Titlebook: Dynamic Data Driven Applications Systems; Third International Frederica Darema,Erik Blasch,Alex Aved Conference proceedings 2020 Springer

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Dynamic Data-Driven Application Systems for NASA’s Science Mission Directorateiniaturized science instruments makes possible domain-specific scientific investigations. When coupled with numerical prediction models, these types of spacecraft will enable new scientific investigations of phenomena that previously could not have been studied or would have been too expensive to study.

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Predictive Digital Twins: Where Dynamic Data-Driven Learning Meets Physics-Based Modelingortance is a tight feedback loop between models and data, which has long been a central concept in DDDAS. This keynote talk presents an approach to create, update, and deploy data-driven physics-based digital twins. We demonstrate the approach through the development of a structural digital twin for a custom-built unmanned aerial vehicle.

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Conference proceedings 2020Boston, MA, USA, in October 2020.. The 21 full papers and 14 short papers presented in this volume were carefully reviewed and selected from 40 submissions. They cover topics such as: digital twins; environment cognizant adaptive-planning systems; energy systems; materials systems; physics-based sys

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978-3-030-61724-0Springer Nature Switzerland AG 2020

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Dynamic Data Driven Applications Systems978-3-030-61725-7Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Bildungsstandards und Verstehenskompetenztool to underpin intelligent automation and drive key decisions. The formulations and methods of dynamic data-driven application systems (DDDAS) have a key role to play in the tasks of inference, assimilation, prediction, control, and planning that enable the digital twin paradigm. Of particular imp

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