Research on structural optimization methods for ultra-long flexible blades considering the multi-scale characteristics of composite materials

With the trend toward larger wind turbines, the increasing length of blades affects both power generation and safety. This study employs the MCT multi-scale failure criterion to investigate the multi-scale characteristics of woven composite materials. The performance parameters are predicted using a meso-scale model, and the results are applied to the structural analysis and optimization of blades. The results show that the material properties predicted by the multiscale method exhibit less than 10% error compared with experimental data. The optimized structure demonstrates significant improvement in axial stiffness with less than 3% mass variation. Reducing the layup mass at the blade tip while increasing mass in the mid-section effectively enhances structural performance. These findings provide valuable guidance for the structural design of ultra-long flexible blades in large wind turbines.

Authors

Institutions

Publication Details

Journal
IET conference proceedings.
Published
2026-02-19
DOI
https://doi.org/10.1049/icp.2025.3913
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on structural optimization methods for ultra-long flexible blades considering the multi-scale characteristics of composite materials

Guangchuan Cao, Hang Meng, Xia Guo
IET conference proceedings.
Wind Energy Research and Development
article

Research on structural optimization methods for ultra-long flexible blades considering the multi-scale characteristics of composite materials

Guangchuan Cao, Hang Meng, Xia Guo
article en

Abstract

With the trend toward larger wind turbines, the increasing length of blades affects both power generation and safety. This study employs the MCT multi-scale failure criterion to investigate the multi-scale characteristics of woven composite materials. The performance parameters are predicted using a meso-scale model, and the results are applied to the structural analysis and optimization of blades. The results show that the material properties predicted by the multiscale method exhibit less than 10% error compared with experimental data. The optimized structure demonstrates significant improvement in axial stiffness with less than 3% mass variation. Reducing the layup mass at the blade tip while increasing mass in the mid-section effectively enhances structural performance. These findings provide valuable guidance for the structural design of ultra-long flexible blades in large wind turbines.

IET conference proceedings.Vol. 2025(38)
North China Electric Power University (CN), Beijing Academy of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 52%
Wind Energy Research and Development
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.