WeChat Mini Program
Old Version Features

The Phase Loop Status of the RF System in CSNS/RCS

12th International Particle Accelerator Conference (IPAC'21), Campinas, SP, Brazil, 24-28 May 2021(2021)

Cited 0|Views4
Abstract
The Rapid Cycling Synchrotron (RCS) of the China Spallation Neutron Source (CSNS) is a high intensity proton accelerator. The acceleration system consists of eight ferrite loaded cavities. The RCS is the space charge dominant machine and it is mitigated through the bunch factor optimization in the beam commissioning, so the injected beam will occupy a larger bucket size and unavoidable mismatch with the bucket, thus the dipole oscillation is excited. The phase loop scheme is designed to restrict the oscillation in the RF system, but the transmission efficiency is reduced by the phase loop and the bunch factor also increases, so the phase loop scheme is studied. To keep the phase loop but also maintain the transmission efficiency, we optimized the original phase loop scheme, but the beam loss still increases small when the loop on. INTRODUCTION The China Spallation Neutron Source [1, 2] (CSNS) is a high intensity proton accelerator-based facility. The accelerator complex includes a negative hydrogen (H-) linac and a rapid cycling synchrotron (RCS). The Hbeam is injected into the RCS through a multi-turn charge-exchange process. The beam is painted in longitudinal plane with the energy deviation between the injected beam energy and the RCS synchronous particle energy. The designed momentum filling is 0.82. The beam is extracted to the target with the beam power of 100 kW. The power will increase to 500 kW by increasing the injection energy to 300 MeV to decrease the space charge effects and increase the beam intensity in the RCS. The CSNS beam commissioning started in 2016 and it was finished in February, 2020, reaching the designed beam power of 100 kW. Figure 1 shows the accelerator layout of the CSNS. The RCS is the core of the CSNS and the main parameters are listed in Table 1. The RCS accumulates and accelerates proton beam from 80 MeV to 1.6 GeV with the repetition rate of 25 Hz. The RF acceleration system consists of eight ferrite loaded cavities. The maximum cavity voltage is set to be 165 kV with a maximum synchronous phase of 45 degrees. The RF frequency is driven by a bias power supply, allowing it to be synchronous changed with beam energy. The RCS is the space charge dominant machine. The space charge effects for the beam with high intensity are dominant before 5 ms and result in beam loss. Therefore, the space charge mitigation is the key task of the beam commissioning. A good way to mitigate the strong space charge effects is to uniform the longitudinal beam distribution, namely to improve the bunch factor. The beam phase is the beam core in longitudinal plane and it is given from the fast-current-transformer (FCT) signal after the digital I/Q demodulation [3]. As the bunch factor increases, the injected beam will occupy a larger bucket size and unavoidable mismatch with the bucket, which will lead to the dipole oscillation in the longitudinal plane. The oscillation will exist long time in the proton ring and it reduces the stability region in longitudinal plane and affects the cavity operation. Therefore, the RF system is designed with a phase loop scheme to damp the oscillation. The beam phase with a digital filter and 90 degrees shift is adopted as a feedback in the loop. However, the transmission efficiency is reduced about one percent after introducing the scheme. The phase loop is introduced and optimized in the paper. Figure 1: The layout of CSNS accelerator: linac and RCS. Table 1: The RCS Main Parameters Parameters Units Values Circumference m 227.92 Injection energy MeV 80 Extraction energy GeV 1.6 Injection energy spread % 0.05 ~ 0.5 Momentum acceptance % 1 Momentum filling factor 0.82 Proton per pulse E13 1.56
More
Translated text
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined