A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation

Bo Qin; Wei Ren

doi:doi:10.11648/j.si.20251303.12

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A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation

Bo Qin, Wei Ren^*

Published in Science Innovation (Volume 13, Issue 3)

Received: 17 April 2025 Accepted: 3 June 2025 Published: 11 June 2025

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Abstract

This paper presents a comprehensive full-stack systems engineering framework designed to enhance the adaptability, scalability, and interoperability of complex systems across various domains, including defense, transportation, and industrial automation. The proposed framework is organized into five interconnected layers: the Task Layer, which defines mission objectives and stakeholder needs; the System Architecture Layer, which captures high-level system behavior and structural decomposition; the Subsystem Layer, responsible for modeling domain-specific subsystems; the Component Layer, which encapsulates functional elements and their interactions; and the Hardware and Software Interface Layer, which manages the integration of physical components with software control logic. A key feature of this framework is its ability to enable seamless transitions from high-level requirements to detailed component specifications, ensuring traceability and coherence throughout the development lifecycle. The integration of standardized interfaces, such as the Functional Mock-up Interface (FMI), enables plug-and-play subsystem integration, promoting modularity and reusability. The framework leverages SysML for architecture modeling, discrete event simulation for subsystem behavior analysis, and a co-simulation environment for synchronized software-hardware interaction. This holistic approach supports robust system verification, validation, and iterative optimization in both design and operational phases. By enabling multi-level abstraction, cross-domain integration, and simulation-based evaluation, this structured framework provides a scalable and flexible platform for addressing the growing complexity of modern systems. It serves as a valuable asset for engineers, architects, and decision-makers seeking to accelerate development cycles, reduce integration risk, and enhance overall system performance.

Published in	Science Innovation (Volume 13, Issue 3)
DOI	10.11648/j.si.20251303.12
Page(s)	26-32
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2025. Published by Science Publishing Group

Keywords

System Engineering, SoS, Simulation System, Framework

References

[1]	Gorod, A., Sauser, B., & Boardman, J. (2008). System-of-systems engineering management: A review of modern history and a path forward. IEEE Systems Journal, 2(4), 484-499.
[2]	Hirshorn, S. R., Voss, L. D., & Bromley, L. K. (2017). NASA systems engineering handbook (No. HQ-E-DAA-TN38707).
[3]	Kossiakoff, A., Sweet, W. N., Seymour, S. J., & Biemer, S. M. (2011). Systems engineering principles and practice (Vol. 83). John Wiley & Sons.
[4]	Nielsen, C. B., Larsen, P. G., Fitzgerald, J., Woodcock, J., & Peleska, J. (2015). Systems of systems engineering: basic concepts, model-based techniques, and research directions. ACM Computing Surveys (CSUR), 48(2), 1-41.
[5]	Dunbar, D., Hagedorn, T., Blackburn, M., Dzielski, J., Hespelt, S., Kruse, B.,... & Yu, Z. (2023). Driving digital engineering integration and interoperability through semantic integration of models with ontologies. Systems Engineering, 26(4), 365-378.
[6]	Icenhour, C., Keniley, S., DeChant, C., Permann, C., Lindsay, A., Martineau, R.,... & Shannon, S. (2018). Multi-physics object oriented simulation environment (moose) (No. INL/CON-18-51061-Rev000). Idaho National Lab.(INL), Idaho Falls, ID (United States).
[7]	Taivalsaari, A., Mikkonen, T., Pautasso, C., & Systä, K. (2021, May). Full stack is not what it used to be. In International conference on web engineering (pp. 363-371). Cham: Springer International Publishing.
[8]	Blanchard, B. S. (2004). System engineering management. John Wiley & Sons.
[9]	Rainey, L. B., & Tolk, A. (2015). Modeling and Simulation Support for System of Systems Engineering Applications.
[10]	Gregory, J., & Salado, A. (2024, July). Towards a Systems Engineering Ontology Stack. In INCOSE International Symposium (Vol. 34, No. 1, pp. 1304-1318).
[11]	Riva, M., Zanutta, A., Genoni, M., Scalera, M. A., & Balestra, A. (2024, August). MBSE or no MBSE: is MBSE the final answer to system engineering?. In Modeling, Systems Engineering, and Project Management for Astronomy XI (Vol. 13099, pp. 115-120). SPIE.
[12]	Sinha, R., Paredis, C. J., Liang, V. C., & Khosla, P. K. (2001). Modeling and simulation methods for design of engineering systems. J. Comput. Inf. Sci. Eng., 1(1), 84-91.
[13]	DoD, D. I. (2008). 5000.02: Operation of the defense acquisition system. US Department of Defense, Washington, DC.
[14]	Hart, L. E. (2015, July). Introduction to model-based system engineering (MBSE) and SysML. In Delaware Valley INCOSE Chapter Meeting (Vol. 30). Mount Laurel, New Jersey: Ramblewood Country Club.
[15]	Babulak, E., & Wang, M. (2010). Discrete event simulation. Aitor Goti (Hg.): Discrete Event Simulations. Rijeka, Kroatien: Sciyo, 1.
[16]	Bullock, D., Johnson, B., Wells, R. B., Kyte, M., & Li, Z. (2004). Hardware-in-the-loop simulation. Transportation Research Part C: Emerging Technologies, 12(1), 73-89.
[17]	Broman, D., Brooks, C., Greenberg, L., Lee, E. A., Masin, M., Tripakis, S., & Wetter, M. (2013, September). Determinate composition of FMUs for co-simulation. In 2013 Proceedings of the International Conference on Embedded Software (EMSOFT) (pp. 1-12). IEEE.
[18]	Kannapinn, M., Schäfer, M., & Weeger, O. (2024). TwinLab: a framework for data-efficient training of non-intrusive reduced-order models for digital twins. Engineering Computations.
[19]	Hällqvist, R., Munjulury, R. C., Braun, R., Eek, M., & Krus, P. (2022). Realizing interoperability between mbse domains in aircraft system development. Electronics, 11(18), 2901.
[20]	Shanks, G. (2003). Real-time Platform Reference Federation Object Model (RPR FOM) Version 2.0 D17. Simulation Interoperability Standards Organization.
[21]	Singh, M., Fuenmayor, E., Hinchy, E. P., Qiao, Y., Murray, N., & Devine, D. (2021). Digital twin: Origin to future. Applied System Innovation, 4(2), 36.
[22]	Sabzian, H., Shafia, M. A., Bonyadi Naeini, A., Jandaghi, G., & Sheikh, M. J. (2018). A review of agent-based modeling (ABM) concepts and some of its main applications in management science. Interdisciplinary Journal of Management Studies (Formerly known as Iranian Journal of Management Studies), 11(4), 659-692.
[23]	Taylor, S. J., Kiss, T., Anagnostou, A., Terstyanszky, G., Kacsuk, P., Costes, J., & Fantini, N. (2018). The CloudSME simulation platform and its applications: A generic multi-cloud platform for developing and executing commercial cloud-based simulations. Future Generation Computer Systems, 88, 524-539.

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APA Style

Qin, B., Ren, W. (2025). A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation. Science Innovation, 13(3), 26-32. https://doi.org/10.11648/j.si.20251303.12

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ACS Style

Qin, B.; Ren, W. A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation. Sci. Innov. 2025, 13(3), 26-32. doi: 10.11648/j.si.20251303.12

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AMA Style

Qin B, Ren W. A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation. Sci Innov. 2025;13(3):26-32. doi: 10.11648/j.si.20251303.12

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@article{10.11648/j.si.20251303.12,
  author = {Bo Qin and Wei Ren},
  title = {A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation
},
  journal = {Science Innovation},
  volume = {13},
  number = {3},
  pages = {26-32},
  doi = {10.11648/j.si.20251303.12},
  url = {https://doi.org/10.11648/j.si.20251303.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20251303.12},
  abstract = {This paper presents a comprehensive full-stack systems engineering framework designed to enhance the adaptability, scalability, and interoperability of complex systems across various domains, including defense, transportation, and industrial automation. The proposed framework is organized into five interconnected layers: the Task Layer, which defines mission objectives and stakeholder needs; the System Architecture Layer, which captures high-level system behavior and structural decomposition; the Subsystem Layer, responsible for modeling domain-specific subsystems; the Component Layer, which encapsulates functional elements and their interactions; and the Hardware and Software Interface Layer, which manages the integration of physical components with software control logic. A key feature of this framework is its ability to enable seamless transitions from high-level requirements to detailed component specifications, ensuring traceability and coherence throughout the development lifecycle. The integration of standardized interfaces, such as the Functional Mock-up Interface (FMI), enables plug-and-play subsystem integration, promoting modularity and reusability. The framework leverages SysML for architecture modeling, discrete event simulation for subsystem behavior analysis, and a co-simulation environment for synchronized software-hardware interaction. This holistic approach supports robust system verification, validation, and iterative optimization in both design and operational phases. By enabling multi-level abstraction, cross-domain integration, and simulation-based evaluation, this structured framework provides a scalable and flexible platform for addressing the growing complexity of modern systems. It serves as a valuable asset for engineers, architects, and decision-makers seeking to accelerate development cycles, reduce integration risk, and enhance overall system performance.
},
 year = {2025}
}

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TY  - JOUR
T1  - A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation

AU  - Bo Qin
AU  - Wei Ren
Y1  - 2025/06/11
PY  - 2025
N1  - https://doi.org/10.11648/j.si.20251303.12
DO  - 10.11648/j.si.20251303.12
T2  - Science Innovation
JF  - Science Innovation
JO  - Science Innovation
SP  - 26
EP  - 32
PB  - Science Publishing Group
SN  - 2328-787X
UR  - https://doi.org/10.11648/j.si.20251303.12
AB  - This paper presents a comprehensive full-stack systems engineering framework designed to enhance the adaptability, scalability, and interoperability of complex systems across various domains, including defense, transportation, and industrial automation. The proposed framework is organized into five interconnected layers: the Task Layer, which defines mission objectives and stakeholder needs; the System Architecture Layer, which captures high-level system behavior and structural decomposition; the Subsystem Layer, responsible for modeling domain-specific subsystems; the Component Layer, which encapsulates functional elements and their interactions; and the Hardware and Software Interface Layer, which manages the integration of physical components with software control logic. A key feature of this framework is its ability to enable seamless transitions from high-level requirements to detailed component specifications, ensuring traceability and coherence throughout the development lifecycle. The integration of standardized interfaces, such as the Functional Mock-up Interface (FMI), enables plug-and-play subsystem integration, promoting modularity and reusability. The framework leverages SysML for architecture modeling, discrete event simulation for subsystem behavior analysis, and a co-simulation environment for synchronized software-hardware interaction. This holistic approach supports robust system verification, validation, and iterative optimization in both design and operational phases. By enabling multi-level abstraction, cross-domain integration, and simulation-based evaluation, this structured framework provides a scalable and flexible platform for addressing the growing complexity of modern systems. It serves as a valuable asset for engineers, architects, and decision-makers seeking to accelerate development cycles, reduce integration risk, and enhance overall system performance.

VL  - 13
IS  - 3
ER  -

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Author Information

Bo Qin

China Academy Electronics and Information Technology, China Electronics Technology Group Corporation, Beijing, China
Wei Ren

China Academy Electronics and Information Technology, China Electronics Technology Group Corporation, Beijing, China

Contact Email

http://orcid.org/0000-0003-2910-2150

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Plain Text BibTeX RIS

APA Style

Qin, B., Ren, W. (2025). A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation. Science Innovation, 13(3), 26-32. https://doi.org/10.11648/j.si.20251303.12

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ACS Style

Qin, B.; Ren, W. A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation. Sci. Innov. 2025, 13(3), 26-32. doi: 10.11648/j.si.20251303.12

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AMA Style

Qin B, Ren W. A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation. Sci Innov. 2025;13(3):26-32. doi: 10.11648/j.si.20251303.12

Copy | Download

@article{10.11648/j.si.20251303.12,
  author = {Bo Qin and Wei Ren},
  title = {A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation
},
  journal = {Science Innovation},
  volume = {13},
  number = {3},
  pages = {26-32},
  doi = {10.11648/j.si.20251303.12},
  url = {https://doi.org/10.11648/j.si.20251303.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20251303.12},
  abstract = {This paper presents a comprehensive full-stack systems engineering framework designed to enhance the adaptability, scalability, and interoperability of complex systems across various domains, including defense, transportation, and industrial automation. The proposed framework is organized into five interconnected layers: the Task Layer, which defines mission objectives and stakeholder needs; the System Architecture Layer, which captures high-level system behavior and structural decomposition; the Subsystem Layer, responsible for modeling domain-specific subsystems; the Component Layer, which encapsulates functional elements and their interactions; and the Hardware and Software Interface Layer, which manages the integration of physical components with software control logic. A key feature of this framework is its ability to enable seamless transitions from high-level requirements to detailed component specifications, ensuring traceability and coherence throughout the development lifecycle. The integration of standardized interfaces, such as the Functional Mock-up Interface (FMI), enables plug-and-play subsystem integration, promoting modularity and reusability. The framework leverages SysML for architecture modeling, discrete event simulation for subsystem behavior analysis, and a co-simulation environment for synchronized software-hardware interaction. This holistic approach supports robust system verification, validation, and iterative optimization in both design and operational phases. By enabling multi-level abstraction, cross-domain integration, and simulation-based evaluation, this structured framework provides a scalable and flexible platform for addressing the growing complexity of modern systems. It serves as a valuable asset for engineers, architects, and decision-makers seeking to accelerate development cycles, reduce integration risk, and enhance overall system performance.
},
 year = {2025}
}

Copy | Download

TY  - JOUR
T1  - A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation

AU  - Bo Qin
AU  - Wei Ren
Y1  - 2025/06/11
PY  - 2025
N1  - https://doi.org/10.11648/j.si.20251303.12
DO  - 10.11648/j.si.20251303.12
T2  - Science Innovation
JF  - Science Innovation
JO  - Science Innovation
SP  - 26
EP  - 32
PB  - Science Publishing Group
SN  - 2328-787X
UR  - https://doi.org/10.11648/j.si.20251303.12
AB  - This paper presents a comprehensive full-stack systems engineering framework designed to enhance the adaptability, scalability, and interoperability of complex systems across various domains, including defense, transportation, and industrial automation. The proposed framework is organized into five interconnected layers: the Task Layer, which defines mission objectives and stakeholder needs; the System Architecture Layer, which captures high-level system behavior and structural decomposition; the Subsystem Layer, responsible for modeling domain-specific subsystems; the Component Layer, which encapsulates functional elements and their interactions; and the Hardware and Software Interface Layer, which manages the integration of physical components with software control logic. A key feature of this framework is its ability to enable seamless transitions from high-level requirements to detailed component specifications, ensuring traceability and coherence throughout the development lifecycle. The integration of standardized interfaces, such as the Functional Mock-up Interface (FMI), enables plug-and-play subsystem integration, promoting modularity and reusability. The framework leverages SysML for architecture modeling, discrete event simulation for subsystem behavior analysis, and a co-simulation environment for synchronized software-hardware interaction. This holistic approach supports robust system verification, validation, and iterative optimization in both design and operational phases. By enabling multi-level abstraction, cross-domain integration, and simulation-based evaluation, this structured framework provides a scalable and flexible platform for addressing the growing complexity of modern systems. It serves as a valuable asset for engineers, architects, and decision-makers seeking to accelerate development cycles, reduce integration risk, and enhance overall system performance.

VL  - 13
IS  - 3
ER  -

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