RAPID: Collaborative Research: Deepwater Horizon: Simulating the three dimensional dispersal of aging oil with a Lagrangian approach

RAPID：合作研究：深水地平线：用拉格朗日方法模拟老化石油的三维扩散

• 批准号: 1048976
• 负责人: Edward Adams
• 金额: $ 2.49万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-15 至 2012-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1048976&HistoricalAwards=false
• 关键词: RAPID; Collaborative; Research; Deepwater; Horizon

Intellectual Merit: Simulation of the subsurface and surface dispersal of oil in the Gulf of Mexico will be conducted with the objective of producing probabilistic envelopes of the spread of different size classes of oil as they age over time. The proposed model system is ready to respond. The SABGOM hydrodynamic model of the Gulf of Mexico and South Atlantic Bight has been successfully coupled with LTRANS, a fully three-dimensional Lagrangian particle tracking model capable of simulating sub-grid scale turbulent motion as well as time-varying particle attributes like diameter, density, and rise/sinking velocities. At distances greater than a few hundred meters above the deepwater source (depending on ambient current speed and stratification), the dispersal of oil depends mainly on the behavior of oil droplets which are fractionated into different sizes. These oil droplets can have orders of magnitude differences in ascent rates (e.g., 6 mm/s and 0.06 mm/s for 300 micron and 30 micron diameter particles, respectively) and change in diameter as they age. Emulsification, interaction with suspended particulate matter, dissolution and other processes can also affect droplet behavior. Our Lagrangian approach is ideally suited for simulating oil dispersal because differences in initial droplet characteristics and time-varying droplet behavior are readily incorporated. In this project, the coupled SABGOM/LTRANS model system will be run for the time period of the Deepwater Horizon oil spill, maps and animations of model output will be produce. The model results will be compared with available observations and will be made available to the oil spill response community. In the near-term, a series of LTRANS simulations will be run using the existing flow field from recent SABGOM model simulations. The Lagrangian dispersion runs will be initialized with a continuous source of particles representing the near-field plume above the well. Each run will simulate the far-field dispersion of those particles based on a specific set of assumptions about particle behavior. As more complete information on the size and composition of gas bubbles and oil droplets emerge, the most realistic particle distributions from the LTRANS ensemble of runs will be selected. As part of this effort, an improved hindcast from the SABGOM model for use with LTRANS will be prodiced and the model skill will be quantified against physical oceanographic observations. In addition, Eulerian and Lagrangian predictions of oil dispersal will be quantitatively compared with observations in order to use the strengths of both approaches to provide the most realistic predictions for the oil response community. Broader Impacts: Mid-term results will be open-source models and model results using existing and likely new, particle-tracking technology for the geosciences and oil-spill response communities. Incorporation of the model into the framework of the Community Surface Dynamics Modeling System (CSDMS) will ensure that the coding structures are suitable for coupling with other models and future distribution for research and educational purposes. In addition, the team members from the USGS will ensure that LTRANS can run with CF-compliant model output, making it functional with over seventeen coastal models, allowing simulations and forecasts to be made throughout the US coastal waters. In addition to providing timely information for oil spill responders, this project will lay the ground work for future efforts that investigate the interaction between oil and larval transport of commercially and ecologically important organisms in the Gulf of Mexico.

智力优点：将对墨西哥湾石油的地下和表面扩散进行模拟，目的是产生不同大小类别的石油随着时间的推移而扩散的概率包络线。所提出的模型系统已准备好做出响应。墨西哥湾和南大西洋湾的 SABGOM 水动力模型已成功与 LTRANS 耦合，LTRANS 是一种全三维拉格朗日粒子跟踪模型，能够模拟亚网格尺度的湍流运动以及随时间变化的粒子属性，如直径、密度，以及上升/下降速度。在深水源上方数百米以上的距离（取决于环境水流速度和分层），石油的扩散主要取决于被分成不同尺寸的油滴的行为。这些油滴的上升速率可能存在数量级差异（例如，对于 300 微米和 30 微米直径的颗粒，分别为 6 毫米/秒和 0.06 毫米/秒），并且随着它们的老化，直径会发生变化。乳化、与悬浮颗粒物质的相互作用、溶解和其他过程也会影响液滴行为。我们的拉格朗日方法非常适合模拟油扩散，因为初始液滴特征和随时间变化的液滴行为的差异很容易被纳入。在该项目中，SABGOM/LTRANS 耦合模型系统将在深水地平线漏油事件期间运行，并生成模型输出的地图和动画。模型结果将与现有观测结果进行比较，并将提供给溢油应急部门。短期内，将使用最近 SABGOM 模型模拟中的现有流场运行一系列 LTRANS 模拟。拉格朗日分散运行将使用代表井上方近场羽流的连续粒子源来初始化。每次运行都将根据一组有关粒子行为的特定假设来模拟这些粒子的远场色散。随着有关气泡和油滴的尺寸和成分的更完整信息的出现，将从 LTRANS 运行集合中选择最真实的颗粒分布。作为这项工作的一部分，将生产出与 LTRANS 一起使用的 SABGOM 模型的改进后报，并且将根据物理海洋学观测来量化模型技能。此外，欧拉和拉格朗日对石油扩散的预测将与观测结果进行定量比较，以便利用这两种方法的优势为石油响应界提供最现实的预测。更广泛的影响：中期结果将是开源模型和使用现有的和可能的新粒子跟踪技术为地球科学和石油泄漏响应社区提供模型结果。将该模型纳入社区表面动力学建模系统（CSDMS）的框架将确保编码结构适合与其他模型耦合以及未来用于研究和教育目的的分发。此外，USGS 的团队成员将确保 LTRANS 能够以符合 CF 的模型输出运行，使其能够与超过 17 个沿海模型一起运行，从而能够在整个美国沿海水域进行模拟和预测。除了为漏油应急人员提供及时信息外，该项目还将为未来研究墨西哥湾石油与具有商业和生态重要性的生物幼体运输之间的相互作用奠定基础。