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ITR/NGS: Collaborative Research: DDDAS: Data Dynamic Simulation for Disaster Management

ITR/NGS: Collaborative Research: DDDAS: Data Dynamic Simulation for Disaster Management
ITR/NGS:合作研究:DDDAS:灾害管理数据动态模拟
批准号:
0325314
负责人:
Jan Mandel
金额:
$62.1万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-09-15 至 2008-08-31

项目摘要

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中文摘要
翻译
janice L. Coen, Craig C. Douglas, Leopoldo P. Franca, Robert Kremens,Jan Mandel, Anatolii Puhalskii, Anthony Vodacek和赵维该项目将为灾害建模和管理开发先进的信息技术工具、数学模型和原型基础设施。该项目将在灾害指挥中心实时为需要的地方提供全面的信息和数值预测。该系统将整合来自数据流的大量信息,例如地图、传感器、测量和天气数据,数学模型将在远程超级计算机上运行。该模型将由动态可用数据控制,结果将在分布式设备中可视化,如通过无线以太网和宽带卫星链路连接到互联网的笔记本电脑和掌上电脑。其他传感器和机载成像仪也将无线联网。设想的建模系统的核心将是该地区周围的荒地和天气的现有计算机模型,这些模型将使用现代软件工程方法作为数据驱动的应用程序从零开始重写,并通过新的数学建模技术和先进的统计技术进行增强,以管理不确定性。高性能中间件将用于将计算节点、传感器节点、测量节点和可视化节点连接到分布式信息和建模系统中。新的网络软件技术将使节点之间的通信安全,并提供服务质量的保证。系统将被设计为能够容忍通信中断、延迟增加和节点消失。
英文摘要
ITR: Collaborative Research: DDDAS:Data Dynamic Simulation for Disaster ManagementJanice L. Coen, Craig C. Douglas, Leopoldo P. Franca, Robert Kremens,Jan Mandel, Anatolii Puhalskii, Anthony Vodacek, and Wei ZhaoThis project will develop advanced Information Technology tools, mathematical models, and prototype infrastructure for disaster modeling and management. The project will bring comprehensive information and numerical prediction where it is needed, at the disaster command center, in real time.The system will incorporate large volume of information from data streams, e.g., as maps, sensor, surveyance, and weather data, and the mathematical model will run on remote supercomputers. The model will be controlled by dynamically available data, and the results visualized in distributed devices, like laptops and palmtops connected to the Internet by wireless ethernet and a broadband satellite link. Other sensors and airborne imagers will also be networked wirelessly. The core of the envisioned modeling system will be an existing computer model of wildland and weather around the area, adn these models will be rewritten from scratch using modern software engineering methodology as a data driven application, and enhanced by new mathematicalmodeling techniques together with advanced statisticaltechniques will be used to manage uncertainty. High-performance middleware will be used toconnect computational nodes, sensor nodes, surveyance nodes, and visualization nodes into adistributed information and modeling system. New network software technologies will makethe communication between the nodes secure and provide quality of service guarantees. Thesystem will be designed to tolerate interruptions of communication, increased latencies, and nodedisappearances.
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