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- Title
Fatigue strength prediction in composite materials of wind turbine blades under dry–wet conditions: An artificial neural network approach.
- Authors
Ziane, Khaled; Zebirate, Soraya; Zaitri, Adel
- Abstract
In this article, the fatigue strength in composite materials of wind turbine blades under dry-wet conditions is predicted using artificial neural networks. Compression-compression constant amplitude fatigue tests were performed on thermoset polymer resins including polyesters and vinyl esters. Coupons were tested under an air temperature of 20°C and 50°C in both "dry" and "wet" conditions. The results show that artificial neural network can provide accurate fatigue strength prediction for different resin matrices under different values of temperature.
- Subjects
FATIGUE life; COMPOSITE materials; WIND turbines; ARTIFICIAL neural networks; THERMOSETTING polymers; MATHEMATICAL models
- Publication
Wind Engineering, 2016, Vol 40, Issue 3, p189
- ISSN
0309-524X
- Publication type
Article
- DOI
10.1177/0309524X16641849