CERN Accelerating science

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Title Data Acquisition System of the CLOUD Experiment at CERN
Author(s) Weber, Stefan K (CERN) ; Miotto, Giovanna Lehmann (CERN) ; Almeida, João (CERN) ; Blanc, Pascal Herve (CERN) ; Dias, António (Lisbon, CENTRA ; Lisbon U.) ; Malaguti, Giulio (CERN) ; Manninen, Hanna E (CERN) ; Pfeifer, Joschka (CERN) ; Ravat, Sylvain (CERN) ; Onnela, Antti (CERN) ; Mathot, Serge (CERN) ; Kirkby, Jasper (CERN ; Goethe U., Frankfurt (main)) ; Tomé, António (Beira Interior U., Covilha) ; Amorim, António (Lisbon, CENTRA ; Lisbon U.)
Publication 2021
Number of pages 13
In: IEEE Trans. Instrum. Meas. 70 (2021) 1-13
DOI 10.1109/TIM.2020.3023210
Accelerator/Facility, Experiment CLOUD
Abstract The Cosmics Leaving OUtdoor Droplets (CLOUD) experiment at the European Organization for Nuclear Research (CERN) is investigating the nucleation and growth of aerosol particles under atmospheric conditions and their activation into cloud droplets. The experiment comprises an ultraclean 26 m3chamber and its associated systems (the CLOUD facility) together with a suite of around 50 advanced instruments attached to the chamber via sampling probes to analyze its contents. The set of instruments changes for each experimental campaign according to the scientific goals. The central function of the CLOUD DAQ (data acquisition) system is to combine the data from these autonomous and inhomogeneous instruments into a single, integrated CLOUD experiment database. The DAQ system needs to be highly adaptable to allow a fast setup over a single installation week at the start of each campaign when the instruments are brought to CERN and installed at the CLOUD chamber. Each campaign requires high flexibility and fast response to changes in instrument configuration or experimental parameters. The experiments require online monitoring of the physical and chemical measurements with delays of only a few seconds. In addition, the raw data, the monitoring databases, and the processed data must be archived and provided to the international collaboration for both real-time and later analyses. We will describe the various components of the CLOUD DAQ and computing infrastructure, together with the reasons for the chosen solutions.
Copyright/License CC-BY-4.0

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