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Structure estimation of vertical axis wind turbine using artificial neural network
Alexandria Engineering Journal ( IF 6.8 ) Pub Date : 2021-06-08 , DOI: 10.1016/j.aej.2021.05.002
S. Teksin , N. Azginoglu , S.O. Akansu

Vertical axis wind turbines (VAWTS) can be a suitable choice for usage in urban areas. Wind conditions and structural parameters are critical to power production. In this study, some variations of a darrieus vawt was attempted via wind tunnel testing. A modified naca4412 blade profile was selected for this investigation. The influence of aspect ratios, angle of attack, chord length, etc. were investigated experimentally. After taken more than 800 data artificial neural network (ANN) was applied to estimate the other range of scales using different algorithms that are utilized the aforementioned experimental parameters. This study focuses on the design criteria and application of VAWTS inbuilt real environments without testing. The results have been promising and will provide ease of design for similar designs. Moreover, this work will contribute to environmental cleanup and a more livable world by increasing renewable energy resources.



中文翻译:

基于人工神经网络的垂直轴风力机结构估计

垂直轴风力涡轮机 (VAWTS) 是在城市地区使用的合适选择。风力条件和结构参数对电力生产至关重要。在这项研究中,通过风洞测试尝试了 darrieus vawt 的一些变化。本次调查选择了修改后的 naca4412 叶片轮廓。通过实验研究了纵横比、攻角、弦长等的影响。在采用了 800 多个数据之后,人工神经网络 (ANN) 被应用于使用利用上述实验参数的不同算法来估计其他范围的尺度。本研究侧重于 VAWTS 内置真实环境的设计标准和应用,无需测试。结果很有希望,并将为类似的设计提供设计便利。而且,

更新日期:2021-07-30
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