...
首页> 外文期刊>Philosophical transactions of the Royal Society. Mathematical, physical, and engineering sciences >Towards reduced order modelling for predicting the dynamics of coherent vorticity structures within wind turbine wakes
【24h】

Towards reduced order modelling for predicting the dynamics of coherent vorticity structures within wind turbine wakes

机译:朝着减少秩序建模,以预测风力涡轮机唤醒相干涡度结构的动态

获取原文
获取原文并翻译 | 示例

摘要

The dynamics of the velocity field resulting from the interaction between the atmospheric boundary layer and a wind turbine array can affect significantly the performance of a wind power plant and the durability of wind turbines. In this work, dynamics in wind turbine wakes and instabilities of helicoidal tip vortices are detected and characterized through modal decomposition techniques. The dataset under examination consists of snapshots of the velocity field obtained from large-eddy simulations (LES) of an isolated wind turbine, for which aerodynamic forcing exerted by the turbine blades on the atmospheric boundary layer is mimicked through the actuator line model. Particular attention is paid to the interaction between the downstream evolution of the helicoidal tip vortices and the alternate vortex shedding from the turbine tower. The LES dataset is interrogated through different modal decomposition techniques, such as proper orthogonal decomposition and dynamic mode decomposition. The dominant wake dynamics are selected for the formulation of a reduced order model, which consists in a linear time-marching algorithm where temporal evolution of flow dynamics is obtained from the previous temporal realization multiplied by a time-invariant operator.
机译:由大气边界层和风力涡轮机阵列之间的相互作用产生的速度场的动态可以显着影响风力发电厂的性能和风力涡轮机的耐用性。在这项工作中,通过模态分解技术检测和特征,检测到风力涡轮机唤醒和螺旋涡流的稳定性的动力学。正在检查的数据集包括从孤立的风力涡轮机的大涡流模拟(LES)获得的速度场的快照,其通过致动器线模型模仿涡轮层施加的涡轮机叶片的空气动力学强制。特别注意螺旋末端涡旋的下游演化与涡轮机塔的交替涡流之间的相互作用。通过不同的模态分解技术询问LES数据集,例如适当的正交分解和动态模式分解。选择主导的唤醒动力学用于制定减少的订单模型,这由线性时间行进算法组成,其中从前一个时间实现乘以时间不变的运算符来获得流动动态的时间演变。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号