CERN, Geneva, Switzerland
MINES ParisTech, PSL Research University, Paris, France
The Proton Irradiation Facility (IRRAD) is a reference facility at CERN for characterizing detectors and other accelerator components against radiation. To ensure reliable facility operations and smooth experimental data handling, a new IRRAD Data Manager (IDM) web application has been developed and first used during the last facility run before the CERN Long Shutdown 2. Following best practices in User Experience design, IDM provides a user-friendly interface that allows both users to handle their samples’ data and the facility operators to manage and coordinate the experiments more efficiently. Based on the latest web technologies such as Django, JQuery and Semantic UI, IDM is characterized by its minimalistic design and functional robustness. In this paper, we present the key features of IDM, our design choices and its overall software architecture. Moreover, we discuss scalability and portability opportunities for IDM in order to cope with the requirements of other irradiation facilities.
CERN, Meyrin, Switzerland
MINES ParisTech, PSL Research University, Paris, France
EPFL, Lausanne, Switzerland
The IRRAD proton irradiation facility at CERN was built during the Long Shutdown 1 (LS1) to address the irradiation experiment needs of the community working for the High-Luminosity (HL) upgrade of the LHC. The present IRRAD is an upgrade of a historical service at CERN that, since the 90’s, exploits the high-intensity 24 GeV/c PS proton beam for radiation-hardness studies of detector, accelerator and semiconductor components and materials. During its first run (2015-2018), IRRAD provided a key service to the CERN community, with more than 2500 samples irradiated. IRRAD is operated via custom-made irradiation systems, beam diagnostics and data management tools. During the Long Shutdown 2 (LS2), IRRAD will undergo several upgrades in order to cope also with new requirements arising for projects beyond the HL-LHC. In this paper, we (1) describe the various hardware and software equipment developed for IRRAD, and (2) present the main challenges encountered during the first years of operation, which have driven most of the improvements planned for LS2 such as applying machine-learning techniques in the processing and real-time analysis of beam profile data.