Multiphysics Stimulated Simulation Digital Twin Methods for Fleet Management

The objectives of fleet management are typically readiness, availability, and reduced risk and cost. Of course, data management is essential to handle multiple data streams from many platforms. But heart of successful, proactive fleet management is science and engineering behind interpretive analysis used for each tail number. That is focus of present paper. Science and engineering have generally focused on detecting discrete events, especially early in life, then on deciding when a certain collection of those events warrants corrective action (e.g., maintenance). This approach has two serious shortcomings for composite material components. First, composite structures rarely fail from damage initiation; they generally fail from damage accumulation and interaction. Second, limits on performance (e.g., stiffness, strength, and life) are determined by emergent behavior defined by interactive degradation events (from the bottom) and by assembly of extrinsic factors including manufacturing, geometry and morphology, load history, and expected performance (from top). The present paper discusses a rational engineering approach to real-time tail number prognosis of composite structures based on measurement and science-based interpretation of changes in multi-physical material properties. Examples of approach will be provided and application paths discussed. Relationships to durability, reliability, risk, and liability will also be identified.