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Article: Integrated design framework of next-generation 85-m wind turbine blade: Modelling, aeroelasticity and optimization

TitleIntegrated design framework of next-generation 85-m wind turbine blade: Modelling, aeroelasticity and optimization
Authors
Issue Date2018
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/compositesb
Citation
Composites Part B: Engineering, 2018, v. 159, p. 53-61 How to Cite?
AbstractThe National Energy Administration of China has promoted the use of wind energy to replace the conventional fossil energy, which provides an inexhaustible and eco-friendly alternative to the increasing energy demand. 10-MW wind turbine is the next-generation turbine with 85-m blade length, which poses great challenges in the engineering design, manufacturing, transportation, installation and maintenance. The paper aims to establish a numerical framework that integrates 3D full-scale modelling, analysis and parametric optimization. Isogeometric Analysis (IGA) enables seamless integration between structural modelling and computational analysis by using NURBS as basis functions. Aerodynamic forces and rotor power of blade subject to wind will be obtained by FAST. The Kirchhoff-Love shell element will be employed for 3D blade modelling to reduce rotational degrees of freedom and alleviate shear locking. The integrated framework residing within Rhino-based Grasshopper will be performed to model and analyse the wind turbine. Parametric optimization using pattern search algorithm targets at a family of turbines that satisfies the Tsai-Wu failure criterion and deformation constraint. The framework is deployed on a 10-MW turbine blade based on the initial design upscaled from the NREL 5-MW baseline model. The optimal blade design with shear webs has gained 20.9% improvement in performance.
Persistent Identifierhttp://hdl.handle.net/10722/264573
ISSN
2019 Impact Factor: 7.635
2015 SCImago Journal Rankings: 2.125

 

DC FieldValueLanguage
dc.contributor.authorDeng, X-
dc.contributor.authorWu, N-
dc.contributor.authorYang, K*-
dc.contributor.authorChan, WL-
dc.date.accessioned2018-10-22T07:57:12Z-
dc.date.available2018-10-22T07:57:12Z-
dc.date.issued2018-
dc.identifier.citationComposites Part B: Engineering, 2018, v. 159, p. 53-61-
dc.identifier.issn1359-8368-
dc.identifier.urihttp://hdl.handle.net/10722/264573-
dc.description.abstractThe National Energy Administration of China has promoted the use of wind energy to replace the conventional fossil energy, which provides an inexhaustible and eco-friendly alternative to the increasing energy demand. 10-MW wind turbine is the next-generation turbine with 85-m blade length, which poses great challenges in the engineering design, manufacturing, transportation, installation and maintenance. The paper aims to establish a numerical framework that integrates 3D full-scale modelling, analysis and parametric optimization. Isogeometric Analysis (IGA) enables seamless integration between structural modelling and computational analysis by using NURBS as basis functions. Aerodynamic forces and rotor power of blade subject to wind will be obtained by FAST. The Kirchhoff-Love shell element will be employed for 3D blade modelling to reduce rotational degrees of freedom and alleviate shear locking. The integrated framework residing within Rhino-based Grasshopper will be performed to model and analyse the wind turbine. Parametric optimization using pattern search algorithm targets at a family of turbines that satisfies the Tsai-Wu failure criterion and deformation constraint. The framework is deployed on a 10-MW turbine blade based on the initial design upscaled from the NREL 5-MW baseline model. The optimal blade design with shear webs has gained 20.9% improvement in performance.-
dc.languageeng-
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/compositesb-
dc.relation.ispartofComposites Part B: Engineering-
dc.titleIntegrated design framework of next-generation 85-m wind turbine blade: Modelling, aeroelasticity and optimization-
dc.typeArticle-
dc.identifier.emailDeng, X: xwdeng@hku.hk-
dc.identifier.authorityDeng, X=rp02223-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.compositesb.2018.09.028-
dc.identifier.hkuros295216-
dc.identifier.volume159-
dc.identifier.spage53-
dc.identifier.epage61-
dc.publisher.placeUnited Kingdom-

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