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AI Architecture › Physical Interfaces
Physical Interfaces

Divertor Thermography Interface

Infrared cameras give a 2-D surface-temperature field on the divertor and first wall; the interface turns raw frames into calibrated heat-flux maps.

STRATEGY / SLOW ▲ ▼ MICROSECOND REAL-TIMEL7Ecosystem & Strategytelemetry ▲ control ▼open ▸L6Experience & Visualizationtelemetry ▲ control ▼open ▸L5Applications & Copilotstelemetry ▲ control ▼open ▸L4Orchestrationtelemetry ▲ control ▼open ▸L3Twin Modeling & AItelemetry ▲ control ▼open ▸L2Data Fabrictelemetry ▲ control ▼open ▸L1Control Planetelemetry ▲ control ▼open ▸L0Foundationtelemetry ▲ control ▼open ▸PHYSICAL S.M.A.R.T. GENERATOR PLANTBREEDER · HYPERION1R0 1.2 m · A 2.5 · 16.84 T · δ −0.30BURNER · TANDEM MIRROR2317 T throat · 26.49 T plug · fₙ 5.44% · DEC1 center stack + plasma · 2 high-field plug · 3 expander → direct converterCOLOR GRAMMAR strategy AI-workflow infra/data models reactor/DECLINE SEMANTICStelemetry (µs)controlKRONOS FUSION ENERGYAI-NATIVE S.M.A.R.T. GENERATORMASTER BLUEPRINTSHEET 01REV. 2026-08L0-L7 · 2 MACHINES
The AI-Native S.M.A.R.T. Generator Master Blueprint — eight layers (L0→L7), one control stack, wired to both machines. Telemetry rises in microseconds; control descends the same path.

From frames to heat flux

A single thermocouple gives a point; the divertor needs a field. Infrared thermography cameras image the strike-point region and reconstruct surface temperature across the target, which the twin inverts into a heat-flux map. This map drives detachment control and erosion trending.

The inversion

python
# surface heat flux from IR temperature history
# solve 1-D transient conduction per pixel:
#   rho*c_p dT/dt = d/dx( k dT/dx )
# with measured surface T(t) as boundary condition
q_surf[px] = invert_conduction(T_ir[px, :], material[px])
heatmap = assemble(q_surf)     # 2-D flux field for control + twin

The inversion is per-pixel transient conduction using the measured surface-temperature history as the boundary condition — it is model-based, so its accuracy depends on the material properties and on emissivity calibration. A layer of redeposited material changes emissivity and biases the reading, which is why calibration drift is tracked continuously.

Consumers

Owner: sense-side L2 for frame transport and timestamping; L3 for inversion and heat-flux mapping. Timing: the map updates fast enough for detachment control (tens of ms) but is not on the protection path itself. Design-and-simulation specification, validated against the twin.

Content reviewed August 2026 · design-and-simulation stage