物理
唤醒
偏移量(计算机科学)
机械
涡轮机
航空航天工程
动力学(音乐)
气象学
经典力学
声学
热力学
计算机科学
工程类
程序设计语言
作者
Renwei Ji,Jinhai Zheng,Mi-An Xue,Ke Sun,Yonglin Ye,Renqing Zhu,E. Fernandez-Rodriguez,Yuquan Zhang
摘要
The misalignment between flow and rotor can significantly alter the efficiency of the tidal stream turbine (TST), and therefore, it is vital to predict the flow in the tidal field and the performance of the TST under yaw-offset conditions. First, this paper implements a high-precision Lagrangian dynamic sub-grid-scale model based on the large-eddy simulation (LES) method. A classical computational fluid dynamics benchmark case is selected to validate the accuracy of the dynamic LES (DLES) method. The results indicate that the newly implemented dynamic LES method exhibits reduced dissipation and effectively captures the local effects of non-uniform flow fields, including vortex structures. Second, an efficient high-fidelity numerical method (AL-DLES) for forecasting the TST wake is presented by integrating an actuator line (AL) code with the aforementioned DLES method based on the Lagrangian framework. After comparing the experimental results, it was discovered that the newly developed AL-DLES coupling approach, which addresses the issues of challenging turbine meshing, rapid wake dissipation, and insufficient flow field fidelity in previous methods, can accurately simulate the forces acting on the TST while also capturing detailed characteristics of the flow field. Furthermore, the study will be extended to investigate the TST wake dynamics under various yaw-offset conditions, exploring the mechanisms of instability evolution in wake meandering. Meanwhile, the latest third-generation (Ωnew) vortex identification program is implemented and successfully applied to the wake vortex visualization of the TST under yaw-offset conditions. Through a comparative analysis of three distinct vortex identification approaches, it was demonstrated that the Ωnew method exhibits superior accuracy in capturing the vortex system located behind the rotor, eliminating the need for manual threshold selection. In addition, it is capable of simultaneously capturing both strong and weak vortices, which is a vital aspect for future wake research.
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