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Transforming Systems Engineering Through Integrating Modeling and Simulation and the Digital Thread

Abstract

This chapter introduces the Digital Engineering Framework for Integration and Interoperability (DEFII) as a methodological foundation for the use of ontologies and graph data structures in a digital engineering context. DEFII leverages enabling technologies to support modeling and simulation in different engineering disciplines and provides an approach for integrating analysis models and simulations results into a coherent digital thread that crosses disciplines at different levels of abstraction. The chapter presents a simple catapult use case and a python-based implementation of the methodology to provide further details of how the methodology can work in a domain-specific example.

Leads

Daniel Dunbar

Stevens Institute of Technology

Tom Hagedorn

Stevens Institute of Technology

Timothy D. West

Stevens Institute of Technology

Brian Chell

Stevens Institute of Technology

John Dzielski

Stevens Institute of Technology

Mark R. Blackburn

Stevens Institute of Technology

Publications

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  8. Bone, M., Blackburn, M., Kruse, B. et al. (2018). Toward an interoperability and integration framework to enable digital thread. System 6 (4): 46. https://doi.org/10.3390/systems6040046.

  9. Bone, M.A., Blackburn, M.R., Rhodes, D.H. et al. (2019). Transforming systems engineering through digital engineering. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 16 (4): 339–355. https://doi.org/10.1177/1548512917751873.

  10. Cilli, M. V. (2015). Improving defense acquisition outcomes using an integrated systems engineering decision management (ISEDM) approach [PhD Thesis]. In ProQuest Dissertations and Theses.Doctoral dissertation. Stevens Institute of Technology. http://ezproxy.stevens.edu/login?url=https://www.proquest.com/dissertations-theses/improving-defense-acquisition-outcomes-using/docview/1776469856/se-2?accountid=14052.

  11. Cilli, M., Parnell, G.S., Cloutier, R., and Zigh, T. (2015). A systems engineering perspective on the revised defense acquisition system. Systems Engineering 18 (6): 584–603. https://doi.org/10.1002/sys.21329.

  12. Cotter, M., Hadjimichael, M., Markina-Khusid, A., and York, B. (2022). Automated detection of architecture patterns in MBSE models. In: Recent Trends and Advances in Model Based Systems Engineering (ed. A.M. Madni, B. Boehm, D. Erwin, et al.), 81–90. Springer International Publishing https://doi.org/10.1007/978-3-030-82083-1_8.

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  14. Dunbar, D., Hagedorn, T., Blackburn, M., and Verma, D. (2022). Use of semantic web technologies to enable system level verification in multi-disciplinary models. In: Advances in Transdisciplinary Engineering (ed. B.R. Moser, P. Koomsap, and J. Stjepandić). IOS Press https://doi.org/10.3233/ATDE220632.

  15. Dunbar, D., Blackburn, M., Hagedorn, T., and Verma, D. (2023). Graph representation of system of analysis in determining well-formed construction. 2023 Conference on Systems Engineering Research (CSER) (16–17 March 2023). Hoboken, NJ: Stevens Institute of Technology.

  16. Dunbar, D., Hagedorn, T., Blackburn, M. et al. (2023). Driving digital engineering integration and interoperability through semantic integration of models with ontologies. Systems Engineering 21662. https://doi.org/10.1002/sys.21662.

  17. Hennig, C., Viehl, A., Kämpgen, B., and Eisenmann, H. (2016). Ontology-based design of space systems. In: The Semantic Web – ISWC 2016, vol. 9982 (ed. P. Groth, E. Simperl, A. Gray, et al.), 308–324. Springer International Publishing https://doi.org/10.1007/978-3-319-46547-0_29.

  18. Medvedev, D., Shani, U., and Dori, D. (2021). Gaining insights into conceptual models: a graph-theoretic querying approach. Applied Sciences 11 (2): 765. https://doi.org/10.3390/app11020765.

  19. Mordecai, Y., Fairbanks, J.P., and Crawley, E.F. (2021). Category-theoretic formulation of the model-based systems architecting cognitive-computational cycle. Applied Sciences 11 (4): 1945. https://doi.org/10.3390/app11041945.

  20. Noy, N.F., Crubezy, M., Fergerson, R.W. et al. (2003). Protégé-2000: an open-source ontology-development and knowledge-acquisition environment. AMIA Annual Symposium Proceedings 2003: 953.

  21. Ruttenberg, A. (2020). Basic Formal Ontology (BFO). https://basic-formal-ontology.org (accessed June 11, 2023).

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The Systems Engineering Research Center (SERC) was established in the Fall of 2008 as a government-designated University Affiliated Research Center (UARC). The SERC has produced 15 years of research, focused on an updated systems engineering toolkit (methods, tools, and practices) for the complex cyber-physical systems of today and tomorrow.


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