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CMG: Collaborative Research: Adaptive Numerical Methods for Shallow Water Circulation with Applications to Hurricane Storm Surge Modeling

CMG: Collaborative Research: Adaptive Numerical Methods for Shallow Water Circulation with Applications to Hurricane Storm Surge Modeling
CMG:合作研究:浅水循环自适应数值方法及其在飓风风暴潮建模中的应用
批准号:
0620697
负责人:
Clinton Dawson
金额:
$22.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-09-01 至 2010-08-31

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中文摘要
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英文摘要
The objectives of this project are to improve the accuracy and robustness of storm-surge simulation through improved mathematical modeling, the development of dynamically adaptive numerical algorithms capable of resolving energetic flow features on different scales, increased computational resolution and improved physical description of coastal regions, and through efficient use of parallel computation. The project is inherently interdisciplinary, involving aspects of mathematical modeling, numerical analysis, computational science, coastal engineering, geomorphology, and marine science. The research team will develop improved physical models of storm surges including coupling of circulation, sediment and contaminant transport, and wave models defined on highly resolved computational domains. Adaptive computational methods for solving these models numerically will be formulated and analyzed. The results of this investigation will include an efficient simulator based on these improved physical models and adaptive algorithms, designed for large-scale parallel computation. The simulator will be verified numerically and validated on relevant benchmarks based on laboratory and field data. The synthesis of these ideas will lead to a fully operational hurricane storm-surge model for the Gulf Coast and eastern seaboard of the U.S., capable of predicting storm surges as storms approach landfall and studying the aftermath of storms.As recent events such as Hurricanes Katrina, Rita, and Wilma have demonstrated, the ability to predict and study the effects of hurricane storm surges is a problem of critical national interest. Hurricane Katrina alone is the costliest and fifth-deadliest hurricane in U.S. history; yet with better forecasting, design, and preparation, much of the devastation and loss of life caused by this storm could have been avoided. Hurricane storm-surge models can be used to predict flooding as storms approach landfall for the purposes of emergency management, and can be used in the design and implementation of improved protection systems, including levees, wetlands, seawalls, and flood gates. Computer models of storm surges have been developed; however, only within the past few years has the computational power and resolution been available to begin to model these events with any reasonable degree of certainty. In this project, the investigators will develop mathematical models and state-of-the-art computational algorithms and technologies for simulating storm surges due to hurricanes and other tropical events. The project will involve collaboration among mathematicians, coastal engineers, and marine scientists. The research effort will enhance the training of future scientists and engineers, and the developed methodology will impact other problems in coastal engineering and marine science, including water quality, shipping and ports, marine ecology, naval operations, weather and climate, and wetland degradation.
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Collaborative Research: Advancing the Data-to-Distribution Pipeline for Scalable Data-Consistent Inversion to Quantify Uncertainties in Coastal Hazards
  • 批准号:
    2208461
  • 项目类别:
    Standard Grant
  • 资助金额:
    $17.46万
  • 财政年份:
    2022
  • 负责人:
    Clinton Dawson
  • 依托单位:
PREEVENTS Track 2: Collaborative Research: A Dynamic Unified Framework for Hurricane Storm Surge Analysis and Prediction Spanning across the Coastal Floodplain and Ocean
  • 批准号:
    1854986
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $35.94万
  • 财政年份:
    2019
  • 负责人:
    Clinton Dawson
  • 依托单位:
Collaborative Research: Construction and Analysis of Numerical Methods for Stochastic Inverse Problems with Application to Coastal Hydrodynamics
  • 批准号:
    1818847
  • 项目类别:
    Standard Grant
  • 资助金额:
    $10.0万
  • 财政年份:
    2018
  • 负责人:
    Clinton Dawson
  • 依托单位:
Collaborative Research: Numerical and Probabilistic Modeling of Aboveground Storage Tanks Subjected to Multi-Hazard Storm Events
  • 批准号:
    1635115
  • 项目类别:
    Standard Grant
  • 资助金额:
    $24.0万
  • 财政年份:
    2016
  • 负责人:
    Clinton Dawson
  • 依托单位:
海外基金