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Hazards SEES: Advanced Lagrangian Methods for Prediction, Mitigation and Response to Environmental Flow Hazards

Hazards SEES: Advanced Lagrangian Methods for Prediction, Mitigation and Response to Environmental Flow Hazards
Hazards SEES:用于预测、缓解和响应环境流动危害的先进拉格朗日方法
批准号:
1520825
负责人:
Thomas Peacock
金额:
$281.1万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-01 至 2021-08-31

项目摘要

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中文摘要
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英文摘要
Environmental flow disasters occur when hazardous material is released and dispersed into the environment by the natural processes of air and water. Recent catastrophic examples include: the spread of oil during the Deep Water Horizon disaster, the passage of the ash cloud from the Eyjafjallajokull volcano through commercial air space, and the trail of radioactive waste from the Fukushima reactor disaster. These types of hazards are common and many have profound impacts on society. When hazardous material is released, accurate predictions of where the material is likely to go can greatly improve emergency response and significantly reduce negative consequences. Preparedness and effective response can save many lives, untold environmental damage and enormous financial cost. However, predicting where materials go in complex environmental flows remains a formidable scientific challenge.This project intends to transform science's environmental flow predictive capabilities by exploiting and advancing recent fundamental breakthroughs in four-dimensional (3D+time) Lagrangian methods. This research will integrate theoretical, computational, and observational approaches to develop and utilize cutting-edge Lagrangian methods with data driven modeling for the purpose of uncovering, quantifying and predicting key transport processes and structures during regional flow-based hazards in the ocean and atmosphere. This project will (i) exploit and advance mathematical methods for four-dimensional (3D+time) Lagrangian Coherent Structures (LCS) in order to elucidate unsteady Lagrangian flow transport; (ii) test and develop LCS methods on historical data sets; (iii) produce efficient, accurate, distributed and web-based software to support LCS analysis and visualization; (iv) integrate LCS methodology into numerical models and non-Gaussian data assimilation; (v) perform field testing and a proof-of-concept, coupled ocean-atmosphere field experiment; and (vi) respond to a hazard of opportunity during the tenure of the project.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1038/s41467-020-16281-x
发表时间: 2019-09
期刊: Nature Communications
影响因子: 16.6
作者: [M. Serra;Pratik Sathe;I. Rypina;A. Kirincich;S. Ross;Pierre FJ Lermusiaux;Arthur Allen;T. Peacock;G. Haller]
通讯作者: M. Serra;Pratik Sathe;I. Rypina;A. Kirincich;S. Ross;Pierre FJ Lermusiaux;Arthur Allen;T. Peacock;G. Haller
Finite-time Lyapunov exponents in the instantaneous limit and material transport
瞬时极限和材料传输中的有限时间 Lyapunov 指数
DOI: 10.1007/s11071-020-05713-4
发表时间: 2020
期刊: Nonlinear Dynamics
影响因子: 5.6
作者: [Nolan, Peter J., Serra, Mattia, Ross, Shane D.]
通讯作者: Ross, Shane D.
DOI: 10.1007/s11071-019-04814-z
发表时间: 2017-05
期刊: Nonlinear Dynamics
影响因子: 5.6
作者: [Gary K. Nave;Peter J. Nolan;S. Ross]
通讯作者: Gary K. Nave;Peter J. Nolan;S. Ross
DOI: 10.3390/s18124448
发表时间: 2018-12-01
期刊: SENSORS
影响因子: 3.9
作者: [Nolan, Peter J., Pinto, James, Schmale, David G., III]
通讯作者: Schmale, David G., III
9
    Collaborative Research: Advancing turbidity currents: moving sources, polydispersity and aggregation
    The vertical propagation of internal waves through the ocean
    Workshop: Uncovering Transport Barriers in Geophysical Flows; Banff International Research Station (BIRS), Banff, Alberta; 22 to 27 September 2013
    DynSyst_Special_Topics/Collaborative Research: A New Braid Theoretic Approach To Uncovering Transport Barriers In Complex Flows
    海外基金