Optimization of Tow-Steered Composite Wind Turbine Blades for Static Aeroelastic Performance Stephen Michael Barr Lehigh University
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Lehigh University Lehigh Preserve Theses and Dissertations 2018 Optimization of Tow-Steered Composite Wind Turbine Blades for Static Aeroelastic Performance Stephen Michael Barr Lehigh University Follow this and additional works at: https://preserve.lehigh.edu/etd Part of the Mechanical Engineering Commons Recommended Citation Barr, Stephen Michael, "Optimization of Tow-Steered Composite Wind Turbine Blades for Static Aeroelastic Performance" (2018). Theses and Dissertations. 4222. https://preserve.lehigh.edu/etd/4222 This Thesis is brought to you for free and open access by Lehigh Preserve. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of Lehigh Preserve. For more information, please contact [email protected]. Optimization of Tow-Steered Composite Wind Turbine Blades for Static Aeroelastic Performance by Stephen M. Barr A Thesis Presented to the Graduate and Research Committee of Lehigh University in Candidacy for the Degree of Master of Science in Mechanical Engineering and Mechanics Lehigh University May 2018 c Copyright by Stephen M. Barr 2018 All Rights Reserved ii This thesis is accepted and approved in partial fulfilment of the requirements for the degree of Master of Science in Mechanical Engineering. Date Dr. Justin W. Jaworski, Thesis Advisor Prof. D. Gary Harlow, Chairperson of Department of Mechanical Engineering and Mechanics iii Acknowledgements I would like to thank my advisor, Dr. Justin W. Jaworski, for the guidance and patience he provided to me throughout this research. I am grateful to not only have had his mentorship in this work, but also in future endeavors. I would also like to thank my employer, Combustion Research and Flow Technology, Inc., and my colleagues who have always been so generous to share their extensive knowledge and experience with me throughout my career and education at Lehigh. Thank you to my Mom, Dad, and brother for supporting me in the pursuit of my de- grees and in everything I do in my life. Finally, thank you to my wife, Kathleen. She inspires me to always be the best I can be, and my accomplishments mean so much more now that they are shared with her. iv Acronyms AEY Annual Energy Yield BEM Blade Element Momentum CAD Computer-Aided Design CFD Computational Fluid Dynamics FEA Finite Element Analysis HAWT Horizontal Axis Wind Turbine MPI Message Passing Interface NURBS Non-Uniform Rational B-Spline SLSQP Sequential Least Squares Quadratic Programming VAT Variable-Angle Tow v Contents Acknowledgements iv Acronyms v List of Tables viii List of Figures ix Abstract 1 1 Introduction 2 1.1 Literature Review . .4 1.1.1 Geometric-Adaptive Tailoring . .4 1.1.2 Material-Adaptive Tailoring . .7 1.2 Major Unresolved Issues . .9 1.3 Research Questions . 10 1.4 Technical Approach . 10 2 Methods and Models 12 2.1 Blade Geometry . 12 2.2 Fluid Model . 13 2.2.1 Incompressible Flow Solver . 13 2.2.2 Computational Fluid Dynamics Grid . 17 2.2.3 Turbulence Modeling . 21 vi 2.3 Structural Model . 22 2.4 Grid Deformation . 26 2.5 Fluid-Structure Coupling . 32 2.6 Optimization . 35 3 Results 38 3.1 Model Validation . 38 3.2 Wall Spacing Effects on Torque . 42 3.3 Optimization Results . 45 3.3.1 Optimization at Discrete Wind Speeds . 46 3.3.2 Design of Single Composite Layup for the Range of Wind Speeds . 52 3.3.3 Solution Dependency on Optimization Parameters . 60 4 Conclusions 64 4.1 Future Work . 65 Bibliography 66 Appendix A Betz Limit 71 Appendix B Converter for Gmsh to Abaqus Input File 75 Appendix C Python Script for Composite Fiber Orientation Specification 86 Appendix D Python Script for Transferring Pressure Loads Between CFD and FEA Grids 96 Biography 102 vii List of Tables 2.1 Airfoil properties for NREL 5-MW wind turbine blade . 14 2.2 Blade material properties . 24 3.1 Torque comparison with Hsu and Bazilevs . 39 3.2 Material properties of composite layup in blade skin used by Bazilevs et al. 42 3.3 Table of torque values for y+ = 1:0 and y+ = 20:0 and NREL report . 44 3.4 Blade RPM versus wind speed . 46 3.5 Comparison of efficiency between baseline and optimal blade designs . 48 viii List of Figures 1.1 Historical trend in wind turbine blade span . .3 1.2 Illustration of a swept twist adaptive rotor blade . .5 1.3 Sandia experimental swept twist adaptive rotor blade . .6 1.4 Illustration of extension-twist and bend-twist coupling . .7 2.1 NREL-5MW blade geometry . 14 2.2 CFD grid . 19 2.3 CFD boundary conditions . 19 2.4 Detail view of boundary layer grid on the blade . 20 2.5 Computational structural grid of NREL 5-MW blade . 22 2.6 Cross-sectional cut of computational structural grid . 23 2.7 Specification of composite fiber orientation along the blade span using a smooth function . 25 2.8 Blade surface pressures extracted from CFD simulation . 26 2.9 Execution time versus number of processors for parallel grid deformation tool 29 2.10 Speedup versus number of processors for parallel grid deformation tool . 30 2.11 Comparison of grid deformation solution using different elemental stiffnesses 33 2.12 Comparison of grid deformation convergence using different elemental stiff- nesses . 33 2.13 Information flow chart of the two-way fluid-structure coupling . 34 2.14 Illustration of the design variables in the optimization . 35 3.1 Frequency analysis of Hsu and Bazilevs unsteady blade tip displacement data 40 ix 3.2 Illustration of the composite layup used in the blade skin used by Bazilevs et al. ........................................ 41 3.3 Comparison of steady-state tip displacement with average values from Hsu and Bazilevs's unsteady results including gravitational effects . 43 3.4 Comparison of computed torque for y+ = 1:0 and y+ = 20:0 against NREL report data . 45 3.5 Objective function history for optimizations at each wind speed . 49 3.6 Optimal twist distribution for each wind speed . 50 3.7 Optimal composite fiber orientation angles as a function of span for each wind speed . 51 3.8 Contours of pressure coefficient for baseline and optimized blade design at a wind speed of 4.4 m/s . 53 3.9 Contours of pressure coefficient for baseline and optimized blade design at a wind speed of 6.7 m/s . 54 3.10 Contours of pressure coefficient for baseline and optimized blade design at a wind speed of 9.0 m/s . 55 3.11 Contours of pressure coefficient for baseline and optimized blade design at a wind speed of 11.4 m/s . 56 3.12 Comparison of thrust force over span between baseline and optimized blades at a wind speed of 4.4 m/s . 57 3.13 Comparison of thrust force over span between baseline and optimized blades at a wind speed of 6.7 m/s . 57 3.14 Comparison of thrust force over span between baseline and optimized blades at a wind speed of 9.0 m/s . 58 3.15 Comparison of thrust force over span between baseline and optimized blades at a wind speed of 11.4 m/s . 58 3.16 Comparison of original blade with blade modified for maximum torque at a wind speed of 4.4 m/s . 59 3.17 Comparison of power increases for Strategy #1 and Strategy #2 . 60 x 3.18 Optimal solution dependency on number of design variables when fiber ori- entations initialized spanwise . 61 3.19 Objective function history using different number of design variables when fiber orientations initialized spanwise . 62 3.20 Objective function history using different number of design variables when fiber orientations initialized to optimal solution using four design variables . 63 A.1 Illustration of the streamtube entering the wind turbine . 72 xi Abstract The concept of passive aeroelastic tailoring is explored to maximize the performance of the NREL 5-MW wind turbine blade in a uniform flow. Variable-angle tow composite materials model the spanwise-variable wind turbine blade design to allow material-adaptive bend- twist coupling under static aerodynamic loading. A constrained optimization algorithm determines the composite fiber angles along the blade span for four inflow conditions rang- ing from cut-in to rated wind speeds. The computational fluid dynamics solver CRUNCH CFD R and commercial finite element analysis solver Abaqus compute the static aero- dynamic loads and structural deformations of the blades, respectively, which are passed iteratively between the solvers until static aeroelastic convergence is achieved. A parallel grid deformation code based on the stiffness method is developed to deform the fluid mesh based on the structural deformation of the blade. The elemental stiffness is set to the inverse of the element volume to preserve the grid quality during grid deformation. Turbine power extraction is predicted to increase by up to 14% when the blade is opti- mized near the cut-in wind speed, and by 7% when optimized at rated wind speed. Using the results from optimizations at discrete wind speeds, two blade design strategies are evaluated to determine a single composite layup for the blade that maximizes performance over the range of wind speeds. The first strategy uses the composite layup optimized at the rated wind speed increasing power extraction by 10% near cut-in and 7% at rated con- ditions, relative to the baseline blade design. The second strategy seeks a new composite layup that most closely matches the optimal blade twist at each wind speed, which results in an increase in power extraction of 14% near cut-in and 3% at rated conditions. 1 Chapter 1 Introduction The goal of a wind turbine is to convert the kinetic energy of oncoming wind into electricity.