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Towards an Extensible Model-Based Digital Twin Framework for Space Launch Vehicles

Ran Wei, Ruizhe Yang, Shijun Liu, Chongsheng Fan, Rong Zhou, Zekun Wu, Haochi Wang, Yifan Cai, Zhe Jiang

TL;DR

This work clarifies Digital Twin definitions and proposes a structured maturity framework to guide DT development for aerospace systems. It introduces DEVOTION, a model-based methodology grounded in MBSE/MDE, and DTME, a toolchain built around the Structured Digital Twin Metamodel (SDTM) to automate DT construction and evolution. Through a space launch vehicle E/E systems case study, the authors demonstrate stepwise progression from a descriptive digital model to a connected, cognitively capable DT, including traceability to heterogeneous models, automated data flows (P2D/D2P/D2D), simulations, 3D visualisation, and probabilistic model checking. The framework emphasizes extensibility, interoperability, and automation, aiming to deliver a scalable DT platform that supports reliability analysis and decision-making across the lifecycle of complex space systems.

Abstract

The concept of Digital Twin (DT) is increasingly applied to systems on different levels of abstraction across domains, to support monitoring, analysis, diagnosis, decision making and automated control. Whilst the interest in applying DT is growing, the definition of DT is unclear, neither is there a clear pathway to develop DT to fully realise its capacities. In this paper, we revise the concept of DT and its categorisation. We propose a DT maturity matrix, based on which we propose a model-based DT development methodology. We also discuss how model-based tools can be used to support the methodology and present our own supporting tool. We report our preliminary findings with a discussion on a case study, in which we use our proposed methodology and our supporting tool to develop an extensible DT platform for the assurance of Electrical and Electronics systems of space launch vehicles.

Towards an Extensible Model-Based Digital Twin Framework for Space Launch Vehicles

TL;DR

This work clarifies Digital Twin definitions and proposes a structured maturity framework to guide DT development for aerospace systems. It introduces DEVOTION, a model-based methodology grounded in MBSE/MDE, and DTME, a toolchain built around the Structured Digital Twin Metamodel (SDTM) to automate DT construction and evolution. Through a space launch vehicle E/E systems case study, the authors demonstrate stepwise progression from a descriptive digital model to a connected, cognitively capable DT, including traceability to heterogeneous models, automated data flows (P2D/D2P/D2D), simulations, 3D visualisation, and probabilistic model checking. The framework emphasizes extensibility, interoperability, and automation, aiming to deliver a scalable DT platform that supports reliability analysis and decision-making across the lifecycle of complex space systems.

Abstract

The concept of Digital Twin (DT) is increasingly applied to systems on different levels of abstraction across domains, to support monitoring, analysis, diagnosis, decision making and automated control. Whilst the interest in applying DT is growing, the definition of DT is unclear, neither is there a clear pathway to develop DT to fully realise its capacities. In this paper, we revise the concept of DT and its categorisation. We propose a DT maturity matrix, based on which we propose a model-based DT development methodology. We also discuss how model-based tools can be used to support the methodology and present our own supporting tool. We report our preliminary findings with a discussion on a case study, in which we use our proposed methodology and our supporting tool to develop an extensible DT platform for the assurance of Electrical and Electronics systems of space launch vehicles.
Paper Structure (46 sections, 18 figures, 1 table)

This paper contains 46 sections, 18 figures, 1 table.

Table of Contents

  1. Introduction
  2. Background and Motivation
  3. Digital Twin
  4. Model Based Systems Engineering (MBSE)
  5. MBSE and Digital Twin
  6. Digital Twin Maturity Matrix
  7. Definition of Digital Twin
  8. Challenges in Developing Digital Twin Systems
  9. Discussion
  10. Proposed Approach
  11. Model Driven Engineering
  12. Approach Discussion
  13. Tool Support
  14. Key Aspects
  15. Domain Specific Language Development
  16. ...and 31 more sections

Figures (18)

  • Figure 1: The evolution of Digital Models into Digital Twins (Adapted from kritzinger2018digital).
  • Figure 2: Stages and key models and processes for the DEVOTION methodology.
  • Figure 3: Architecture of the Digital Twin Management Environment (DTME).
  • Figure 4: The Base package of the Structured Digital Twin Metamodel (SDTM).
  • Figure 5: The Terminology package of the Structured Digital Twin Metamodel (SDTM).
  • ...and 13 more figures