Articles | Volume 11, issue 4
https://doi.org/10.5194/wes-11-1487-2026
https://doi.org/10.5194/wes-11-1487-2026
Research article
 | 
30 Apr 2026
Research article |  | 30 Apr 2026

Efficient derivative computation for unsteady fatigue-constrained nonlinear aero-structural wind turbine blade optimization

Adam Cardoza and Andrew Ning

Related authors

Introduction to and comparison of deep learning and optimization approaches to analytical wake modeling of a tilted wind turbine
James Cutler, Christopher Bay, and Andrew Ning
Wind Energ. Sci., 11, 37–49, https://doi.org/10.5194/wes-11-37-2026,https://doi.org/10.5194/wes-11-37-2026, 2026
Short summary
A comparison of eight optimization methods applied to a wind farm layout optimization problem
Jared J. Thomas, Nicholas F. Baker, Paul Malisani, Erik Quaeghebeur, Sebastian Sanchez Perez-Moreno, John Jasa, Christopher Bay, Federico Tilli, David Bieniek, Nick Robinson, Andrew P. J. Stanley, Wesley Holt, and Andrew Ning
Wind Energ. Sci., 8, 865–891, https://doi.org/10.5194/wes-8-865-2023,https://doi.org/10.5194/wes-8-865-2023, 2023
Short summary
Aeroelastic Tailoring of Wind Turbine Rotors Using High-Fidelity Multidisciplinary Design Optimization
Marco Mangano, Sicheng He, Yingqian Liao, Denis-Gabriel Caprace, Andrew Ning, and Joaquim R. R. A. Martins
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-10,https://doi.org/10.5194/wes-2023-10, 2023
Revised manuscript not accepted
Short summary
Gradient-Based Wind Farm Layout Optimization Results Compared with Large-Eddy Simulations
Jared J. Thomas, Christopher J. Bay, Andrew P. J. Stanley, and Andrew Ning
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2022-4,https://doi.org/10.5194/wes-2022-4, 2022
Revised manuscript not accepted
Short summary
A model to calculate fatigue damage caused by partial waking during wind farm optimization
Andrew P. J. Stanley, Jennifer King, Christopher Bay, and Andrew Ning
Wind Energ. Sci., 7, 433–454, https://doi.org/10.5194/wes-7-433-2022,https://doi.org/10.5194/wes-7-433-2022, 2022
Short summary

Cited articles

Akima, H.: A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures, J. Assoc. Comput. Mach., 17, 589–602, https://doi.org/10.1145/321607.321609, 1970. a
Allen, J., Young, E., Bortolotti, P., King, R., and Barter, G.: Blade planform design optimization to enhance turbine wake control, Journal of Wind Energy, https://doi.org/10.1002/we.2699, 2020. a
American Society for Testing and Materials: Standard Practices for Cycle Counting in Fatigue Analysis, Tech. rep., https://doi.org/10.1520/E1049-85R17, 2017. a
Batay, S., Kamalov, B., Zhangaskanov, D., Zhao, Y., Wie, D., Zhou, T., and Su, X.: Adjoint-Based High Fidelity Concurrent Aerodynamic Design Optimization of Wind Turbine, Fluids, https://doi.org/10.3390/fluids8030085, 2023. a
Bezanson, J., Edelman, A., Karpinski, S., and Shah, V. B.: Julia: A fresh approach to numerical computing, SIAM Rev., 59, 65–98, https://doi.org/10.1137/141000671, 2017. a
Download
Short summary
New software calculates wind turbine blade design improvements 10 times faster than traditional methods while maintaining accuracy. By combining four advanced mathematical techniques, researchers optimized a blade design to reduce energy costs by 12.78 %, making fatigue-aware design practical for engineering applications.
Share
Altmetrics
Final-revised paper
Preprint