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AI Architecture › L0 · Foundation
L0 · Foundation

Negative-Triangularity Shape Scans

Wide equilibrium and stability campaigns mapping the breeder's delta -0.30 ELM-free shape and its operating margins.

THE STACK · click to jumpL7Ecosystem & StrategyL6Experience & VisualizationL5Applications & CopilotsL4OrchestrationL3Twin Modeling & AIL2Data FabricL1Control PlaneL0Foundation▲tlmctl▼L0 · FOUNDATIONThe offline compute substrate — multi-physics & batch training.1Cloud HPCelastic burst2Bare-Metal ClusterGPU / CPU3Supercomputingmulti-physics runs4Batch Trainingmodel builds5Simulation FarmGrad-Shafranov · MHD6Object StorecheckpointsMACHINE TIETrains the models that ship UP to L3 — no real-time path to the machine.KRONOS FUSION ENERGYAI-NATIVE S.M.A.R.T. GENERATORFOUNDATIONSHEET 02REV. 2026-08L0 · AI-NATIVE STACK
L0 · Foundation — its place in the stack (left, click any layer) and its internal components (right). Telemetry rises; control descends.

Why scan the shape

The breeder's edge shape is a deliberate design choice: negative triangularity, delta -0.30, chosen to access an ELM-free edge that avoids the pulsed heat loads of edge-localized modes. To trust that choice, L0 scans the shape space around delta -0.30, computing equilibria and their stability so the design point is understood as a region, not a single fragile setting.

What the scan varies

Each point in the scan is a full equilibrium solve, followed by stability and edge-transport evaluation. The campaign varies triangularity, elongation, and edge gradients around the target, holding the design anchors, R0 1.2 m, aspect ratio 2.5, plasma current 9.66 MA, near their design values, to map how edge behavior changes with shape.

An independent-solve campaign

Because each shape is an independent equilibrium plus stability solve, the scan parallelizes cleanly across the solver farm. It behaves like the neutronics TBR sweep: a wide, embarrassingly parallel exploration that produces a response surface, here mapping shape to edge stability and confinement rather than blanket design to breeding.

The scan quantifies margin. It shows how far the design can drift from delta -0.30 before the ELM-free benefit is lost or a stability limit is approached, which tells the control system how tightly it must hold the shape. That margin becomes a requirement on the twin's equilibrium tracking and the MPC agents that maintain the boundary.

Selected points are re-run on the reproducible core and become training data for the twin's shape-control surrogate. In this way a broad offline exploration of negative triangularity turns into a specific, fast, validated capability to hold the delta -0.30 shape in real time once the breeder operates.

Content reviewed August 2026 · design-and-simulation stage