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

• 批准号: NE/V008099/1
• 负责人: Andreas Baas
• 金额: $ 9.35万
• 依托单位: King's College London
• 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
• 来源: https://gtr.ukri.org/projects?ref=NE%2FV008099%2F1
• 关键词: Investigating; Turbulence; Driven; Sediment; Transport

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.

我们目前预测风吹过海滩和沙漠的沙量的能力在自然环境中测试时表现不佳。然而，对于资源管理和环境工程中的许多实际问题，如海滩通货紧缩、沿海沙丘和生境开发、土壤侵蚀和向大气排放粉尘，准确的预测是至关重要的。当前模型的主要局限性是它们只计算作为单个时间平均风速的函数的传输率。然而，我们知道，被风吹来的沙子--甚至在均匀的海滩和沙漠表面--表现出错综复杂和不断变化的空间模式，最明显的形式是飘带或所谓的“沙蛇”。以前的研究表明，这些模式是由风的个别阵风或涡流形成的，这些阵风或涡流在表面产生和驱动拖带。该研究项目将确定自然风中的涡流和由此产生的沙粒在表面上传输之间的精确函数关系，目标是建立一个新的量化和预测模型，明确纳入与湍流相关的参数。我们通过在海滩上进行现场实验应用最先进的视频成像技术来实现这一点。国际合作伙伴正在部署一种实验室级的测量系统，通过强大的激光光束跟踪风中的涡流以及空气中的沙粒，由多个高速摄像机从不同的视角拍摄。PI将在此基础上增加他的技术，即用普通的GoPro运动相机拍摄流光，并分析镜头，以测量这些图案在接近和进入激光光束时的运动和颗粒密度。这两种类型的粒子图像测速技术在不同的空间尺度上结合在一起，使我们能够探索风、湍流和沙粒运动之间的精确联系，从而建立数学模型。