Structural comparison between representative physics-informed digital twin approaches
| Feature | Conventional PINN digital twins | Mechanism-specific digital twins | Present framework |
|---|---|---|---|
| Primary objective | High-fidelity prediction | Mechanism-level modelling | Physically consistent degradation tracking |
| State dimensionality | Often high-dimensional | Multi-parameter | Compact, physically governed state |
| Governing physics | PDE-based or system-specific | Constitutive or mechanism-dependent | Irreversible kinetic formulation |
| Physical admissibility | May depend on training | System-dependent | Enforced structurally |
| Data requirement | Moderate to high | Moderate | Low to moderate |
| Interpretability | Variable | Moderate | High |
| Feature | Conventional PINN digital twins | Mechanism-specific digital twins | Present framework |
|---|---|---|---|
| Primary objective | High-fidelity prediction | Mechanism-level modelling | Physically consistent degradation tracking |
| State dimensionality | Often high-dimensional | Multi-parameter | Compact, physically governed state |
| Governing physics | PDE-based or system-specific | Constitutive or mechanism-dependent | Irreversible kinetic formulation |
| Physical admissibility | May depend on training | System-dependent | Enforced structurally |
| Data requirement | Moderate to high | Moderate | Low to moderate |
| Interpretability | Variable | Moderate | High |
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