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TRAINABLE 23 workshop

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CERN & GANIL
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40/S2-D01 - Salle Dirac (CERN)

40/S2-D01 - Salle Dirac

CERN

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Adnan Ghribi
Description

TowaRds An INternational network for multiphysics modelling, machine learning And model-Based control in accelerator sciences and technoLogiEs

The digital transformation of our society, using big data is playing an essential role for our environment. Knowledge sharing and open science are also considered to be important parts of the foreseen developments through open source and FAIR principle.


The future project is part of the development of a European roadmap for the use of artificial intelligence in accelerator technology and physics. Indeed, particle accelerators have been an important part of knowledge and technology transfer to society in many fields and disciplines. Today, this ecosystem is made of Research Infrastructures (RI) with quasi-industrial challenges in term of control and reliability. With the fast evolution of the methods and techniques, the gap between existing infrastructures and future projects is increasing. This project proposes to build a bottom-up bridge between institutes, research infrastructures and European projects. Building this bridge, from the numerical methods perspective, needs to set-up a virtual work environment centred around data and methods sharing as well as knowledge and skills transfer between experts and institutes. The HORIZON-INFRA-2024-TECH-01-01 call gives the perfect opportunity for it.


There are two main targets for the identified developments. The first focuses on reliability of RI by increasing the beam time, quality and reproducibility. Anomalies detection, prediction and prevention are an important part of it.


The second builds upon the experience of existing RI and new artificial intelligence (AI) numerical methods to optimise the design of future accelerators as well as the optimisation of their operation strategies and reliability.

 

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