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Big data analytics for the Future Circular Collider reliability and availability studies

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication22nd International Conference on Computing in High Energy and Nuclear Physics (CHEP2016)
PublisherIOP Publishing
DOIs
Publication statusPublished - 23 Nov 2017
Publication typeA4 Article in a conference publication
EventInternational Conference on Computing in High Energy and Nuclear Physics -
Duration: 1 Jan 1900 → …

Publication series

Name Journal of Physics: Conference Series
Volume898
ISSN (Print)1742-6588
ISSN (Electronic)1742-6596

Conference

ConferenceInternational Conference on Computing in High Energy and Nuclear Physics
Period1/01/00 → …

Abstract

Responding to the European Strategy for Particle Physics update 2013, the Future Circular Collider study explores scenarios of circular frontier colliders for the post-LHC era. One branch of the study assesses industrial approaches to model and simulate the reliability and availability of the entire particle collider complex based on the continuous monitoring of CERN's accelerator complex operation. The modelling is based on an in-depth study of the CERN injector chain and LHC, and is carried out as a cooperative effort with the HL-LHC project. The work so far has revealed that a major challenge is obtaining accelerator monitoring and operational data with sufficient quality, to automate the data quality annotation and calculation of reliability distribution functions for systems, subsystems and components where needed. A flexible data management and analytics environment that permits integrating the heterogeneous data sources, the domain-specific data quality management algorithms and the reliability modelling and simulation suite is a key enabler to complete this accelerator operation study. This paper describes the Big Data infrastructure and analytics ecosystem that has been put in operation at CERN, serving as the foundation on which reliability and availability analysis and simulations can be built. This contribution focuses on data infrastructure and data management aspects and presents case studies chosen for its validation.

ASJC Scopus subject areas

Publication forum classification

Field of science, Statistics Finland

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