Workshop on Dynamic Data-Driven Applications Systems (DDDAS) - InfoSymbiotic Systems

动态数据驱动应用系统 (DDDAS) 研讨会 - InfoSymbiotic Systems

• 批准号: 1057753
• 负责人: Craig Douglas
• 金额: $ 4万
• 依托单位: University of Wyoming
• 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: 2010-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1057753&HistoricalAwards=false
• 关键词: Workshop; Dynamic; Data; Driven; Applications

Dynamic Data Driven Application Systems (DDDAS) entails the ability to dynamically incorporate additional data into an executing application, and, conversely, the ability of an application to dynamically steer the measurement process. In DDDAS, the term measurement has been used to connote instrumentation systems, networks of heterogeneous sensors, and embedded controllers. This synergistic and symbiotic feedback control-loop between applications and measurements is a high payoff, novel, and powerful technique for advancing modeling and simulation methods plus instrumentation and control methods, thus creating applications with new and enhanced capabilities. DDDAS creates the potential to transform the way science and engineering are done, to induce fundamental and major advances in the way processes are modeled, designed, implemented, analyzed and understood, and in the way many functions in our society are conducted in numerous broad arenas, e.g., manufacturing, commerce, transportation, hazard prediction/management, and medicine.The unprecedented availability of data from a variety of sensors deployed at great cost requires the development of methodologies for exploiting this data in modeling and simulation. From ice sheets to lake water quality and contaminant transport scientists are increasingly called upon to deliver predictions based on the optimal use of modeling and observation data ? methodologies and theory for such activities thus needs to be a very high priority for research investment. Recent developments in terms of data availability, methodologies for uncertainty quantification and data assimilation have made possible transformative new research. The workshop proposed here will bring together an eclectic group of academics, national laboratory personnel, and funding agency representatives to formulate objectives, priorities, and plans to enable the grand vision described above.

动态数据驱动的应用程序系统（DDDAS）需要动态地将其他数据纳入执行应用程序的能力，相反，应用程序可以动态操纵测量过程的能力。在DDDA中，术语测量已用于表示仪器系统，异质传感器网络和嵌入式控制器。在应用和测量之间，这种协同和共生的反馈控制环是一种高收益，新颖而有力的技术，用于推进建模和仿真方法以及仪器和控制方法，从而创建了具有新和增强功能的应用程序。 DDDA创造了改变科学和工程的方式，引起基本和重大进步的方式，并在过程的建模，设计，实施，分析和理解的方式上以及我们社会中的许多功能都在许多广泛的领域中进行，例如制造，商务，运输，危险/管理的范围，具有较大的范围。开发用于在建模和仿真中利用此数据的方法。从冰盖到湖水质量，越来越多地要求基于建模和观察数据的最佳使用来提供预测？因此，这些活动的方法和理论必须是研究投资的很高优先事项。在数据可用性，不确定性量化方法和数据同化的方法方面的最新发展使新研究成为可能。这里提出的研讨会将汇集一个折衷的学者，国家实验室人员和资助机构代表，以制定目标，优先事项和计划，以实现上述宏大的远见。