Challenges and opportunities: can machine learning help speed up the development of magnetic confined fusion?
- 12:00 11th June 2024 ( week 8, Trinity Term 2024 )Room 051, Wolfson Building
Magnetic confinement is currently thought to be the most promising route to the exploitation of fusion energy on earth. Both the tokamak and stellarator configurations have been extensively studied, and considerable steps forward have been made in understanding the underlying physics and solving the engineering challenges. But before a power plant can successfully deliver electricity to the grid, some major hurdles still need to be overcome.
In this presentation, we will consider some of these challenges (recirculating power, long-pulse, divertor power load, etc.) and discuss how they are being tackled in present-day experiments. From the hot core, through the plasma boundary and up to the reactor first wall, we will review the range of time- scales and gradient lengths, symmetries and asymmetries that have to be probed to understand such a complex system. We will examine the elaborate diagnostic suite used to characterise and control the plasma dynamics, focusing on parametric interdependencies of the measurements, and highlighting the need for integrated data analysis and model-driven workflows.
Speaker bio
Marco Sertoli is senior plasma physicist at Tokamak Energy where he has been leading the Experimental Diagnostic Analysis group, accountable for analysis, interpretation, validation, visualisation and management of diagnostic data of the ST40 tokamak experiment, located in Oxfordshire.
He previously worked at UKAEA (Culham, UK), at the Max-Planck-Institut for plasma physics (Munich, Germany), and at the Consorzio RFX research centre (Padova, Italy). He has been scientific coordinator and has contributed to experiments on the experimental fusion devices at these institutes, and has performed research on a wide set of topics, including impurity transport, Magneto-Hydro-Dynamic (MHD) instabilities, auxiliary heating, dust, and disruptions. He has experience with many different plasma diagnostic systems, and is particularly interested in integrated analysis workflows that combine a wide set of measurement techniques, overlapping with theoretical and numerical modelling, working towards a holistic view of experimental plasma physics.
Marco holds a master’s degree in Physics from Turin University (Italy), a master’s in Engineering and Physics of Plasmas from Padova University (Italy), and a PhD in Physics from the LMU University and the Max-Planck-Institut für Plasmaphysikin Munich (Germany).
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