Speaker
Description
Particle accelerators exhibit complex behaviour emerging from the interaction of diverse machine systems, services, beam and environmental conditions. Since 2015 we explore the fitness of probabilistic reliability engineering to particle accelerators. The investigation relies on the LHC as use-case. Results indicate that the approach, already well established in manufacturing, automotive, pharmaceutical, process and other industries fits well the needs of particle accelerator facilities. Consequently, an R&D project has been launched to develop an open method to model and simulate the behaviour large systems efficiently.
It does not rely on graphical user interfaces, permits specifying large sets of equipment characteristics in time and space saving manner, adequately addresses building models in a collaborative fashion, is data store agnostic and is incrementally extensible to different modelling techniques and simulation engines. Considering the processing requirements, the implementation by Ramentor will also permit deployment in a distributed computing cluster, leading simulation times cut by a factor 10 to 100. The approach and tool will help building reliability, availability and energy
efficiency into the designs of a future circular collider. Ramentor will offer the suite to industrial clients for the assessment and improvement of energy efficiency and availability in very diverse domains such as data centres, cargo handling and natural gas distribution.
