, the three-dimensional mathematical model of the impeller is established for a horizontal axis wind turbine blade design, and a programming language is used to achieve the parameter calculation of the aerodynamic blade design. The secondary development technique of UG is used in 3D modeling. 2) The spatial coordinates of each cross section data file calculated by design programs can be directly read, the three-dimensional solid blade can be automatically generated to achieve the impeller geometric modeling parameters and the rate of three-dimensional modeling is greatly accelerated in order to lay the foundation for integrated design of the wind turbine. The results greatly reduce the pre-treatment time on impeller CFD analysis. 3) The maximum start torque of the wind driven equipment is calculated by Fluent and the efficiency of it is enhanced greatly. References 1 CORALLO A, LAUBACHER R, MARGHERITA A, TURRISI G. Enhancing product development through knowledge-based engineering (KBE) J. Journal of Manufacturing Technology Management, 2009, 20(8): 10701083. 2 GUO Tao, YANG Hua-lin. Method for the combination of knowledge fusion and blurry inference J. Journal of Harbin Institute of Technology, 2006, 38(10): 18091812. (in Chinese) 3 LIU Xiao-ka, ZHU Xiao-cheng, DU Zhao-hu. The blade design and automatic modeling of horizontal axis wind turbine J. Energy Technology, 2010, 31(3): 155158. (in Chinese) 4 WANG Zheng, WU Hu, SHI Ya-feng, Wang Hong-bo. Application study on 3D modeling of axial compressor blades based on CFD and CAD J. Interna