Towards Passive Aeroelastic Tailoring of Large Wind Turbines Using High-Fidelity Multidisciplinary Design Optimization

Mangano, Marco; He, Sicheng; Liao, Yingqian; Caprace, Denis-Gabriel; Martins, Joaquim R. R. A.

doi:10.2514/6.2022-1289

Cited by 7 publications

(9 citation statements)

References 63 publications

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“…We use our MDO framework, MACH, to perform aerostructural optimization studies using high-fidelity CFD and CSM analysis tools . This framework uses a coupled-adjoint approach for gradient computation and has been extensively used for wing Liem et al, 2015;Burdette and Martins, 2018;Brooks et al, 2018Brooks et al, , 2019Bons et al, 2022;Brooks et al, 2020;Bons and Martins, 2020) and hydrofoil design (Garg et al, 2017(Garg et al, , 2019Liao et al, 2021Liao et al, , 2022. This paper applies the same methodology to a high-fidelity wind turbine aerostructural model to demonstrate the potential performance and mass reduction benefits of integrating this approach in rotor blade design.…”

Section: Contributions and Outlinementioning

confidence: 99%

“…The assumptions on our structural model are discussed in Section 4. Our previous paper also included tip displacement constraints (Mangano et al, 2022), which will be the object of future studies.…”

Section: Contributions and Outlinementioning

confidence: 99%

“…The panel discretization follows the main geometry breaks of the outer mold line. Our previous work (Mangano et al, 2022) compared different parametrization approaches, and future developments of the structural model will analyze the effects of structural design variables distribution in more detail. The structural analysis with fixed loads is faster than the aerodynamic analysis by more than four orders of magnitude on average, considering the L1 aerodynamic mesh we use in this study.…”

Section: Structural Modelmentioning

confidence: 99%

“…The present work expands and supersedes the conference proceedings of Mangano et al (2022) by using updated tools and models to increase the complexity of the optimization studies and extend the design space exploration scope. The following section reviews the state-of-the-art for wind turbine design optimization and highlights our contributions to large wind turbine rotor designs.…”

Section: Introductionmentioning

confidence: 96%

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Aeroelastic Tailoring of Wind Turbine Rotors Using High-Fidelity Multidisciplinary Design Optimization

Mangano

Liao

et al. 2023

Preprint

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Abstract. Reducing the cost of energy from wind power is a critical step towards decarbonizing the electric grid and mitigating climate change effects. Computational models are crucial in understanding the complex, multiphysics interactions of modern, highly flexible wind turbine rotors. When coupled with numerical optimization, such models provide an efficient way to explore the design space. We propose a high-fidelity aerostructural framework that couples computational fluid dynamics with 5 computational structural mechanics to analyze and optimize wind turbines. The framework uses a gradient-based optimization strategy with gradients efficiently computed using a coupled-adjoint approach. We optimize a benchmark utility-scale wind turbine rotor and explore its trade-offs between steady-state aerodynamic efficiency and structural weight. The optimizations account for a representative below-rated operating condition and use more than 100 structural and geometric design variables. The monolithic approach we propose is compared with a loosely-coupled optimization strategy used for the structural sizing 10 of the baseline rotor layout. We then discuss specific optimized blade features and a broader design trade space exploration between extracted torque and rotor mass. Optimized layouts increase the torque by up to 14 % and reduce the mass by up to 9 % or reduce the mass by up to 27 % with the same torque output compared to the baseline blade. The results demonstrate the benefits of optimizing a tightly-coupled aerostructural model and reveal additional insights that high-fidelity analysis provide to complement conventional design approaches.

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Section: Contributions and Outlinementioning

confidence: 99%

Section: Contributions and Outlinementioning

confidence: 99%

Section: Structural Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

See 2 more Smart Citations

Aeroelastic Tailoring of Wind Turbine Rotors Using High-Fidelity Multidisciplinary Design Optimization

Mangano

Liao

et al. 2023

Preprint

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“…This approach was made computationally tractable thanks to analytic gradients, though the cost of the RANS CFD still greatly increased the optimization cost. Frameworks implementing 3D blade-resolved simulations exist for analysis purposes and researchers have made inroads to inclusion within a design optimization, although the high computational requirements and software complexities have so far limited the application to niche design scenarios [10,11].…”

Section: Introductionmentioning

confidence: 99%

Wind turbine blade design with airfoil shape control using invertible neural networks

Jasa

Glaws

Bortolotti

et al. 2022

J. Phys.: Conf. Ser.

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Wind turbine blade design is a highly multidisciplinary process that involves aerodynamics, structures, controls, manufacturing, costs, and other considerations. More efficient blade designs can be found by controlling the airfoil cross-sectional shapes simultaneously with the bulk blade twist and chord distributions. Prior work has focused on incorporating panel-based aerodynamic solvers with a blade design framework to allow for airfoil shape control within the design loop in a tractable manner. Including higher fidelity aerodynamic solvers, such as computational fluid dynamics, makes the design problem computationally intractable. In this work, we couple an invertible neural network trained on high-fidelity airfoil aerodynamic data to a turbine design framework to enable the design of airfoil cross sections within a larger blade design problem. We detail the methodology of this coupled framework and showcase its efficacy by aerostructurally redesigning the IEA 15-MW reference wind turbine blade. The coupled approach reduces the cost of energy by 0.9% compared to a more conventional design approach. This work enables the inclusion of high-fidelity aerodynamic data earlier in the design process, reducing cycle time and increasing certainty in the performance of the optimal design.

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Multi-material and thickness optimization of a wind turbine blade root section

Hermansen,

Lund

2024

Struct Multidisc Optim

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Structural optimization has been shown to be an invaluable tool for solving large-scale challenging design problems, and this work concerns such optimization of a state-of-the-art laminated composite wind turbine blade root section. For laminated composites structures, the key design parameters are material choice, fiber orientation, stacking sequence, and layer thickness, however a framework for treating these simultaneously in optimization, on the current wind turbine blade scale, has not been demonstrated. Thus, the motivation and novelty of the present work is providing and demonstrating a general gradient-based approach applicable to wind turbine blades, where the key design parameters and structural criteria, i.e., buckling, static strength, and fatigue damage, are considered for multiple design load cases. The optimization framework is based on a variation of the Discrete Material and Thickness Optimization approach, where the thickness is directly parametrized, allowing for appropriately treating the sandwich parts of the blade. It is demonstrated how optimization leads to a design consisting of complex variable-thickness laminates, a good overall distribution of the structural criteria in the model, and a significant reduction in mass compared to the initial design.

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Towards Passive Aeroelastic Tailoring of Large Wind Turbines Using High-Fidelity Multidisciplinary Design Optimization

Cited by 7 publications

References 63 publications

Aeroelastic Tailoring of Wind Turbine Rotors Using High-Fidelity Multidisciplinary Design Optimization

Aeroelastic Tailoring of Wind Turbine Rotors Using High-Fidelity Multidisciplinary Design Optimization

Wind turbine blade design with airfoil shape control using invertible neural networks

Multi-material and thickness optimization of a wind turbine blade root section

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