Multi-Scale Computational Methods for Coastal Flooding

沿海洪水的多尺度计算方法

• 批准号: 1720288
• 负责人: Kyle Mandli
• 金额: $ 15万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1720288&HistoricalAwards=false
• 关键词: Multi; Scale; Computational; Methods; Coastal

Flooding along the nation's coastlines can lead to devastating consequences both to life and property as seen in Hurricanes Katrina and Sandy. Efforts to protect our coastlines from the most dangerous of these events is critical to our sustainable future along our nation's coastlines. The goal of this project is to provide a means for improving our ability to forecast and predict these events while taking into account key coastal infrastructure that are designed to protect at-risk populations. This work not only enables direct reduction of loss of life and economic impact via better forecasts however, it also enables the application of mathematics and computation that can start to ask and answer critical questions such as "I want to build a sea-wall, where should I put it and how high should it be?". The context of these questions is also critical, budgetary constraints and optimal protection are of course central to this effort and this projects aims to enable answering these questions as well.The project develops numerical methods that can answer questions related to climate change adaptation strategies addressing coastal flooding due to tsunamis and storm surge. Both types of events have in the past proven themselves to be immensely destructive and promise to be so in the future. Unfortunately with climate change these events could be made worse, whether due to rising sea-levels or changes to the likelihood of dangerous storms, it is critical to a sustainable existence along the coastlines of the world that we address the threat of coastal flooding. The work proposed focuses on developing numerical methods that include sub-grid-scale structures that help protect coastal communities with barriers such as sea-walls. The basis of the work will be the GeoClaw framework, a finite-volume, wave- propagation, and structured- grid code that has previously been validated for both tsunami and storm surge events. GeoClaw addresses some of the multi-scale nature of the coastal flooding problem by using adaptive mesh refinement (AMR) and local time stepping but struggles to resolve fine-scale structures without significant penalty due to the resolutions required. The work proposed focuses on representing barriers at the sub-grid-scale level without the need for fully resolving these structures. This will be accomplished by the development of a new Riemann solver that will be able to represent zero-width barriers at grid cell edges. This capability will then be used in conjunction with h-box and semi-Lagrangian methods allowing the barriers to have flexible parameterizations in terms of placement with respect to the grid. The method will then be tested on realistic cases and be incorporated into a larger optimization framework that is geared towards finding optimal adaptation solutions emphasizing the capabilities of the flexible specification of the barrier.

沿着国家海岸线的洪水可能会对生命和财产造成毁灭性的后果，就像卡特里娜飓风和桑迪飓风一样。 努力保护我们的海岸线免受这些事件中最危险的事件的影响，对我们国家海岸线的可持续未来沿着至关重要。 该项目的目标是提供一种手段，提高我们预测和预报这些事件的能力，同时考虑到旨在保护风险人口的关键沿海基础设施。 这项工作不仅可以通过更好的预测直接减少生命损失和经济影响，而且还可以应用数学和计算，开始提出和回答关键问题，例如“我想建一个海堤，我应该把它放在哪里，应该有多高？". 这些问题的背景也是至关重要的，预算限制和最佳保护当然是这项工作的核心，本项目旨在回答这些问题，以及该项目开发的数值方法，可以回答有关气候变化适应战略的问题，解决沿海洪水由于海啸和风暴潮。 这两种类型的事件在过去都证明了自己具有巨大的破坏性，并承诺在未来也会如此。不幸的是，随着气候变化，这些事件可能会变得更糟，无论是由于海平面上升还是危险风暴可能性的变化，我们应对沿海洪水的威胁对世界沿海沿着的可持续生存至关重要。 拟议的工作重点是制定数值方法，包括次网格规模的结构，有助于保护沿海社区的障碍，如海堤。 这项工作的基础将是GeoClaw框架，这是一个有限体积、波传播和结构化网格代码，以前已在海啸和风暴潮事件中得到验证。GeoClaw通过使用自适应网格细化（AMR）和本地时间步进来解决沿海洪水问题的一些多尺度性质，但由于所需的分辨率，很难解决精细尺度结构而不会造成重大损失。 建议的工作重点是在子网格尺度上代表障碍，而不需要完全解决这些结构。这将通过开发一个新的黎曼解算器来实现，该解算器将能够代表网格单元边缘的零宽度障碍。 这种能力，然后将被用于与h盒和半拉格朗日方法，使障碍有灵活的参数化方面的放置相对于网格。然后，该方法将在实际案例中进行测试，并纳入一个更大的优化框架，该框架旨在寻找最佳适应解决方案，强调屏障灵活规范的能力。

项目成果

A Novel Framework for Parametric Analysis of Coastal Transition Zone Modeling

沿海过渡区建模参数分析的新框架

• DOI: 10.1111/1752-1688.12983
• 发表时间: 2022
• 期刊: JAWRA Journal of the American Water Resources Association
• 作者: Chegini, Taher;de Almeida Coelho, Gustavo;Ratcliff, John;Ferreira, Celso M.;Mandli, Kyle;Burke, Patrick;Li, Hong‐Yi
• 通讯作者: Li, Hong‐Yi

An $h$-Box Method for Shallow Water Equations Including Barriers

包括障碍物的浅水方程的$h$盒法

• DOI: 10.1137/19m128363x
• 发表时间: 2021
• 期刊: SIAM Journal on Scientific Computing
• 影响因子: 3.1
• 作者: Li, Jiao;Mandli, Kyle T.
• 通讯作者: Mandli, Kyle T.

Numerical Considerations for Quantifying Air–Water Turbulence with Moment Field Equations

用矩场方程量化空气-水湍流的数值考虑

• DOI: 10.1007/s42286-021-00048-y
• 发表时间: 2021
• 期刊: Water Waves
• 作者: Conroy, Colton J.;Mandli, Kyle T.;Kubatko, Ethan J.
• 通讯作者: Kubatko, Ethan J.

Continental Scale Heterogeneous Channel Flow Routing Strategy for Operational Forecasting Models

业务预测模型的大陆尺度异质河道流量路由策略

• DOI: 10.1111/1752-1688.12847
• 发表时间: 2021
• 期刊: JAWRA Journal of the American Water Resources Association
• 作者: Meselhe, Ehab;Lamjiri, Maryam A.;Flint, Kelly;Matus, Sean;White, Eric D.;Mandli, Kyle
• 通讯作者: Mandli, Kyle