...
首页> 外文期刊>Boundary-layer Meteorology >Dissipation Intermittency Increases Long-Distance Dispersal of Heavy Particles in the Canopy Sublayer
【24h】

Dissipation Intermittency Increases Long-Distance Dispersal of Heavy Particles in the Canopy Sublayer

机译:耗散间歇性增加了冠层亚层中重颗粒的远距离弥散

获取原文
获取原文并翻译 | 示例
           

摘要

The dispersion of heavy particles such as seeds within canopies is evaluated using Lagrangian stochastic trajectory models, laboratory, and field experiments. Inclusion of turbulent kinetic energy dissipation rate intermittency is shown to increase long-distance dispersal (LDD) by contributing to the intermittent ejection of particles to regions of high mean velocity outside the canopy volume. Model evaluation against controlled flume experiments, featuring a dense rod canopy, detailed flow measurements, and imaged trajectories of spherical particles, demonstrates that superimposing a terminal velocity on the fluid velocity is insufficient to determine the particle dispersal kernel. Modifying the trajectory model by adding dissipation intermittency is found to be significant for dispersal predictions along with the addition of inertial and crossing trajectories' effects. Comparison with manual seed-release experiments in a forest using wind-dispersed seeds shows that the model captures most of the measured kernels when accepted uncertainties in plant area index and friction velocity are considered. Unlike the flume experiments, the model modifications for several wind-dispersed seeds have minor effects on short-distance dispersal. A large increase was predicted in LDD when including dissipation intermittency for the forest experiment. The main results suggest that fitting or calibrating models to the 'main body' of measured kernels may not offer extrapolating foresight to LDD predictions. As inertial effects were found mostly negligible in the field conditions here, the extended trajectory model requires specifying only the seed's terminal velocity and a constant variance of the normalized dissipation rate. Therefore, the proposed modifications can be readily applied to classical trajectory models so as to improve LDD predictions.
机译:使用拉格朗日随机轨迹模型,实验室和田间实验评估重粒子(例如种子)在冠层中的分散。湍流动能耗散率的间歇性包括在内,可通过促使颗粒间歇性喷出到冠层体积之外的高平均速度区域而增加长距离扩散(LDD)。针对受控的水槽实验进行的模型评估具有密集的杆顶篷,详细的流量测量结果和球形颗粒的成像轨迹,表明在流体速度上叠加最终速度不足以确定颗粒的分散核。发现通过增加耗散间歇性来修改轨迹模型对于色散预测以及增加惯性和交叉轨迹的影响非常重要。与使用风分散种子的森林中手动种子释放实验的比较表明,当考虑到植物面积指数和摩擦速度的可接受不确定性时,该模型将捕获大多数测得的籽粒。与水槽实验不同,几种风散种子的模型修改对短距离散布的影响很小。当包括森林实验的耗散间歇性时,LDD预计会大大增加。主要结果表明,将模型拟合或校准到所测仁的“主体”可能无法提供对LDD预测的外推预测。由于在这里的田间条件下惯性效应几乎可以忽略不计,因此扩展的轨迹模型仅需要指定种子的最终速度和归一化耗散率的恒定方差。因此,所提出的修改可以容易地应用于经典轨迹模型,以改善LDD预测。

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