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AI Architecture › L6 · Experience
L6 · Experience

Training-Simulator Mode

The same interface, driven by the twin instead of live diagnostics, so operators rehearse both machines — including unsafe-to-create upsets — before and between real runs.

THE STACK · click to jumpL7Ecosystem & StrategyL6Experience & VisualizationL5Applications & CopilotsL4OrchestrationL3Twin Modeling & AIL2Data FabricL1Control PlaneL0Foundation▲tlmctl▼L6 · EXPERIENCE & VISUALIZATIONHow people see, steer, and review the plant.1Control-Room 3D Twinlive overlays2Plant-Floor SCADAoperations HMI3Mobile Engineeringfield access4Alerting UXtriage & escalation5DashboardsKPIs & health6Replayincident reviewMACHINE TIESurfaces the L3 twin state and L5 copilots to human operators.KRONOS FUSION ENERGYAI-NATIVE S.M.A.R.T. GENERATOREXPERIENCE & VISUALIZATIONSHEET 08REV. 2026-08L6 · AI-NATIVE STACK
L6 · Experience & Visualization — its place in the stack (left, click any layer) and its internal components (right). Telemetry rises; control descends.

Rehearse on the real interface, not a mock-up

Operators build reliable intuition only by practicing on the interface they will actually use. Training-simulator mode runs the full control-room surface — 3D twin overlay, dashboards, alerting, countdown — driven by the KRONOS-CTRL twin instead of live diagnostics. Nothing about the operator's mental model changes between training and operation, which is why the twin-first approach is central while the machines are still being built toward first-of-a-kind first tritium (~2030).

Scripted scenarios, including the unsafe ones

The simulator can present situations that would be reckless to create on real hardware: a breeder disruption sequence, a cascading diagnostic failure that forces the twin onto imputed inputs, a burner plug-density excursion, a magnet quench precursor at the 16.84 T peak field. Operators rehearse the recognition, the triage, and the countdown decision under realistic time pressure, and learn where the AI's confidence should and should not be trusted.

Measuring and closing the loop

The simulator is also where the interface itself is tested. Operator situational awareness is probed with SAGAT-style freezes, cognitive load is estimated during scripted upsets, and any display that spikes load or degrades awareness is revised. Notification thresholds, alarm rationalization, and layout are all tuned against simulator evidence rather than opinion. Trainee performance and the interface's performance improve together.

Training draws directly on the what-if scenario console and recorded incident replays as scenario seeds, and its findings feed cognitive-load and notification design. The same firewall applies: the simulator can never reach live actuation.

Content reviewed August 2026 · design-and-simulation stage