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AI Architecture › L3 · Twin Modeling & AI
L3 · Twin Modeling & AI

KRONOS-CTRL: Thermomechanics Module

The Thermomechanics module maps thermal loads and strain across the vessel, magnets, and divertor, turning physics into structural-health state.

THE STACK · click to jumpL7Ecosystem & StrategyL6Experience & VisualizationL5Applications & CopilotsL4OrchestrationL3Twin Modeling & AIL2Data FabricL1Control PlaneL0Foundation▲tlmctl▼L3 · TWIN MODELING & AIThe KRONOS-CTRL digital twin and its predictive shadow.1KRONOS-CTRL Twinlive plant state2GNNscoupled subsystems3PINNsphysics-constrained4Anomaly Ensemblesdrift & fault detection5MPCreceding-horizon control6Predictive Shadowruns seconds aheadMACHINE TIEState estimate descends to L1 control; alerts rise to L4 / L5.KRONOS FUSION ENERGYAI-NATIVE S.M.A.R.T. GENERATORTWIN MODELING & AISHEET 05REV. 2026-08L3 · AI-NATIVE STACK
L3 · Twin Modeling & AI — its place in the stack (left, click any layer) and its internal components (right). Telemetry rises; control descends.

Scope

The Thermomechanics module models heat and mechanical stress in the machine structure: volumetric neutron heating in the blanket and vessel, surface heat flux on the divertor and first wall, Lorentz and preload stresses in the REBCO magnets, and the resulting temperature and strain fields. It converts the physics from the other modules into the mechanical state that governs component life and near-term thermal margins.

Inputs and outputs

The divertor and expander are the highest-heat-flux surfaces and set a hard thermal constraint that shape-control MPC (breeder) and end-loss handling (burner) must respect; the module supplies the live heat-flux estimate and margin. The carbon-fiber cocoon and CrMoNbV vessel are tracked for thermal expansion, which feeds back geometry changes to the equilibrium and free-boundary solves.

Structural health monitoring

The module maintains a structural-health record by fusing the strain-gauge network (through the sensor-topology GNN), the accumulated neutron fluence from Neutronics, and the ICE-PISTON preload-cycle signatures. Deviation of measured strain from the modeled coupled pattern is the input to the strain-anomaly detector; drift in the preload signature across cycles indicates fatigue. This turns the twin into a continuous structural-health monitor, not just a plasma model.

A physics-informed thermomechanical surrogate (conduction plus thermoelastic response) keeps the module fast enough for the shadow, validated against finite-element thermomechanical reference models the same way the equilibrium PINN is validated against FEM.

Content reviewed August 2026 · design-and-simulation stage