FLUID STRUCTURE INTERACTION MODELLING OF WIND TURBINE BLADES BASED ON COMPUTATIONAL FLUID DYNAMICS AND FINITE ELEMENT METHOD

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1 Proceedings of the 6th International Conference on Mechanics and Materials in Design, Editors: J.F. Silva Gomes & S.A. Meguid, P.Delgada/Azores, July 2015 PAPER REF: 5769 FLUID STRUCTURE INTERACTION MODELLING OF WIND TURBINE BLADES BASED ON COMPUTATIONAL FLUID DYNAMICS AND FINITE ELEMENT METHOD Athanasios Kolios 1(*), Lin Wang 1 1 Offshore Renewable Energy Centre, School of Energy, Environment and Agrifood, Cranfield University, UK (*) a.olios@cranfield.ac.u ABSTRACT The increasing size and flexibility of large wind turbine blades introduces considerable aeroelastic effects, which are caused by FSI (Fluid Structure Interaction). These effects might result in aeroelastic instabilities problems, such as edgewise instability and flutter, which can be devastating to the blades and the wind turbine. Therefore, accurate FSI modelling of wind turbine blades is crucial in the development of large wind turbines. In this study, a FSI model for wind turbine blades at full scale is established. The aerodynamic loads are calculated using CFD (Computational Fluid Dynamics), and the blade structural responses are determined using FEA (Finite Element Analysis). The coupling of CFD and FEA is based on the one-way coupling, in which the aerodynamic loads calculated from CFD modelling are mapped to FEA modelling as load boundary conditions. A 5MW horizontal-axis wind turbine blade is chosen as a case study. The blade pressure distributions, blade stress distributions and blade deformation are investigated based on the one-way FSI modelling. Keywords: Wind turbine blade, FSI (Fluid Structure Interaction), CFD (Computational Fluid Dynamics), FEM (Finite Element Method). INTRODUCTION The size of large wind turbines has increased dramatically in recent years. The increasing size and flexibility of large wind turbine blades introduces significant aeroelastic effects, which are caused by FSI (Fluid-Structure Interaction). Specifically, during the operation of wind turbines, the blade experiences deformation due to aerodynamic loads. The deformed blade affects in turn the surrounding flow field, which in return influences the aerodynamic loads on the blade. The interaction of fluid and structure might result in aeroelastic instability problems, such as edgewise instability and flutter, which can be devastating to the blade and the wind turbine. Therefore, accurate FSI modelling of wind turbine blades is crucial in the development of large wind turbines. FSI modelling requires an aerodynamic part to calculate the wind loads and a structural part to determine structural responses. For the aerodynamic part, BEM (Blade Element Momentum) model (Glauert, 1935) has been extensively used due to its efficiency and reasonable accuracy. The high efficiency of the BEM model also maes it suitable for design optimisation, which generally involves a large number of case studies. Based on the BEM model and different optimisation strategies, a series of case studies have been performed to optimise the aerodynamic performance for both fixed-speed wind turbine blades (Wang et al., 2012a, Liu et al., 2013) and variable-speed wind turbine blades (Wang et al., 2012b, Zhao et al., 2012). However, the BEM model is incapable of providing detailed information on the -967-

2 Trac_L Energy and Thermo-Fluids Systems flow field, such as flow visualisation and wae development. These information are important for wind turbine designers to have a better understanding of the flow field around the blade and to further improve the design. Obtaining detailed information on the flow field requires more advanced aerodynamic models. One well-nown example is the CFD (Computational Fluid Dynamics) model, which has been receiving great attention in recent years due to the rapid advancement of computer technology. For the structural part of FSI modelling, beam models have been widely used due to their efficiency and reasonable accuracy. Based on a nonlinear beam model, authors have developed a nonlinear aeroelastic model for wind turbine blades(wang et al., 2014b). The beam model is characterised by cross-sectional properties, such as mass per unit length and cross-sectional stiffness, which can be obtained by using specialised cross-sectional models (Wang et al., 2014a). However, the beam model is incapable of providing some important information for the blade design, such as detailed stress distributions within the blade structure. To obtain these detailed information, it is necessary to construct the blade using 3D (three-dimensional) finite element analysis (FEA). One challenge facing wind turbine designers today is to couple CFD and FEA for FSI modelling. The coupling methods for FSI modelling can be categorised into two groups, i.e. two-way coupling and one-way coupling. In the two-way coupling, the results of the aerodynamic model are mapped to the structural model and these results are mapped bac to the aerodynamic model and so on until convergence is reached or the process is terminated manually. The two-way coupling is time-consuming because it requires a time-dependent analysis and involves the modification of the mesh of both aerodynamic model and structural model. In case of the one-way coupling, the results of the aerodynamic model are mapped to the structural model, but the results of the structural model are not mapped bac to the aerodynamic model. The one-way coupling does not include the modification of any of the meshes and it allows a steady analysis, saving much computational resources compared to the two-way coupling. Therefore, the one-way coupling is commonly used as the first attempt of the FSI modelling. In this study, a FSI model for wind turbine blades at full scale is established. The aerodynamic forces are calculated using CFD and blade structural responses are determined using FEA. The coupling strategy is based on the one-way coupling strategy, in which aerodynamic loads calculated from CFD modelling are imported to FEA modelling as load boundary conditions. The established FSI model is applied to the simulation of NREL(National Renewable Energy Laboratory) 5MW horizontal-axis wind turbine (Jonman et al., 2009), a representative of megawatt-class horizontal-axis wind turbines. METHODS Wind Turbine Model The wind turbine model used in this study is the NREL 5MW wind turbine (Jonman et al., 2009), which is a reference turbine created by NREL to support concept studies aimed at assessing offshore wind turbine technology. This wind turbine is a conventional three-bladed upwind horizontal-axis turbine, utilising variable-speed variable-pitch control. The main parameters of the turbine are summarised in Table

3 Proceedings of the 6th International Conference on Mechanics and Materials in Design, Editors: J.F. Silva Gomes & S.A. Meguid, P.Delgada/Azores, July 2015 Table 1 - Main parameters of NREL 5MW wind turbine Parameters Values Rated power (MW) 5 Number of blades 3 Rotor radius (m) 63 Rated wind speed (m/s) 11.4 Rated rotor rotational speed (rpm) 12.1 The chord and twist angle distributions of NREL 5MW wind turbine blade are depicted in Fig. 1, and its details can be found in Ref. (Jonman et al., 2009). The 3D geometry model of the blade is illustrated in Fig Chord (m) r/r Twist (deg.) r/r Fig. 1 - Chord and twist angle distributions of NREL 5MW wind turbine blade CFD MODELLING Fig. 2-3D geometry model of NREL 5MW wind turbine blade Computational domain and boundary conditions The three blades of the rotor are symmetric and therefore only a single blade is needed in the CFD modelling. Fig. 3 depicts the computational domain and boundary conditions. As it can be seen from Fig. 3, the computational domain is a one-third sector domain. The upstream velocity inlet boundary is 3 times of blade radius in front of the rotor plane, and its radius is also 3 times of blade radius. The pressure outlet boundary is 6 times of blade radius behind the rotor plane, and its radius is also 6 times of blade radius. The top surface of the computational domain is also considered to be the velocity inlet boundary. The inlet wind -969-

4 Trac_L Energy and Thermo-Fluids Systems velocity and outlet pressure equal to the free-stream wind velocity and standard atmospheric pressure, respectively. Periodic boundary conditions are applied to symmetric planes to tae account of the remaining blades. The blade is regarded as a stationary non-slip wall, and a rotating frame is applied to the whole computational domain to tae account of the rotor rotational speed. Fig. 3 - Computational domain and boundary conditions for CFD modelling CFD Mesh Fig. 4 presents the mesh of the computational domain. The computational domain is meshed with unstructured mesh. As illustrated in Fig. 5, prism layers are applied to the blade surfaces to have a better resolution of boundary layer flow. The element size of blade surfaces is 0.1m, and the element size of the remaining surfaces is 2m. The total cell number of the computational domain is approximately 2.4 million. Fig. 4 - CFD mesh -970-

5 Proceedings of the 6th International Conference on Mechanics and Materials in Design, Editors: J.F. Silva Gomes & S.A. Meguid, P.Delgada/Azores, July 2015 Fig. 5 - Prism layers on blade surfaces Turbulence model In the present study, the SST (shear-stress transport) model is chosen to model the turbulent flow. The SST model is a two-equation turbulence model developed by Menter(FLORIAN, 1993, Menter, 1994). The model is a combination of the model, which is ideal for simulating flow in the near-wall region, and the ε model, which is well suited for modelling flow in the far field. In the SST model, the model is used in the near-wall region and switches to the ε in the free stream, well utilising the advantages of both and ε models. The SST model has been widely used for CFD modelling of wind turbine blades, showing very promising results for separate flows (Mo and Lee, 2012). The turbulence inetic energy and specific dissipation rate in the SST calculated using the following transport equations (Fluent, 2013): t t x ( ρ) + ( ρu ) x = ( ρ) + ( ρu ) i i i i x = j x Γ j Γ x j ~ + G + G x j Y Y + S + D + S model are (Eq.1) where t is the time; ρ is the fluid density; Γ and Γ respectively represent the effective diffusivity of and ; G ~ represents the generation of turbulence inetic energy caused by mean velocity gradients; G represents the generation of ; Y and Y respectively represent the dissipation of and due to turbulence; D represents the cross-diffusion term; S and S are user-defined source terms

6 Trac_L Energy and Thermo-Fluids Systems Solution method For wind turbine blades, the relative wind speed is much lower than the speed of sound and therefore the flow can be considered incompressible. In this study, the air density is regarded as a constant with a value of 1.225g/m 3. The incompressible Reynolds-Averaged Navier- Stoes (RANS) equations are solved using the pressure-based coupled algorithm (Fluent, 2013), which solves the momentum equation and the pressure-based continuity equation in a closely coupled manner. Compared to the pressure-based segregated algorithm, in which the momentum equation and pressure-based continuity equations are solved separately, the pressure-based coupled algorithm significantly improves the rate of solution convergence. Additionally, it wors very efficiently for transient problems when larger time steps are required. FEA MODELLING Material properties Wind turbine blades are generally made of composite materials due to their high strength-toweight ratio and good fatigue performance. Shear webs are generally used within the blade structure in order to further enhance the strength of the blade. However, the detailed structural layout data of the NREL 5MW wind turbine blade, such as shear web locations and composite layups, are not publicly available. For this reason, the blade structure in this study is simply assumed to be made of a single composite material and the shear webs are ignored. The material properties of the blade used in this study are listed in Table 2. Table 2 - Material properties of the blade E x (GPa) E y (GPa) G xy (GPa) v ρ (g/m 3 ) xy FEA Mesh and blade thicness distribution Fig. 6 presents the mesh of the blade structure. The blade structure is meshed using structured mesh with shell elements. The mesh size is 0.3m, and the total number of shell elements is 3,256. Fig. 6 - Mesh of blade structure For a wind turbine blade, the sectional loads (such as resultant forces and moments) increase from the blade tip to the blade root. Therefore, the blade root requires thicer structure than the blade tip in order to resist the loads. In this study, the thicness of the blade structure is assumed to decrease linearly from the blade root with a value of 0.10m to the blade tip with a value of 0.01m, as illustrated in Fig

7 Proceedings of the 6th International Conference on Mechanics and Materials in Design, Editors: J.F. Silva Gomes & S.A. Meguid, P.Delgada/Azores, July Thicness (m) Boundary conditions r/r Fig. 7 - Thicness distribution of blade structure In addition to aerodynamic loads, there are two other important sources of loads on the blades, i.e. 1) gravity loads, which are introduced by the gravity of the blades; and 2) centrifugal loads, which are caused by the rotation of the blades. In this study, the rotor rotational speed is applied to the blade structure to tae account of the centrifugal loads, and the gravity loads are also applied to the blade structure. Additionally, a fixed boundary condition is applied to the blade root. ONE-WAY FSI COUPLING In this study, the coupling method of the FSI modelling is based on the one-way coupling, in which the aerodynamic loads calculated from CFD modelling are mapped to FEA modelling as load boundary conditions. The schematic of the one-way FSI modelling is presented in Fig. 8. Fig. 8 - Schematic of one-way FSI modelling The CFD modelling presented in Section 2.2 is implemented using ANSYS FLUENT (Fluent, 2013) and the FEA modelling presented in Section 2.3 is implemented using ANSYS static -973-

8 Trac_L Energy and Thermo-Fluids Systems structural module(ansys, 2013). The one-way coupling of CFD and FEA is implemented using ANSYS Worbench, as illustrated in Fig. 9. Fig. 9 - Schematic of one-way FSI modelling in ANSYS Worbench RESULTS AND DISCUSSIONS Based on the one-way FSI modelling, the pressure distributions, blade deformation and blade stress distributions of the NREL 5MW wind turbine blade are examined. In this case, the wind speed, rotor rotational speed and blade pitch angle are 11.4m/s, 12.1rpm and 0, respectively. The pressure distributions on the blade pressure side and the blade suction side are presented in Fig.10. Figs. 11 and 12 illustrate the blade deformation and stress distributions, respectively. Fig Blade pressure distributions -974-

9 Proceedings of the 6th International Conference on Mechanics and Materials in Design, Editors: J.F. Silva Gomes & S.A. Meguid, P.Delgada/Azores, July 2015 Fig Blade deformation Fig Blade stress distributions From Fig. 10 we can see that the pressure in front of the blade is higher than the pressure behind the blade. The pressure difference produces the thrust force on the blade. From Fig. 11 we can see that the maximum blade deformation is about 0.797m, occurring at the blade tip. As can be seen from Fig. 12, the maximum von-mises stress is MPa, which is within the allowable stress

10 Trac_L Energy and Thermo-Fluids Systems 4. CONCLUSION In this study, a FSI model for wind turbine blades has been established by coupling CFD (computational fluid dynamics) and FEA (finite element analysis). The coupling strategy is based on one-way coupling, in which the aerodynamic loads calculated by CFD modelling are mapped to FEA modelling as load boundary conditions. The FSI model has been applied to NREL 5MW wind turbine blade, a representative of large-scale horizontal-axis wind turbine blades. The pressure distributions, blade stress distributions and blade deformation have been examined based on the one-way FSI modelling. Future wors include the two-way FSI modelling and aeroelastic stability analysis of largescale wind turbine blades. REFERENCES [1]-ANSYS, A Version 15.0; ANSYS. Inc.: Canonsburg, PA, USA November. [2]-FLORIAN, R. M Zonal two equation - turbulence models for aerodynamic flows. AIAA Paper [3]-FLUENT, A Ansys fluent 15.0 theory guide. Ansys Inc. [4]-GLAUERT, H Airplane propellers. Aerodynamic theory, 4, [5]-JONKMAN, J. M., BUTTERFIELD, S., MUSIAL, W. & SCOTT, G Definition of a 5-MW reference wind turbine for offshore system development, National Renewable Energy Laboratory Golden, CO. [6]-LIU, X., WANG, L. & TANG, X Optimized linearization of chord and twist angle profiles for fixed-pitch fixed-speed wind turbine blades. Renewable Energy, 57, [7]-MENTER, F. R Two-equation eddy-viscosity turbulence models for engineering applications. AIAA journal, 32, [8]-MO, J.-O. & LEE, Y.-H CFD Investigation on the aerodynamic characteristics of a small-sized wind turbine of NREL PHASE VI operating with a stall-regulated method. Journal of mechanical science and technology, 26, [9]-WANG, L., LIU, X., GUO, L., RENEVIER, N. & STABLES, M. 2014a. A mathematical model for calculating cross-sectional properties of modern wind turbine composite blades. Renewable Energy, 64, [10]-WANG, L., LIU, X., RENEVIER, N., STABLES, M. & HALL, G. M. 2014b. Nonlinear aeroelastic modelling for wind turbine blades based on blade element momentum theory and geometrically exact beam theory. Energy, 76, [11]-WANG, L., TANG, X. & LIU, X. 2012a. Blade Design Optimisation for Fixed-Pitch Fixed-Speed Wind Turbines. ISRN Renewable Energy. [12]-WANG, L., TANG, X. & LIU, X. 2012b. Optimized chord and twist angle distributions of wind turbine blade considering Reynolds number effects. WEMEP. India. [13]-ZHAO, J., LIU, X. W., WANG, L. & TANG, X. Z Design attac angle analysis for fixed-pitch variable-speed wind turbine. Advanced Materials Research, 512,