LISIDD

Research laboratory in Industrial Safety Engineering and Sustainable Development

Fatigue strength prediction in composite materials of wind turbine blades under dry–wet conditions: An artificial neural network approach


Journal article


Khaled Ziane, Soraya Zebirate, Adel Zaitri
Wind Engineering, vol. 40, 2016 Jun, pp. 189--198


Cite

Cite

APA   Click to copy
Ziane, K., Zebirate, S., & Zaitri, A. (2016). Fatigue strength prediction in composite materials of wind turbine blades under dry–wet conditions: {An} artificial neural network approach. Wind Engineering, 40, 189–198. https://doi.org/10.1177/0309524X16641849


Chicago/Turabian   Click to copy
Ziane, Khaled, Soraya Zebirate, and Adel Zaitri. “Fatigue Strength Prediction in Composite Materials of Wind Turbine Blades under Dry–Wet Conditions: {An} Artificial Neural Network Approach.” Wind Engineering 40 (June 2016): 189–198.


MLA   Click to copy
Ziane, Khaled, et al. “Fatigue Strength Prediction in Composite Materials of Wind Turbine Blades under Dry–Wet Conditions: {An} Artificial Neural Network Approach.” Wind Engineering, vol. 40, June 2016, pp. 189–98, doi:10.1177/0309524X16641849.


BibTeX   Click to copy

@article{ziane2016a,
  title = {Fatigue strength prediction in composite materials of wind turbine blades under dry–wet conditions: {An} artificial neural network approach},
  year = {2016},
  month = jun,
  journal = {Wind Engineering},
  pages = {189--198},
  volume = {40},
  doi = {10.1177/0309524X16641849},
  author = {Ziane, Khaled and Zebirate, Soraya and Zaitri, Adel},
  month_numeric = {6}
}