unsteady aerodynamic force
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Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 476
Author(s):  
Mingming Zhang ◽  
Shurong Hao ◽  
Anping Hou

In order to obtain the aerodynamic loads of the vibrating blades efficiently, the eXterme Gradient Boosting (XGBoost) algorithm in machine learning was adopted to establish a three-dimensional unsteady aerodynamic force reduction model. First, the database for the unsteady aerodynamic response during the blade vibration was acquired through the numerical simulation of flow field. Then the obtained data set was trained by the XGBoost algorithm to set up the intelligent model of unsteady aerodynamic force for the three-dimensional blade. Afterwards, the aerodynamic load could be gained at any spatial location during blade vibration. To evaluate and verify the reliability of the intelligent model for the blade aerodynamic load, the prediction results of the machine learning model were compared with the results of Computation Fluid Dynamics (CFD). The determination coefficient R2 and the Root Mean Square Error (RMSE) were introduced as the model evaluation indicators. The results show that the prediction results based on the machine learning model are in good agreement with the CFD results, and the calculation efficiency is significantly improved. The results also indicate that the aerodynamic intelligent model based on the machine learning method is worthy of further study in evaluating the blade vibration stability.


2018 ◽  
Vol 30 (1) ◽  
pp. 016107 ◽  
Author(s):  
L. L. Kang ◽  
L. Q. Liu ◽  
W. D. Su ◽  
J. Z. Wu

Author(s):  
Gangsik Yun ◽  
Dongho Oh ◽  
Youngjin Kim ◽  
JiHyeon Kim ◽  
TaeHyeong Kim

Unsteady aerodynamic forces generally have been treated as subjects to avoid or control. However, more energy resources could be gained if humans could use the unsteady aerodynamic force that can destroy massive structures. In this paper, an energy harvesting device was proposed using the flutter phenomenon, which is one of the phenomena of aerodynamic instability. Unlike existing flutter-based energy harvesting devices, the proposed device can be operated regardless of wind direction. A prototype was developed for a performance evaluation in a wind tunnel, and displacement measurements were taken over varying wind speeds.


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