Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 894-903 |
| Seitenumfang | 10 |
| Fachzeitschrift | Composite Structures |
| Jahrgang | 184 |
| Frühes Online-Datum | 2 Nov. 2017 |
| Publikationsstatus | Veröffentlicht - 15 Jan. 2018 |
Abstract
This paper presents a novel methodology to simultaneously determine the optimal ply-order, ply-number and ply-drop configuration of laminate wind turbine blades using simulation-based optimization, considering the shape that the laminates are expected to attain after large elastic deformations. This methodology combines Genetic Algorithms with the Inverse Finite Element Method. As an actual engineering application, we redesigned the composite stacking layout of a medium-power 40-kW wind turbine blade to reduce its weight, subjected to mechanical and manufacturing constraints such as allowable tip deflection, maximum stress, natural frequencies, and maximum number of successive identical plies. Results demonstrate weight reductions of up to 15% compared to the initial layout, proving that the proposed methodology is a robust redesign tool capable of effectively determining the optimal composite stacking layout of laminate wind turbine blades.
ASJC Scopus Sachgebiete
- Werkstoffwissenschaften (insg.)
- Keramische und Verbundwerkstoffe
- Ingenieurwesen (insg.)
- Tief- und Ingenieurbau
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in: Composite Structures, Jahrgang 184, 15.01.2018, S. 894-903.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Simultaneous ply-order, ply-number and ply-drop optimization of laminate wind turbine blades using the inverse finite element method
AU - Albanesi, Alejandro
AU - Bre, Facundo
AU - Fachinotti, Victor
AU - Gebhardt, Cristian
PY - 2018/1/15
Y1 - 2018/1/15
N2 - This paper presents a novel methodology to simultaneously determine the optimal ply-order, ply-number and ply-drop configuration of laminate wind turbine blades using simulation-based optimization, considering the shape that the laminates are expected to attain after large elastic deformations. This methodology combines Genetic Algorithms with the Inverse Finite Element Method. As an actual engineering application, we redesigned the composite stacking layout of a medium-power 40-kW wind turbine blade to reduce its weight, subjected to mechanical and manufacturing constraints such as allowable tip deflection, maximum stress, natural frequencies, and maximum number of successive identical plies. Results demonstrate weight reductions of up to 15% compared to the initial layout, proving that the proposed methodology is a robust redesign tool capable of effectively determining the optimal composite stacking layout of laminate wind turbine blades.
AB - This paper presents a novel methodology to simultaneously determine the optimal ply-order, ply-number and ply-drop configuration of laminate wind turbine blades using simulation-based optimization, considering the shape that the laminates are expected to attain after large elastic deformations. This methodology combines Genetic Algorithms with the Inverse Finite Element Method. As an actual engineering application, we redesigned the composite stacking layout of a medium-power 40-kW wind turbine blade to reduce its weight, subjected to mechanical and manufacturing constraints such as allowable tip deflection, maximum stress, natural frequencies, and maximum number of successive identical plies. Results demonstrate weight reductions of up to 15% compared to the initial layout, proving that the proposed methodology is a robust redesign tool capable of effectively determining the optimal composite stacking layout of laminate wind turbine blades.
KW - Composite materials
KW - Inverse finite element
KW - Multilayered shells
KW - Optimization
KW - Wind turbine blade
UR - http://www.scopus.com/inward/record.url?scp=85032585436&partnerID=8YFLogxK
U2 - 10.1016/j.compstruct.2017.10.051
DO - 10.1016/j.compstruct.2017.10.051
M3 - Article
AN - SCOPUS:85032585436
VL - 184
SP - 894
EP - 903
JO - Composite Structures
JF - Composite Structures
SN - 0263-8223
ER -