Optimizing Diagnostic Analysis Chain and Data Storage System in the ST40 fusion device

Magnetic confinement devices are a promising path to achieve controlled fusion, where plasma, the fourth state of matter, is contained by magnetic fields and heated to extreme temperatures. A comprehensive set of diagnostic systems is essential to generate and control the plasma and sustain fusion reactions. The analyses of the data produced must be deployed in a specific order, considering potential interdependencies and the availability of raw data. The ST40 tokamak, operated by Tokamak Energy Ltd in Oxfordshire, United Kingdom, achieved a milestone by reaching 100 million Kelvin ion temperature[1] , marking a significant breakthrough for spherical tokamaks and highlighting the role of the private sector in fusion energy research. In this poster, the Post Pulse Analysis Chain (PPAC) responsible for inter-pulse diagnostic data analysis of ST40 is discussed. PPAC executes over 20 analysis scripts written in Python, MATLAB, Fortran, and IDL and is managed by SLURM workload manager[2] to deal with inter-dependencies and resource allocation. The experimental data is stored in a centralized database called MDSplus[3], accessible to anyone within Tokamak Energy's network. The poster also gives an overview of various diagnostic analyses and explains the workflow organization, discussing data storage and retrieval strategies in the MDSplus system, and code deployment, showcasing the effectiveness of PPAC for informed experimental operation. A recording of this session is available on YouTube: https://youtu.be/MjhhCI0GOU8