SMStefano Marchioni

Stefano Marchioni

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

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Stefano Marchioni has a total of 13 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Real-time vertical instability growth rate formulation and proximity controller application in the TCV tokamak

    by Stefano Marchioni, Federico Felici, Olivier Sauter, Cristian Galperti, Antoine Merle, Alessandro Pau, Francesco Carpanese

  • Open Access

    FGE: A Fast Free-Boundary Grad-Shafranov Evolutive Solver

    by Cosmas Heiß, Antoine Merle, Francesco Carpanese, Federico Felici, Craig Donner, Stefano Marchioni, Alessandro Mari, Olivier Sauter

    Accurate and rapid simulation of the free boundary tokamak plasma equilibrium evolution is essential for modern plasma control, stability analysis, and scenario development. This paper presents the Free-Boundary Grad-Shafranov Evolutive (FGE) code, a highly flexible and control-oriented solver designed to address the challenges posed by advanced plasma configurations across a range of devices. FGE evolved from the FBT [Hofmann, 1988] and LIUQE [Moret et al., 2015] codes and is part of the MEQ suite, sharing many of the low-level optimized functions. It self-consistently solves the free-boundary Grad-Shafranov equation coupled with circuit equations for external conductors and models for plasma profile evolution. The code implements a fully non-linear, Newton-based framework with multiple, highly optimized solver options, state representations, and residual formulations that enable rapid computation across different simulation setups. A key capability is the self-consistent integration of various 0D and 1D current diffusion equations (CDEs) to model the resistive evolution of the plasma current profile as well as the ability to model plasmas with multiple magnetic axes (Doublets). Furthermore, FGE allows to linearize the plasma dynamics around a given equilibrium to generate a state-space model suitable for controller design and analysis. Numerical studies are presented demonstrating the code's speed of convergence and validating its performance against experimental data. Furthermore, benchmarks against the RAPTOR and KINX codes for profile evolution and vertical growth rate estimates are presented highlighting FGE's capabilities for both prediction and analysis.