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Combining CFD and artificial neural network techniques to predict vortex-induced vibration mechanism for wind turbine tower hoisting
Communications in Nonlinear Science and Numerical Simulation ( IF 3.9 ) Pub Date : 2022-06-27 , DOI: 10.1016/j.cnsns.2022.106688
Yiming Chen, Xin Jin, Peng Cheng, Huali Han, Yang Li

In this study, we consider a vortex-induced vibration suppression scheme for wind turbine tower hoisting process based on computational fluid dynamics. We propose a triangular cross-section spiral flow-disturbing device designed to suppress vibration, and we performed a three-dimensional numerical analysis on the steady-state and transient vibration responses of a simulated wind turbine tower. Considering the large amount of calculations and considerable time consumption of CFD simulation, we propose a hybrid meta-model to predict the results of a CFD simulation. The prediction results show that the accuracy of the prediction model met structural engineering design requirements, and the calculation time was effectively reduced. Thus, we establish a set of digital prediction methods for tower hoisting operation and maintenance.



中文翻译:

结合CFD和人工神经网络技术预测风机塔架吊装涡激振动机理

在这项研究中,我们考虑了一种基于计算流体动力学的风力涡轮机塔架吊装过程的涡激振动抑制方案。我们提出了一种用于抑制振动的三角形截面螺旋扰流装置,并对模拟的风力涡轮机塔架的稳态和瞬态振动响应进行了三维数值分析。考虑到 CFD 模拟的大量计算和大量时间消耗,我们提出了一种混合元模型来预测 CFD 模拟的结果。预测结果表明,预测模型的准确性满足结构工程设计要求,有效减少了计算时间。因此,我们建立了一套塔吊运维的数字预测方法。

更新日期:2022-06-27
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