Adjoint-Based High-Fidelity Structural Optimization of Wind-Turbine Blade for Load Stress Minimization

Anderson, Evan M.; Bhuiyan, Faisal H.; Mavriplis, Dimitri J.; Fertig, Ray S.

doi:10.2514/1.j057756

Cited by 15 publications

(6 citation statements)

References 23 publications

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“…This is in addition to the ease of mathematical constraints formulation possibility in multi-objective optimisation problems [14][15][16][17]20]. For example, Anderson et al [18] developed an adjoint-based multidisciplinary optimisation platform for optimising the structural properties of a 13 m scaled wind farm technology facility. They coupled the optimisation problem to the RANS fluid dynamics solver within a structural finite element method framework.…”

Section: Optimisationmentioning

confidence: 99%

“…These advanced multi-physics-based optimisation methods within CFD allow the creation of multiple engineering components in the wind and solar energy sectors. For example, they can enable the optimal design of future aerodynamic blades and the embedded electrical motor in a wind turbine for optimal performance [18]. They can also provide the optimal distribution of semiconductor materials used in PV cells and the optimal design of solar collectors [19].…”

Section: Introductionmentioning

confidence: 99%

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The Role of Computational Science in Wind and Solar Energy: A Critical Review

Drikakis

Dbouk

2022

Energies

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This paper concerns technology challenges for the wind and solar sectors and the role of computational science in addressing the above. Wind energy challenges include understanding the atmospheric flow physics, complex wakes and their interaction with wind turbines, aeroelastic effects and the associated impact on materials, and optimisation of wind farms. Concentrated solar power technologies require an optimal configuration of solar dish technology and porous absorber in the volumetric solar receiver for efficiency and durability and to minimise the convective heat losses in the receiver. Computational fluid dynamics and heat transfer have advanced in terms of numerical methods and physics-based models and their implementation in high-performance computing facilities. Despite this progress, computational science requires further advancement to address the technological challenges of designing complex systems accurately and efficiently, as well as forecasting the system’s performance. Machine Learning models and optimisation techniques can maximise the performance of simulations and quantify uncertainties in the wind and solar energy technologies. However, in a similar vein, these methods require further development to reduce their computational uncertainties. The need to address the global energy challenges requires further investment in developing and validating computational science methods and physics-based models for accurate and numerically efficient predictions at different scales.

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Section: Optimisationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Role of Computational Science in Wind and Solar Energy: A Critical Review

Drikakis

Dbouk

2022

Energies

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“…[6][7][8] Several authors have explored some specific issues of the structural optimization of the composite blades. In work by Anderson et al, 9 a high-fidelity multidisciplinary optimization capability is employed for the structural optimization of wind turbine blades. The optimal fiber angles distribution throughout the internal structure of the blade were sought to minimize a stress parameter for each of several load cases.…”

Section: Introductionmentioning

confidence: 99%

“…Buckney et al 14 utilized the topology optimization to find optimal structural configurations for a 3-MW wind turbine blade and saved weight by up to 13.8% compared to a conventional design. Generally speaking, there are two different approaches to achieve structural optimization of the blade: the first approach is the optimization in spanwise material distribution, the selection of materials, size of parts such as spar flange and shear webs through the knowledge of typical blade build-up and constraint [9][10][11][12] ; the other is topology optimization, which seeks the optimal material distribution. 13,14 Here the authors' focus will be the first approach.…”

Section: Introductionmentioning

confidence: 99%

Robust optimization for composite blade of wind turbine based on kriging model

Yan

Wei

et al. 2020

Advanced Composites Letters

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Structural optimization models often feature many uncertain factors, which can be handled by robust optimization. This work presents a complete robust optimization program for composite blade based on the kriging approximation model. Two case studies were given and performed using a genetic algorithm. The first being typical optimization, where the first natural frequency of the blade is selected as the optimized objective and the optimal sizing distribution for the entire blade shell is sought to ignore the uncertain factors. The other case determines the standard deviation of the optimized objective in the first case as another optimization goal. Moreover, a 6 σ robustness for the optimization results of the two cases was evaluated. The result shows that typical optimization increases the first natural frequency of the blade by 19%, while its robustness level has a reduction of 61% compared with the first blade. Nevertheless, the robust optimization not only results in an increment of 15.4% in the first natural frequency of the blade but also increases its robustness level by up to 90%. Therefore, the proposed approach can effectively improve optimization objectives, especially reduce the impacts of uncertainties on the objective functions.

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“…Initially introduced by Pironneau [27] for fluid mechanics, the adjoint method was subsequently adapted for aerodynamic shape optimization by Jameson [28]. The method has since been widely employed in gradient-based optimization for various applications, such as hydrodynamics [29,30], aerodynamics [19,[31][32][33][34][35][36], structures [37,38], and heat transfer [39,40].…”

Section: Adjoint Methodsmentioning

confidence: 99%

High-fidelity aerodynamic and aerostructural optimization of UAV propellers

Toman

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Adjoint-Based High-Fidelity Structural Optimization of Wind-Turbine Blade for Load Stress Minimization

Cited by 15 publications

References 23 publications

The Role of Computational Science in Wind and Solar Energy: A Critical Review

The Role of Computational Science in Wind and Solar Energy: A Critical Review

Robust optimization for composite blade of wind turbine based on kriging model

High-fidelity aerodynamic and aerostructural optimization of UAV propellers

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