Executive Summary
This paper provides a comprehensive review of Digital Twin (DT) technology in defense modeling and simulation. It discusses DT applications for planning, training, and operations, introducing a characterization framework and a taxonomy of defense use cases. The authors consolidate existing research, present findings from a stakeholder questionnaire, and identify key gaps and future research directions, such as interoperability, security, and system integration.
Why It Matters
This document is crucial for defense analysts as it outlines how Digital Twin technology can revolutionize military planning, training, and operational efficiency, while also highlighting critical challenges for its successful integration.
Key Takeaways
- Digital Twins offer significant potential to enhance simulation fidelity, interoperability, and decision support across defense applications.
- Key challenges for Digital Twin adoption in defense include interoperability, security, and system integration, as revealed by stakeholder feedback.
- A standardized characterization framework is proposed to unify and standardize defense Digital Twins across various domains and use cases.
- The technology integrates real-time data, AI, and simulation to create dynamic virtual replicas of physical systems.
- Digital Twins can optimize resource management, enable predictive maintenance, and improve asset availability in military contexts.
Strategic Relevance
Digital Twin technology has the potential to significantly improve military readiness, operational efficiency, and decision-making by providing high-fidelity virtual replicas of physical systems and environments. Its successful implementation can lead to optimized resource allocation, enhanced training, and proactive maintenance, directly impacting strategic capabilities and tactical execution.