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: Massachusetts Institute of Technology
• 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
• 起止时间: 2015-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1520825&HistoricalAwards=false
• 关键词: Hazards; SEES; Advanced; Lagrangian; Methods

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.

当有害物质通过空气和水的自然过程释放和扩散到环境中时，就会发生环境流动灾害。 最近的灾难性例子包括：深水地平线灾难期间的石油扩散，埃亚菲亚德拉冰盖火山灰云通过商业空域，以及福岛反应堆灾难的放射性废物痕迹。这些类型的危害很常见，许多危害对社会产生深远影响。当危险材料被释放时，准确预测材料可能流向何处可以大大改善应急响应，并显著减少负面后果。 做好准备和作出有效反应可以挽救许多人的生命，挽救无数的环境破坏和巨大的财政成本。然而，预测材料在复杂环境流动中的去向仍然是一个艰巨的科学挑战。该项目旨在通过利用和推进四维（3D+时间）拉格朗日方法的最新基本突破，改变科学的环境流动预测能力。这项研究将整合理论，计算和观测方法，开发和利用尖端的拉格朗日方法与数据驱动的建模，以揭示，量化和预测海洋和大气中区域流动灾害期间的关键传输过程和结构。该项目将（一）开发和改进四维（3D+时间）拉格朗日相干结构的数学方法，以阐明非定常拉格朗日流输运;（二）在历史数据集上测试和开发拉格朗日相干结构方法;（三）制作高效、准确、分布式和基于网络的软件，以支持拉格朗日相干结构分析和可视化;（iv）将LCS方法纳入数值模式和非高斯数据同化;（v）进行实地测试和概念验证、海洋-大气耦合实地实验;（vi）在项目期间应对机会风险。

项目成果

Search and rescue at sea aided by hidden flow structures

• 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

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.

Trajectory-free approximation of phase space structures using the trajectory divergence rate

• 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

Coordinated Unmanned Aircraft System (UAS) and Ground-Based Weather Measurements to Predict Lagrangian Coherent Structures (LCSs)

• 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

Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science during the LAPSE-RATE Campaign

• DOI: 10.3390/s19092179
• 发表时间: 2019-05-01
• 期刊: SENSORS
• 影响因子: 3.9
• 作者: Barbieri, Lindsay;Kral, Stephan T.;de Boer, Gijs
• 通讯作者: de Boer, Gijs