Semantic Factor-Space Architecture for Aerospace and Defense Digital Twin Systems

This paper introduces a semantic factor-space architecture for representing and analyzing complex aerospace systems. The approach organizes subsystem properties, behaviors, and operational dependencies into orthogonal semantic threads that provide a consistent structure across design stages and model fidelity levels. The resulting representation enables reasoning across subsystem models developed in different engineering disciplines, supporting impact tracing, constraint evaluation, and cross-domain consistency without requiring specialized modeling environments. A directed dependency graph complements the semantic thread structure and enables upstream, downstream, and iterative propagation of subsystem interactions using simulation identifiers, operational intervals, and component metadata. The framework supports both conceptual design analysis and operational system evaluation while allowing incremental refinement as subsystem models mature. The architecture can be implemented using standard relational database technologies and integrated with existing simulation workflows. By formalizing subsystem attributes and their dependencies within a unified structure, the approach supports digital twin integration, cross-domain verification, and systematic reasoning across interconnected engineering systems. Potential applications include early envelope assessment, propagation-based diagnostics, and integration with future AI-supported verification and autonomous system development.