CSR-CSI: DDDAS-The Pervasive Dynamical Ecosystem for Oceanographic Research

CSR-CSI：DDDAS-海洋学研究的普遍动力生态系统

• 批准号: 0720836
• 负责人: Dimitris Metaxas
• 金额: $ 30万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0720836&HistoricalAwards=false
• 关键词: CSR; CSI; DDDAS; Pervasive; Dynamical

This proposal develops, deploys and evaluates a prototype pervasive dynamic oceanographic ecosystem that integrates sensors, networks, observatories, and computational algorithms to enable dynamic data driven application systems research (DDDAS) in oceanography and in particular the study of anoxia and hypoxia off the coast of New Jersey. The research findings are also incorporated in cross-disciplinary research curricula (across SOE, FAS and MCS) to provide students with the skills needed by the rapidly expanding network of research and applied observatories being constructed. New research methods in distributed resource allocation, distributed simulation environments, nonlinear dynamic system theory for swarming and computer vision learning methods are used to achieve the proposed goals. The result and impact of this DDDAS framework, is to integrate computational infrastructure that includes computers, networks, data archives, instruments, observatories, experiments, and embedded sensors and actuators, to address important national and global challenges such as(1) safe and efficient navigation and marine operations, (2) efficient oil and hazardous material spill trajectory prediction and clean up, (3) monitoring, predicting and mitigating coastal hazards, (4) military operations, (5) search and rescue, and (6) prediction of harmful algal blooms, hypoxic conditions, and other ecosystem or water quality phenomena.

该提案开发，部署和评估一个原型普遍的动态海洋生态系统，集成传感器，网络，观测站，和计算算法，使动态数据驱动的应用系统研究（DDDAS）在海洋学，特别是缺氧和缺氧的研究关闭新泽西海岸。研究结果也被纳入跨学科的研究课程（跨SOE，FAS和MCS），为学生提供所需的快速扩展的研究和应用观测站网络正在建设的技能。为了实现所提出的目标，采用了分布式资源分配、分布式仿真环境、非线性动态系统理论和计算机视觉学习方法。该DDDAS框架的结果和影响是整合包括计算机、网络、数据档案、仪器、观测站、实验以及嵌入式传感器和致动器在内的计算基础设施，以应对重要的国家和全球挑战，例如（1）安全有效的导航和海上作业，（2）有效的石油和危险物质泄漏轨迹预测和清理，（3）监测，预测和减轻沿海灾害，（4）军事行动，（5）搜索和救援，以及（6）预测有害藻华，缺氧条件和其他生态系统或水质现象。