Cited by 18Wind Energy Research and DevelopmentMechanical Behavior of CompositesFiber-reinforced polymer composites

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Recent Advances in the Analysis of Functional and Structural Polymer Composites for Wind Turbines

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Abstract

Achieving the full potential of wind energy in the global renewable transition depends critically on enhancing the performance and reliability of polymer composite components. This review synthesizes recent advances from 2022 to 2025, including the development of next-generation hybrid composites and the application of high-fidelity computational methods—finite element analysis (FEA), computational fluid dynamics (CFD), and fluid–structure interaction (FSI)—to optimize structural integrity and aerodynamic performance. It also explores the transformative role of artificial intelligence (AI) in structural health monitoring (SHM) and the integration of Internet of Things (IoT) systems, which are becoming essential for predictive maintenance and lifecycle management. Special focus is given to harsh offshore environments, where polymer composites must withstand extreme wind and wave conditions. This review further addresses the growing importance of circular economy strategies for managing end-of-life composite blades. While innovations such as the geometric redesign of floating platforms and the aerodynamic refinement of blade components have yielded substantial gains—achieving up to a 30% mass reduction in PLA prototypes—more conservative optimizations of internal geometry configurations in GFRP blades provide only around 7% mass reduction. Nevertheless, persistent challenges related to polymer composite degradation and fatigue under severe weather conditions are driving the adoption of real-time hybrid predictive models. A bibliometric analysis of over 1000 publications confirms more than 25 percent annual growth in research across these interconnected areas. This review serves as a comprehensive reference for engineers and researchers, identifying three strategic frontiers that will shape the future of wind turbine blade technology: advanced composite materials, integrated computational modeling, and scalable recycling solutions.

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Metadata

Authors
Lagos, F., Menacer, B., Salas, A., Narayan, S., Medina, C., Valle, R., Garrido, C., Pincheira, G., Oñate, A., Hunter-Alarcón, R., & Tuninetti, V.
Affiliations
  • Universidad de La Frontera (CL)
  • Ecole Supérieure en Génie Electrique et Energétique d'Oran (DZ)
  • University of Concepción (CL)
  • Tecnológico de Monterrey (MX)
  • Universidad Autónoma de Chile (CL)
  • University of Bío-Bío (CL)
  • Universidad de Talca (CL)
  • Department of Materials Engineering (DIMAT), Faculty of Engineering, Universidad de Concepción, Concepción 4070138, Chile
  • Composite Materials Laboratory, Department of Mechanical Engineering, Universidad de La Frontera, Temuco 4780000, Chile
Corresponding author
Tuninetti, Víctor
Venue
Polymers
Publisher
MDPI AG
Published
2025-08-28
Volume
17
Issue
17
Pages
2339
ISSN
2073-4360 (ISSN-L)
OpenAlex
W4413779607
Cited by
18
References
184
Citations by year
2026: 15 · 2025: 3
FWCI
0.80
Type
journal article
Language
en
Open access
Locations
  • Polymers (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • Omeka S (Universidad de La Frontera) (submittedVersion, cc-by-nc-nd)
Topics
  • Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Wind Energy Research and Development
  • Physical Sciences › Engineering › Mechanics of Materials › Mechanical Behavior of Composites
  • Physical Sciences › Engineering › Mechanical Engineering › Fiber-reinforced polymer composites
Keywords
wind turbine blades, polymer composites, hybrid composites, finite element analysis, computational fluid dynamics, fluid-structure interaction, structural health monitoring, artificial intelligence, Internet of Things, predictive maintenance, offshore wind energy, composite recycling, circular economy, composite degradation, fatigue (material), mass reduction, aerodynamic optimization

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