Synchronizing the Shadow to the Real Plant
A forecast that drifts from reality is worse than none; Kronos continuously corrects the twin toward live telemetry so the shadow stays anchored.
Prediction plus correction
The predictive shadow is a predict-correct cycle. Each step, the twin predicts the next state from its physics, then corrects that prediction toward the latest L2-validated measurements. This is classical state estimation applied to a multi-physics twin: the physics provides the forward model, the diagnostics provide the corrections, and the estimator blends them by their relative trust.
Handling latency and rate
Diagnostics arrive at different rates and with different latencies, magnetics fast, Thomson scattering slower, neutron counting integrated over a window. The synchronizer time-aligns them using L2 timestamps and folds each in when it arrives, rather than waiting for the slowest. Fast magnetics keep the equilibrium anchored between slower kinetic updates; the kinetic updates correct profile drift when they come.
- Predict: advance the coupled twin state one step via surrogates
- Align: time-stamp and register multi-rate diagnostics from L2
- Correct: pull the state toward measurements weighted by trust
- Impute: use GNN-reconstructed values (with widened uncertainty) for dropped channels
When channels drop, the GNN imputation feeds the correction step but with inflated measurement uncertainty, so the estimator leans more on physics where data is missing and does not over-trust a reconstructed value. If observability degrades badly, the correction weakens and the twin's confidence drops, again the honest-degradation principle.
Pre-FOAK there is no real plant to synchronize to, so the shadow is validated in a plant-in-the-loop simulation where a high-fidelity offline model plays the role of the machine. This exercises the full predict-correct loop, including latency and dropout handling, so that when FOAK telemetry arrives ~2030 the synchronizer is already validated and only needs recalibration to real signals.