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Introduction to the Dynamic Data Driven Applications Systems (DDDAS) Paradigm

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Handbook of Dynamic Data Driven Applications Systems

Abstract

Dynamic Data Driven Applications Systems (DDDAS) is a paradigm for systems analysis and design, and a framework that dynamically couples high-dimensional physical and other analysis models and methods, run-time measurements, and computational architectures. Some of the foremost early applications of DDDAS successes range from environmental assessment of adverse weather and natural disasters such as tornadic activity, hurricane formation and trajectory, wildfire monitoring and volcanic plume detection and tracking, to real-time structural health monitoring in aerospace systems and electrical power grids operation, and to medical and societal applications. Monitoring, understanding and predicting behaviors of complex and dynamic systems with DDDAS principles has expanded over the years to demonstrate new and advanced capabilities in other applications that span space situational awareness, unmanned aerial vehicle (UAV) design and operation, and complex systems adaptive management and security applications. Recent efforts reflect the digital age of information management such as multimedia analysis, electrical power grid control, other civilian infrastructures, and biohealth concerns. Underlying DDDAS developments are advances in sensor design, signal processing and filtering, as well as computational architectures and communications. The book highlights for the reader DDDAS-based advances, with more information available in the DDDAS society’s website: www.1dddas.org.

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Notes

  1. 1.

    Darema coined the term DDDAS in 1999, but she conceived the key concepts of the paradigm itself in 1980, when she was working in large nuclear radiation transport modeling for oil exploration through nuclear accelerator neutron and gamma-ray measurements; between 1980 and through the 80’s, in organizational private communications Darema discussed about “DDDAS” ideas under the title “Gedanken Laboratory” and presented it in [3].

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Acknowledgements

Work presented in this book was supported in part by the DDDAS Program of the Air Force Office of Scientific Research (AFOSR) as well as other funding agencies. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Air Force Research Laboratory or the U.S. Government, or any other funding entities.

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Authors and Affiliations

  1. Air Force Office of Scientific Research, Arlington, VA, USA

    Erik P. Blasch

  2. InfoSymbiotics Systems Society, Boston, MA, USA

    Frederica Darema

  3. Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI, USA

    Dennis Bernstein

Authors
  1. Erik P. Blasch
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  2. Frederica Darema
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  3. Dennis Bernstein
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Correspondence to Erik P. Blasch .

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Editors and Affiliations

  1. Air Force Office of Scientific Research, Arlington, VA, USA

    Erik P. Blasch

  2. InfoSymbiotics Systems Society, Boston, MA, USA

    Frederica Darema

  3. Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

    Sai Ravela

  4. Air Force Research Lab, Rome, NY, USA

    Alex J. Aved

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Blasch, E.P., Darema, F., Bernstein, D. (2022). Introduction to the Dynamic Data Driven Applications Systems (DDDAS) Paradigm. In: Blasch, E.P., Darema, F., Ravela, S., Aved, A.J. (eds) Handbook of Dynamic Data Driven Applications Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-74568-4_1

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  • DOI: https://doi.org/10.1007/978-3-030-74568-4_1

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