Paper | Title | Other Keywords | Page |
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MOPOST010 | Deuteron Beam Power Ramp-Up at SPIRAL2 | linac, cavity, MMI, LEBT | 70 |
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The SPIRAL2 linac commissioning started on 8 July 2019 after obtaining the authorisation to operate by the French Safety Authority. The tuning of the two Low Energy Beam Transport (LEBT), Radio Frequency Quadrupole (RFQ), Medium Energy Beam Transport (MEBT), Superconducting (SC) linac and High Energy Beam Transport (HEBT) was done with H+, 4He2+ and D+ beams during three periods of six months each in 2019, 2020 and 2021. The results obtained in 2021 with a D+ beam are presented. The strategy for the tuning of the MEBT, including three rebunchers, is described. The comparison between the beam parameter measurements and reference simulations are also presented. The main results of the power ramp-up to 10 kW in the linac with a 5 mA D+ beam are next reported. Finally, the extrapolation from the nominal power (200 kW) to the obtained results is analysed. | |||
DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-MOPOST010 | ||
About • | Received ※ 08 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 18 June 2022 | ||
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TUPOST048 | Development of a Virtual Diagnostic for Estimating Key Beam Descriptors | simulation, diagnostics, real-time, controls | 969 |
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Funding: Science and Technology Facilities Council (STFC), U.K. Research and Innovation (UKRI) Real-time beam descriptive data such as emittance, envelope and loss, are central to accelerator operations, including online diagnostics, maintenance and beam quality control. However, these cannot always be obtained without disrupting user runs. Physics-based simulations, such as particle tracking codes, can be leveraged to provide estimates of these beam descriptors. However, such simulation-based methods are computationally intensive requiring access to high performance computing facilities, and hence, they are often non-realistic for real-time purposes. The proposed work explores the feasibility of using machine learning to replace these simulations with fast-executing inference models based on surrogate modelling. The approach is intended to provide the operators with estimates of key beam properties in real time. Bayesian optimisation is used to generate a synthetic dataset to ensure the input space is efficiently sampled and representative of operating conditions. This is used to train a surrogate model to predict beam envelope, emittance and loss. The methodology is applied to the ISIS MEBT as a case study to evaluate the performance of the surrogate model. |
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DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST048 | ||
About • | Received ※ 01 June 2022 — Revised ※ 12 June 2022 — Accepted ※ 27 June 2022 — Issue date ※ 02 July 2022 | ||
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WEPOTK001 | Status of the Normal Conducting Linac at the European Spallation Source | DTL, MMI, rfq, LEBT | 2019 |
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The construction of the ESS accelerator is in full swing. Many key components have been delivered from our in-kind partners and installation, testing and commissioning is making remarkable progress. The first machine section to be commissioned with beam is the Normal Conducting Linac (NCL). When completed, a 14 Hz, 2.86 ms proton beam up to 62.5 mA will be transported from the Ion Source, through the Low Energy Beam Transport (LEBT) line, the Radiofrequency Quadrupole (RFQ), the Medium Energy Beam Transport (MEBT) line and the five Drift Tube Linac (DTL) tanks up to 90 MeV where it will be injected in the first superconducting module of the machine. This paper will highlight recent progress across the NCL, present briefly the first commissioning results and discuss the upcoming phases as well as challenges in delivering a machine capable of meeting the requirements for a next generation spallation neutron facility. | |||
DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-WEPOTK001 | ||
About • | Received ※ 13 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 02 July 2022 | ||
Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | ||