Digital Twin
A continuously updated virtual model of a physical system, used for analysis, monitoring, and prediction.
Definition
A digital twin is a detailed virtual model of a physical asset or system that mirrors its behavior, ideally kept in sync with real data. It serves as a testbed for analysis, what-if studies, and prediction without touching the physical system.
The value of a twin scales with how faithfully it mirrors the real system and how current its data is; a stale or oversimplified twin can mislead. Validating the twin against known behavior, and being explicit about its assumptions, is what keeps it a trustworthy stand-in.
A digital twin is only as trustworthy as its fidelity to the real system and the currency of its data; a stale or oversimplified twin can mislead as easily as inform. Rigorous validation against known behavior, and explicit statements of the assumptions and limits built into the model, are what keep it a dependable stand-in. For systems not yet built, a design-stage twin communicates and tests the intended machine while making clear it represents intent, not measured reality.
Ingredients
- A physics-based or data-driven model of the system.
- A link to data (real sensors, or simulation for a design-stage twin).
- Interactive analysis and visualization.
- Verification and validation against known behavior.
Why it matters
Digital twins let engineers explore behavior, test changes, and anticipate problems safely and cheaply. For systems not yet built, a design-stage twin is a way to study and communicate the intended machine before any hardware exists.
Fusion connection
Kronos maintains a digital twin of Hyperion built on frozen physics, letting engineers and reviewers examine the design in simulation. It represents a design and simulation model, not a built machine, ahead of construction beginning Q2 2027.