Replication Data for: A Real-Time Optimization Backbone for Fusion Plasma Control: Quadratic-Programming, Reduced-Basis and Adjoint-Sensitivity Engines at Control Latency
Year: 2026
Type: dataset
Abstract: Replication data for the paper A Real-Time Optimization Backbone for Fusion Plasma Control: Quadratic-Programming, Reduced-Basis and Adjoint-Sensitivity Engines at Control Latency (Kronos Fusion Energy 2026 Publication Series, paper 2.87), published at doi:10.5281/zenodo.22645899. Abstract of the paper. Real-time control of a compact, high-power-density spherical tokamak is a constrained optimization problem that must be solved to a certified answer inside each control period, every period; the controller is only as trustworthy as its ability to solve that program fast, accurately, and safely. We formalise the optimization backbone that makes this tractable for the Kronos Hyperion breeder (design point I_p=9.66 MA, Q=3.076, P_ fus=85.04 MW, negative triangularity δ=-0.30, B_0=8 T, elongation κ=2.0, major radius =1.20 m, aspect ratio A=2.5, centrepost peak field 16.84 T) and demonstrate three of its four engines at the kernel level, deriving each as an explicit mathematical program. (i) A control-barrier quadratic program (QP) renders the operating set \βN 3.5\ forward-invariant: we prove invariance by a comparison-lemma argument and confirm it numerically — a perturbation sequence that drives the unclamped loop to βN=4.20 with 50/100 steps in violation is held by the clamped loop at a maximum βN=3.500 with minimum barrier value +0.000 and 0/100 violations, using only a bounded, non-saturating actuator command u[1.06,1.25]. What this dataset contains data/key_values.csv and data/anchors.json: the frozen design-point values quoted in the paper (symbol, value, unit, provenance), in machine-readable form. data/verification.csv: the validator gates the paper cites, each with its verdict and a link to a live recompute page. figures/: the figures from the paper, as vector PDF, with an inventory. a-real-time-optimization-backbone-for-fusion-plasma-con.data-methods.pdf: methods, the computational codes used, and the full value table. data/data_dictionary.md: column definitions. Every value is a frozen design-point number that is independently re-run and recorded in the Kronos Physics De-Risking Register (doi:10.5281/zenodo.22645689). The paper itself is not duplicated here; read it at the DOI above.
Source: Harvard Dataverse
DOI: 10.7910/dvn/mnv0nr
Author: Ford, P I
Language: English
Subfield: Nuclear and High Energy Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7214653835