MAS-DT

基本信息

批准号：
NE/Z503381/1
负责人：
Justin Buck
金额：
$ 84.9万
依托单位：
NATIONAL OCEANOGRAPHY CENTRE
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2024
资助国家：
英国
起止时间：
2024 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FZ503381%2F1
关键词：
MAS DT

项目摘要

The National Oceanography Centre (NOC) operates ocean gliders for the Met Office and Royal Navy to collect earth observations, driving ocean forecast models. These models, in turn, underpin operational weather forecasts. Currently, observations are targeted at ocean model grid boxes in high-impact areas of UK waters. An extension of this approach is to optimise ocean glider observations to maximise their impact on ocean models and, thus, weather forecasts using the concept of an interoperable Digital Twin (DT) building on recent IMFe recommendations. We propose a demonstrator digital twin which combines earth observations with sub-surface ocean glider data and operational ocean model. The resulting novel four-dimensional picture will be presented through a User interface (UI), allowing scientists to identify the potential observations which could have the most impact, and allowing the definition of operational objectives to be achieved those observations. The objectives will feed a mission planning service that will take account of glider capabilities (such as battery life and speed) to re-task the glider, thus optimising the observations for most impact, creating a virtuous feedback circle between the observing capability and the ocean model data assimilation. This feedback between scientists, earth observation data, and glider operations in near real-time will maximise the value of the observations collected and their impact on ocean forecasting. This in turn will maximise the societal value of these publicly funded ocean observations. While this project will assemble and demonstrate the digital twin around Met Office operations, this DT will be a generic framework that will support plug-and-play interoperability of different models and autonomy engines to drive observations to optimise models. It is envisaged the applicability of the results will scale to the piloting operations for marine autonomous systems spanning a wide range of vehicle operations including the NERC research community. The work will build on, and directly contribute to further development of the Information Management Framework for environmental digital twins (IMFe), focusing on the interfaces between existing components via a communities of practice approach with best practices being included in community outputs (such as the Turing way and the TWINE community). This will enable the reuse of project outputs by the broader digital twin community. The project also aims to sustain the NERC Digital Twins senior stakeholder forum under the umbrella of the TWINE grouping of projects.

国家海洋学中心 (NOC) 为英国气象局和皇家海军运营海洋滑翔机来收集地球观测数据，驱动海洋预报模型。这些模型反过来又支撑了天气预报的运行。目前，观测针对的是英国水域高影响区域的海洋模型网格箱。这种方法的延伸是优化海洋滑翔机观测，以最大限度地提高其对海洋模型的影响，从而利用基于国际货币基金组织最近建议的可互操作数字孪生 (DT) 概念进行天气预报。我们提出了一个演示数字孪生，它将地球观测与地下海洋滑翔机数据和操作海洋模型相结合。由此产生的新颖的四维图片将通过用户界面（UI）呈现，使科学家能够识别可能产生最大影响的潜在观察结果，并允许定义实现这些观察结果的操作目标。这些目标将提供给任务规划服务，该服务将考虑滑翔机的能力（例如电池寿命和速度）来重新分配滑翔机的任务，从而优化观测以获得最大的影响，在观测能力和海洋之间创建良性反馈循环模型数据同化。科学家、地球观测数据和滑翔机操作之间的这种近乎实时的反馈将最大限度地提高所收集观测数据的价值及其对海洋预报的影响。这反过来又将使这些公共资助的海洋观测的社会价值最大化。虽然该项目将围绕气象局运营组装和演示数字孪生，但该 DT 将是一个通用框架，将支持不同模型和自主引擎的即插即用互操作性，以驱动观测以优化模型。预计该结果的适用性将扩展到海洋自主系统的试点操作，涵盖广泛的车辆操作，包括 NERC 研究界。这项工作将建立在环境数字孪生信息管理框架 (IMFe) 的基础上，并直接促进其进一步发展，通过实践社区方法重点关注现有组件之间的接口，并将最佳实践纳入社区产出（例如图灵路和 TWINE 社区）。这将使更广泛的数字孪生社区能够重复使用项目输出。该项目还旨在在 TWINE 项目分组的保护下维持 NERC 数字孪生高级利益相关者论坛。