Raffaele Piergallini
Bayesian optimization of the CHERAB code for the reconstruction of the D-α camera view in ST40 tokamak.
Rel. Fabio Subba, Matteo Moscheni. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Energetica E Nucleare, 2023
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Abstract
The next generation of nuclear fusion devices aims to achieve and sustain significantly improved plasma performance compared to existing tokamaks. This requires reliable quantification of plasma properties, power, and particle exhaust during the design phase and diagnosis during operations. Moreover, unprecedented levels of neutron irradiation are expected in pilot plants, which pose operational and servicing challenges. In this context, synthetic diagnostics are valuable tools for the fusion community. They support the interpretation of experimental data, which is inherently challenging, and enable careful diagnostic design and integrated analyses for capturing essential plasma features. The D-α camera, for example, can infer properties of the neutral deuterium distribution in the chamber, making it useful for diagnosing the edge plasma, particularly in detached divertor regimes.
This work, conducted in collaboration with Tokamak Energy Ltd, utilizes the 3D Monte-Carlo inverse ray-tracing software CHERAB to simulate the 2D perspective of a synthetic D-α camera
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