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Three-Dimensional flow Structure and the Fluvial Dynamics of Stream Confluences

Three-Dimensional flow Structure and the Fluvial Dynamics of Stream Confluences
三维水流结构与河道交汇处的河流动力学
批准号:
9710068
负责人:
Bruce Rhoads
金额:
$12.88万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1997
资助国家:
美国
项目状态:
已结题
起止时间:
1997-07-01 至 2002-01-31

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中文摘要
翻译
伊利诺伊大学厄巴纳-香槟分校这项研究的目的是研究汇流的三维结构、导致这种结构的机制以及三维流动与汇流形态之间的联系。具体目标是确定流体运动的三维模式和促成这种模式的因素,检查不同尺度之间的相互作用,并将连贯的三维流体运动与泥沙流动和侵蚀模式联系起来。这将通过使用Sontek声学多普勒测速仪来实现。从测量计划获得的数据将使用一种创新的稳健统计程序进行分析,该程序将从混合总体中提取样本数据,并将其划分为组成部分总体。研究结果将通过在伊利诺伊大学国家超级计算应用中心使用最先进的可视化软件开发汇流动力学的动态可视化模型来综合。
英文摘要
University of Illinois, Urbana-Champaign The objective of this investigation is to focus upon the three dimensional structure of flow at confluences, the mechanisms responsible for this structure, and the connection between three-dimensional flow and confluence morphology. Specific objectives are to identify 3-D patterns of fluid motion and factors that contribute to this, examine the interaction among various scales, and link coherent 3-D fluid motion to sediment flow and patterns of erosion. This will be accomplished through the use of a Sontek acoustic doppler velocimeter. Data obtained from the measurement program will be analyzed using an innovative robust statistical procedure that partitions sample data drawn from a mixed population into component populations. Results of the research will be synthesized by developing dynamic visualization models of confluence dynamics using state of the art visualization software at the National Center for Supercomputing Applications at the University of Illinois.
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会议论文
Collaborative Research: Mixing at Stream and River Confluences
Doctoral Dissertation Research: Influence of Riparian Vegetation on Near-Bank Flow Structure and Erosion Rates on a Large Alluvial River
Fluvial Dynamics of Cutoffs and Abandoned Channel Development on Meandering Rivers
Doctoral Dissertation Research: Investigation of Interactions Among Near-Bank Turbulence, Flow Structure, and Bank Retreat in a Compound Meander Loop
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis