Antoine Guinet | Searcharxiv

arXiv2026

Data-Driven Optimisation of Superconducting Magnets at CEA Paris-Saclay

Superconducting magnets for particle accelerators are particularly challenging to design because they involve a large number of coupled physical phenomena and the management of complex datasets. Artificial Intelligence (AI), including machine learning and advanced optimisation techniques, offers promising approaches to address these challenges and accelerate the design process. This paper presents a new AI-based optimisation and data management platform, and highlights several ongoing applications of AI methods carried out at CEA Paris-Saclay, including multiphysics optimisation using active learning, topology optimisation, holistic modelling of an Electron Cyclotron Resonance (ERC) ion source, and anomaly detection in quench events.

physics.acc-ph↗

arXiv2026

Quench Protection in Insulated REBCO Conductors: Design Optimization and Fast Detection via REBCO SQD

This work was conducted within the framework of the exploratory French project PEPR SupraFusion, which aims to advance the field of fusion energy by developing High-Temperature Superconductor (HTS)-based demonstrators capable of storing significant energy while operating under high magnetic fields and currents. Ensuring a reliable protection during a quench in Insulated REBCO conductors is challenging\,: slow normal-zone propagation and validation delays allow the hotspot's temperature to reach damaging levels. We compare (i) conductor protection via copper-stabilizer optimization and (ii) a co-wound, REBCO superconducting quench detector (SQD) that is electrically isolated yet thermally coupled and intentionally deoxygenated to lower Tc and Ic for an earlier transition. Onedimensional THEA modeling shows that a good choice of stabilizer cross-section makes the protection possible during quench events by keeping the temperature of the hotspot within a safe limit. The simulations also demonstrate that the use of a REBCO SQD enables the quench detection at lower temperatures.

cond-mat.supr-con↗