Investigating Turbulence-Driven Sediment Transport with Field Applications of Particle Image Velocimetry

通过粒子图像测速的现场应用研究湍流驱动的沉积物输送

基本信息

  • 批准号:
    NE/V008099/1
  • 负责人:
  • 金额:
    $ 9.35万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2020
  • 资助国家:
    英国
  • 起止时间:
    2020 至 无数据
  • 项目状态:
    已结题

项目摘要

Our current capabilities for predicting amounts of sand moved by wind over beaches and in deserts perform poorly when tested in the natural environment. Accurate predictions are crucial, however, to many practical problems in resource management and environmental engineering, such as beach deflation, coastal dune and habitat development, soil erosion, and dust emissions into the atmosphere. The principal limitation of the current models is that they calculate transport rate only as a function of a single time-averaged wind speed. We know, however, that wind-blown sand - even over uniform beaches and desert surfaces - displays intricate and shifting spatial patterns, most visibly in the form of streamers or so-called 'sand-snakes'. Previous research has suggested that these patterns are formed by individual gusts, or eddies, of wind that generate and drive the streamers over the surface.The research project will determine the precise functional relationships between eddies in natural winds and resultant sand transport over the surface, with the goal of establishing a new quantitative and predictive model that explicitly incorporates parameters related to the turbulence.We do this by applying state-of-the-art video imaging technology in field experiments on a beach. The International Partner is deploying a laboratory-grade measurement system for tracking eddies in the wind as well as airborne sand grains through a powerful laser beam, filmed by multiple high-speed video cameras from different viewing angles. The PI will add to this his technique of filming streamers with ordinary GoPro sports cameras and analysing the footage to measure the movements and grain densities of these patterns as they approach and enter the laser beam. The combination of these two types of Particle Image Velocimetry on different spatial scales allows us to interrogate the precise links between wind turbulence and sand movement so that we can establish a mathematical model.
在自然环境中测试时,我们目前预测海滩和沙漠中风移动的沙子数量的能力表现很差。然而,对于资源管理和环境工程中的许多实际问题,如海滩收缩、海岸沙丘和栖息地发展、土壤侵蚀和粉尘排放到大气中,准确的预测是至关重要的。目前的模型的主要局限性是,它们计算的传输率只作为一个单一的时间平均风速的函数。然而,我们知道,风吹沙-即使在均匀的海滩和沙漠表面-显示复杂和变化的空间模式,最明显的形式是飘带或所谓的“沙蛇”。先前的研究表明,这些模式是由风的个别阵风或漩涡形成的,这些阵风或漩涡产生并驱动表面上的飘带。该研究项目将确定自然风中的漩涡与表面上的沙尘输送之间的精确函数关系,目标是建立一个新的定量和预测模型,明确纳入与湍流相关的参数。在海滩的野外实验中应用最先进的视频成像技术。国际合作伙伴正在部署一个实验室级的测量系统,通过强大的激光束跟踪风中的漩涡以及空中的沙粒,由多个高速摄像机从不同的视角拍摄。PI将添加他的技术,用普通的GoPro运动相机拍摄彩带,并分析镜头,以测量这些图案在接近和进入激光束时的运动和颗粒密度。在不同的空间尺度上结合这两种类型的粒子图像测速技术,使我们能够询问风湍流和沙运动之间的精确联系,以便我们可以建立一个数学模型。

项目成果

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Andreas Baas其他文献

Andreas Baas的其他文献

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{{ truncateString('Andreas Baas', 18)}}的其他基金

A cellular automaton model for investigating landscape development in vegetated aeolian environments.
用于研究植被风沙环境中景观发展的元胞自动机模型。
  • 批准号:
    NE/D521314/1
  • 财政年份:
    2006
  • 资助金额:
    $ 9.35万
  • 项目类别:
    Research Grant

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