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Model-Based Systems Engineering for Systems Simulation

  • Renan Leroux
  • Marc PantelEmail author
  • Ileana Ober
  • Jean-Michel Bruel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11246)

Abstract

Model-Based Systems Engineering and early simulation based Validation & Verification are now key enablers for managing the complexity in the development of modern complex systems like Cyber-Physical Systems. Models provide a formal account of system requirements and design decisions. Model simulation enables both design exploration and design versus requirements correctness assessment. Model simulation activities rely on Simulation Systems (i.e. systems that execute the model simulation). System execution environment models play a key role during these activities. Appropriate models must be developed for each kind of analysis conducted during Validation & Verification. More and more often, complex Systems Engineering is conducted in Extended Enterprises and the simulation activities are performed using partial models that must be completed with mock-up models for missing parts of the system. The development of Simulation Systems is thus costly and error prone and would benefit from the same Systems Engineering principles that are applied to the product. We propose a methodology for a seamless integration of the Simulation Systems development in the Products Systems Engineering. This method imports the available elements from the models of the system and its environment, from the Systems Engineering for Product space to a dedicated Systems Engineering for Simulation space. The required mock-up models are then defined in the Systems Engineering for Simulation space. As a result, we target a better management and reuse of the various environment and mock-up models in the various simulation activities during the development of the same product. This proposal is independent both of the actual methods and tools used to model the system and of the simulation environment.

Notes

Acknowledgements

The authors would like to thank the MOISE project members for their contributions as well as the IRT-SE and the French Commissariat Général à l’Investissements and the Agence Nationale de la Recherche for their financial support in the frame of the Programme d’Investissement d’Avenir.

References

  1. 1.
    Leroux, R., Ober, I., Pantel, M., Bruel, J.-M.: Modeling co-simulation: a first experiment. In: Proceedings of MODELS-2017, Satellite Event: Workshops, September 2017. http://ceur-ws.org/Vol-2019/gemoc_3.pdf
  2. 2.
    Sirin, G., Paredis, C., Yannou, B., Coatanéa, E., Landel, E.: A model identity card to support simulation model development process in a collaborative multidisciplinary design environment. IEEE Syst. J. 9(4), 1–12 (2015)CrossRefGoogle Scholar
  3. 3.
    Capasso, C., Hammadi, M., Patalano, S., Renaud, R., Veneri, O.: A multi-domain modelling and verification procedure within MBSE approach to design propulsion systems for road electric vehicles. In: Mechanics & Industry, vol. 18, p. 107. AFM, EDP Sciences 2016, January 2017. www.mechanics-industry.org
  4. 4.
    Fiorese, S.: Découvrir et comprendre l’Ingénierie Système. AFIS - Cepaduès, March 2012Google Scholar
  5. 5.
    BKCASE, SEBoK: guide to the engineering body of knowledge. http://sebokwiki.org/wiki/Guide_to_the_Systems_Engineering_Body_of_Knowledge_(SEBoK)
  6. 6.
    Topper, J.S., Horner, N.C.: Model-based systems engineering in support of complex systems development. Johns Hopkins APL Tech. Digest 32(1), 419–432 (2013)Google Scholar
  7. 7.
    Shephard, M.S., Beall, M.W., O’Bara, R.M., Webster, B.E.: Toward simulation-based design. Finite Elem. Anal. Des. 40(12), 1575–1598 (2004).  https://doi.org/10.1016/j.finel.2003.11.004CrossRefGoogle Scholar
  8. 8.
    Graignic, P., Vosgien, T., Jankovic, M., Tuloup, V., Berquet, J., Troussier, N.: Complex system simulation: proposition of a MBSE framework for design-analysis integration. Procedia Comput. Sci. 16, 59–68 (2013)CrossRefGoogle Scholar
  9. 9.
    INCOSE, Systems Engineering Handbook, A Guide for System Life Cycle Processes and Activities, 4th edn. Wiley, New York (2015). https://sepnobrasil.yolasite.com/resources/INCOSESystemsEngineeringHandbook4e2015.pdf
  10. 10.
    Retho, F., Smaoui, H., Vannier, J.-C., Dessante, P.: Model of intention: a concept to support models building in a complex system design project. In: ERTS, pp. 115–126 (2014)Google Scholar
  11. 11.
    Retho, F., Smaoui, H., Vannier, J.-C., Dessante, P.: A model-based method to support complex system design via systems interactions analysis. In: Proceedings of the Posters Workshop at CSD&M (2013)Google Scholar
  12. 12.
    Sirin, G., Retho, F., Yannou, B., Callot, M., Dessante, P., Landel, E.: Multidisciplinary simulation model development: early inconsistency detection during the design stage. In: Advances in Engineering Software (2017). https://hal.archives-ouvertes.fr/hal-01673538
  13. 13.
    FMI: Functional Mockup Interface. http://fmi-standard.org/
  14. 14.
    Galtier, V., Vialle, S., Dad, C., Tavella, J.-P., Lam-Yee-Mui, J.-P., Plessis, G.: FMI-based distributed multi-simulation with DACCOSIM. In: Proceedings of the Symposium on Theory of Modeling and Simulation: DEVS Integrative Symposium, ser. DEVS 2015, San Diego, CA, USA: Society for Computer Simulation International 2015, pp. 39–46 (2015). http://dl.acm.org/citation.cfm?id=2872965.2872971
  15. 15.
    Neema, H., et al.: Model-based integration platform for FMI co-simulation and heterogeneous simulations of cyber-physical systems. In: Proceedings of the 10th International Modelica Conference, 10–12 March 2014, Lund, Sweden, vol. 96. Linköping University Electronic Press; Linköpings universitet, pp. 235–245 (2014)Google Scholar
  16. 16.
    Dahmann, J.S., Fujimoto, R.M., Weatherly, R.M.: The department of defense high level architecture. In: Winter Simulation Conference (1997)Google Scholar
  17. 17.
    Dahmann, J.S., Fujimoto, R.M., Weatherly, R.M.: The DoDHigh Level Architecture: an update. In: Winter Simulation Conference (1998)Google Scholar
  18. 18.
    DACCOSIM: Distributed architecture for controlled co-simulation. https://sourcesup.renater.fr/daccosim/index.html
  19. 19.
    The Modelica Association: Modelica. https://www.modelica.org/
  20. 20.
    Bossa, B., Boulbene, B., Dubé, S., Pantel, M.: Towards a co-simulation based model assessment process for system architecture. In: Proceedings of the 2nd Workshop on the Formal CoSimulation of Cyber Physical Systems, Satellite Event of the Software Engineering and Formal Methods Conference (2018)Google Scholar
  21. 21.
    Voirin, J.-L.: Model-Based System and Architecture Engineering with the Arcadia Method. ISTE Press - Elsevier, London (2017)CrossRefGoogle Scholar
  22. 22.
    CESAM-Community, CESAM: Cesames systems architecting method, January 2017. http://cesam.community/wp-content/uploads/2017/09/CESAM-guide_-_V12092017.pdf

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Renan Leroux
    • 1
    • 2
    • 3
  • Marc Pantel
    • 1
    • 2
    Email author
  • Ileana Ober
    • 1
    • 2
  • Jean-Michel Bruel
    • 1
    • 2
  1. 1.Institute Technology (IRT) Antoine de Saint-ExupéryToulouseFrance
  2. 2.University of Toulouse/Institute for Research in Informatics of ToulouseToulouseFrance
  3. 3.ALTRANToulouseFrance

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