Accelerator Reliability Workshop 2019(2019加速器可靠性国际研讨会)

Session

New Trends, Big Data, Machine Learning

15 Nov 2019, 08:30

Guangzhou SYSU Kaifeng Hotel

Conveners

New Trends, Big Data, Machine Learning

• Brower Julian (高能所)

Contribution list Timetable

25. Web Application for Operations

Ms Nina He (TRIUMF)

15/11/2019, 08:30

oral

Web applications are very popular tools now in the operations and they will become more and more useful along with web technology development. Because web applications have the advanced benefits like cross operating system, easy to use, and update without download the software. By using these very useful tools we can speedup operation, do monitoring the system easily, organizing people and...

28. Status of Application of Machine Learning Techniques at CRYRING ESR

Dr Wolfgang Geithner (GSI Helmholtzzentrum fur Schwerionenforschung)

15/11/2019, 09:00

New Trends, Big Data, Machine Learning – was “Innovations in Accelerator Automation and Robotics – J. Brower” and “Big Data and Machine Learning – D. Newhart”

oral

The ion storage ring is a FAIR phase 0 machine and used as test bed for FAIR concepts and prototypes in addition to being a facility for physics experiments. CRYRING ESR is equipped with an offline ion source and linear accelerator providing ion beams with energies up to 300 keV per u. This so called injector can be operated independently of FAIR or GSI and is used for machine testing and...

60. Using laser scanners and trackers to optimize accelerator installations

Mr Doug Preddy (Triumf)

15/11/2019, 09:30

oral

By combining data from laser trackers and laser scanners we can develop 3D models of an accelerator system as it is built. This allows more precise shielding installations, higher tolerancing of equipment placement and a more productive design environment. Scans of areas are taken during beam off periods and combined with other alignment parameters. The designers can use this information to...