Combining CFD and artificial neural network techniques to predict vortex-induced vibration mechanism for wind turbine tower hoisting

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. (C) 2022 Elsevier B.V. All rights reserved.

Automated summary

This study introduces a vortex-induced vibration suppression scheme for wind turbine tower hoisting process based on computational fluid dynamics, with the use of numerical analysis and a hybrid meta-model to predict simulation results, ultimately providing digital prediction methods for tower hoisting operation and maintenance.