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3D Model
AI Architecture › Physical Interfaces
Physical Interfaces

Vessel Structural-Health-Monitoring Interface

Distributed strain, displacement, and acoustic sensing on the vessel feed the twin's fatigue model and a slow structural-alarm path.

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.

What it watches

Both machines subject their vacuum vessels to large, cyclic electromagnetic and thermal loads — the breeder from disruptions and the 9.66 MA current, the burner from its mirror fields and thermal cycling. The structural-health-monitoring (SHM) interface instruments the vessel so cumulative damage is tracked long before it becomes a fault.

Sensor set

python
# rainflow fatigue accumulation (twin, slow loop)
cycles = rainflow(strain_history[node])
for (amp, mean, n) in cycles:
    D[node] += n / N_allow(amp, mean)     # Miner's rule
if D[node] > D_warn:
    schedule_inspection(node)             # predictive maintenance

Two paths

PathOwnerTrigger
fast alarmL1overstress/limit
fatigue trendL3cumulative D
maintenanceL4/L7inspection window

The fast path is a simple limit alarm owned by L1; it exists for gross overstress, not routine control. The valuable path is slow: the twin integrates strain cycles into a damage estimate (Miner's rule via rainflow counting) that drives predictive maintenance and spare-parts planning.

Owner: sense-side L2; fatigue model L3; maintenance L4/L7. Calibration ties gauges to a known load and tracks drift so accumulated damage is never computed through a stale sensor. Design-and-simulation specification, exercised against the twin's thermomechanics module.

Content reviewed August 2026 · design-and-simulation stage