globalchange  > 全球变化的国际研究计划
项目编号: 1659923
项目名称:
Predictive Models for Wave Damping by Flexible Aquatic Vegetation
作者: Heidi Nepf
承担单位: Massachusetts Institute of Technology
批准年: 2017
开始日期: 2017-02-15
结束日期: 2020-01-31
资助金额: 440751
资助来源: US-NSF
项目类别: Standard Grant
国家: US
语种: 英语
特色学科分类: Geosciences - Earth Sciences
英文关键词: vegetation ; wave ; model ; wave motion ; wave energy ; flexible vegetation ; plant ; wave energy dissipation ; aquatic vegetation ; vegetation restoration ; predictive model ; wave amplitude ; project ; combined wave-current condition ; fluid-flexible-structure interaction ; wave-field parameter ; reconfigured flexible plant ; flexible surface ; vegetation drag ; new model ; model blade ; paddle wavemaker ; meadow
英文摘要: Aquatic vegetation provides many natural benefits, including the protection of shorelines from storms and erosion, the provision of habitat, and the improvement of water quality. Waves can kick up sediment from the bed causing erosion, making the water cloudy and adding pollutants to the water. Vegetation reduces wave motion and keeps sediment from being kicked up. However, this benefit of vegetation cannot be incorporated into lake and coastal management plans, because there is no accurate method for predicting the reduction of wave motion by vegetation. This project will develop a model for predicting the reduction of wave energy from vegetation based on the characteristic of the vegetation, including geometry, size and flexibility. With this new model, engineers and watershed managers will be able to assess different scenarios of vegetation restoration for their potential to protect shorelines and to reduce erosion events that drive poor water quality.

This laboratory study explores the interaction between flexible vegetation and waves to develop predictive models for the impact of vegetation on wave energy dissipation. Flexible vegetation bends in response to flow, and this reconfiguration alters the vegetation drag. The impact of reconfiguration can be described in terms of an effective plant length, le, which is the length of rigid plant that imparts the same hydrodynamic drag as the reconfigured flexible plant. In a preliminary study, the PI?s lab developed scaling laws for individual plants with simple strap morphology (fresh and saltwater eelgrass) that predict the drag in current and in waves. This new study will extend the scaling laws to communities of plants (meadows), to conditions with combined currents and waves, and to plants of more complex morphology (e.g. Elodea and Potamogeton). Specifically, this study will develop models to predict le from plant geometric and biomechanical properties, and current and wave-field parameters, and will demonstrate how the effective length can be used to predict the wave energy dissipation over a meadow in waves and in combined wave-current conditions. The experiments will be carried out in a 24m-long and 60cm-deep water channel with a paddle wavemaker. Initially, model blades will be constructed from low (LDPE) and high (HDPE) density polyethylene. Later experiments will consider more complex morphologies using both live plants and 3-D printed models. The motion of individual blades will be captured with digital imaging, and the forces on individual blades in isolation and within a meadow will be measured with a submersible force transducer. The velocity field will be measured with acoustic Doppler velocimetry and PIV. The dissipation of wave energy will be estimated from the longitudinal decay of wave amplitude, which will be measured using resistance-type water surface gages. This project will contribute fundamental understanding to fluid-flexible-structure interaction, which is relevant to many engineering topics, e.g. passive energy-harvesting devices and flow-control with flexible surfaces. Relevant to earth systems, this project will develop a unified model for predicting wave dissipation due to plants of different morphology and across the range of relevant field conditions.
资源类型: 项目
标识符: http://119.78.100.158/handle/2HF3EXSE/90537
Appears in Collections:全球变化的国际研究计划
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Heidi Nepf. Predictive Models for Wave Damping by Flexible Aquatic Vegetation. 2017-01-01.
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