06 Beam Instrumentation, Controls, Feedback, and Operational Aspects
T33 Online Modeling and Software Tools
Paper Title Page
WEPAF003 Beamline Architect 1812
  • J.D. Kunz, C.M. Conrad, L.M. Romero
    Anderson University, Anderson, USA
  Funding: Indiana Space Grant Fellowship Program 2015-2018, subaward number 4103-82252
Beamline Architect is a new particle accelerator simulation tool. Currently, two of the most widely used tools in this field are G4beamline and COSY Infinity. While these codes are fast and quite accurate, sometimes their interfaces can be time-consuming for students to learn, particularly undergraduate students or students whose primary field is not accelerator physics. Without Beamline Architect, each code has its own high-level language that must be manually written into a file and then executed on the command line. Moreover, sometimes the use of both simulation tools is warranted in order to check for consistency between the codes. Writing the codes by hand or translating between software can sometimes be cumbersome, even for experts. Furthermore, knowledge of an additional language, such as Python, is required in order to analyze the outputs of the codes (which may be in different formats from one another). Beamline Architect is a tool that provides a graphical user interface to G4beamline and COSY Infinity. This lets the user build a particle accelerator channel in 3D with or without using code. The channel may then be saved, exported, translated, or run. Any output data will be plotted in Beamline Architect using Python, since it is both flexible aesthetically and quite standard in the particle accelerator community. For undergraduate and non-accelerator students, Beamline Architect allows a hands-on experience with accelerator simulations. Some applications for these students include health physics radiation dosimetry problems, medical imaging mechanics, security scanner simulations, and (of course) accelerator channel design for particle physics experiments. For experts, Beamline Architect provides visual confirmation of the channel and a faster, more consistent way of cross-referencing results between the codes.
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-WEPAF003  
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WEPAF009 Optimising Response Matrix Measurements for LOCO Analysis 1826
  • Y.E. Tan
    AS - ANSTO, Clayton, Australia
  The Linear Optics from Closed Orbit (LOCO) method is a common tool for determining storage ring lattice functions and requires a measured BPM to Corrector response matrix. For very large rings with many correctors, such measurements can be time consuming. The following study investigates how the number of correctors and the signal-to-noise ratio (SNR) affects the LOCO analysis results. For the Australian Synchrotron, the results show that four distributed correctors per plane with a SNR of >1000 is sufficient to fit the betatron functions to an accuracy of less than 0.2%.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-WEPAF009  
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WEPAF022 Application of Machine Learning to Minimize Long Term Drifts in the NSLS-II Linac 1867
  • R.P. Fliller, C. Gardner, P. Marino, R.S. Rainer, M. Santana, G.J. Weiner, X. Yang, E. Zeitler
    BNL, Upton, Long Island, New York, USA
  Funding: This manuscript has been authored by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy
Machine Learning has proven itself as a useful technique in a variety of applications from image recognition to playing Go. Artificial Neural Networks have certain advantages when used as a feedforward system, such as the predicted correction relies on a model built from data. This allows for the Artificial Neural Network to compensate for effects that are difficult to model such as low level RF adjustments to compensate for long term drifts. The NSLS-II linac suffers from long terms drifts from a number of sources including thermal drifts and klystron gain variations. These drifts have an effect on the injection efficiency into the booster, and if left unchecked, portions of the bunch train may not be injected into the booster, and the storage ring bunch pattern will ultimately suffer. In this paper, we discuss the application of Artificial Neural Networks to compensate for long term drifts in the NSLS-II linear accelerator. The Artificial Neural Network is implemented in python allowing for rapid development of the network. We discuss the design and training of the network, along with results of using the network in operation.
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-WEPAF022  
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WEPAF030 HEPS High-Level Software Architecture Plan 1884
  • C.P. Chu, Y.S. Qiao, C.H. Wang
    IHEP, Beijing, People's Republic of China
  • H.H. Lv
    SINAP, Shanghai, People's Republic of China
  Funding: Work supported by the Chinese Academy of Science and the HEPS-TF Project.
The High Energy Photon Source (HEPS) is a planned ultra-low emittance synchrotron radiation based light source which requires high precession control systems for both accelerator and beamlines. Such kind of accelerators will require extremely sophisticated high-level control software for both accelerator and beamline operation to achieve not only the demanded precision but also high reliability. This paper outlines the high-level application software architecture design including relational data-bases, software platforms, and advanced controls with machine learning (ML) techniques. Early plan for beam-line control is also reported. For better quality control and easy maintenance, the high-level applications will be built upon matured software platforms. Also, the HEPS High-Level Software team will collaborate with EPICS community for improving the software platforms.
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-WEPAF030  
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WEPAF041 Use of Dimension-Reduction Techniques With Multi-Objective Genetic Algorithms to Improve the Vertical Emittance and Orbit at CESR 1901
SUSPL064   use link to see paper's listing under its alternate paper code  
  • W.F. Bergan, I.V. Bazarov, C.J. Duncan, D. L. Rubin
    Cornell University (CLASSE), Cornell Laboratory for Accelerator-Based Sciences and Education, Ithaca, New York, USA
  • D. Liarte, J.P. Sethna
    Cornell University, Ithaca, New York, USA
  Funding: DOE DE-SC0013571 NSF DGE-1650441
In order to reduce the vertical emittance at the Cornell Electron Storage Ring (CESR), we first measure and correct the vertical orbit, dispersion, and coupling. However, due to the finite resolution of our optics measurements, we still retain a significant residual emittance. In order to correct this further, we made use of the theory of sloppy models, according to which certain high-dimensionality systems can be modeled with significantly fewer "eigenparameters" that still contain most of the effect on the desired objective, in this case, the emittance.* However, we noted that using these knobs for tuning often resulted in increased vertical orbit errors. In an attempt to constrain these, we have applied multi-objective genetic algorithms to this problem. We have found that it can be more efficient to run such algorithms using our eigenparameters as the genes to be varied, as opposed to the raw magnet values. When running with the first 8 such knobs as genes, we can get either orbits or beam sizes as good as we obtain with our regular emittance-tuning algorithm which uses all the corrector magnets.
*K.S. Brown and J.P. Sethna, Phys. Rev. E 68, 021904 (2003).
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-WEPAF041  
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WEPAF044 Automatic Tuning of PETRA, its Injector Complex, and Prospects of Autonomous Operation of PETRA IV 1912
  • I.V. Agapov, H. Ehrlichmann, J. Keil, G.K. Sahoo, R. Wanzenberg
    DESY, Hamburg, Germany
  • Y.-C. Chae
    ANL, Argonne, Illinois, USA
  We present the progress in tuning automation of the PETRA injection complex. The OCELOT optimizer has been ported to the PETRA control system and proof-of-principle tests of transmission efficiency optimization done. We further argue that the next steps in tuning and automation are impossible without rethinking the architecture of the high level contol system. A possible approach to the new system is then sketched.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-WEPAF044  
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WEPAF062 Machine Learning Methods for Optics Measurements and Corrections at LHC 1967
  • E. Fol, F.S. Carlier, J.M. Coello de Portugal, A. Garcia-Tabares, R. Tomás
    CERN, Geneva, Switzerland
  The application of machine learning methods and concepts of artificial intelligence can be found in various industry and scientific branches. In Accelerator Physics the machine learning approach has not found a wide application yet. This paper is devoted to evaluation of machine learning methods aiming to improve the optics measurements and corrections at LHC. The main subjects of the study are devoted to recognition and analysis of faulty beam position monitors and prediction of quadrupole errors using clustering algorithms, decision trees and artificial neural networks. The results presented in this paper clearly show the suitability of machine learning methods for the optics control at LHC and the potential for further investigation on appropriate approaches.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-WEPAF062  
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WEPAF078 Machine Learning Applied at the LHC for Beam Loss Pattern Classification 2020
  • G. Valentino
    University of Malta, Information and Communication Technology, Msida, Malta
  • B. Salvachua
    CERN, Geneva, Switzerland
  Beam losses at the LHC are constantly monitored because they can heavily impact the performance of the machine. One of the highest risks is to quench the LHC superconducting magnets in the presence of losses leading to a long machine downtime in order to recover cryogenic conditions. Smaller losses are more likely to occur and have an impact on the machine performance, reducing the luminosity production or reducing the lifetime of accelerator systems due to radiation effects, such as magnets. Understanding the characteristics of the beam loss, such as the beam and the plane, is crucial in order to correct them. Regularly during the year, dedicated loss map measurements are performed in order to validate the beam halo cleaning of the collimation system. These loss maps have the particular advantage that they are performed in well controlled conditions and can therefore be used by a machine learning algorithm to classify the type of losses during the LHC machine cycle. This study shows the result of the beam loss classification and its retrospective application to beam loss data from the 2017 run.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-WEPAF078  
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WEPAF086 Latest Developments and Updates of the ESS Linac Simulator 2051
  • J.F. Esteban Müller, E. Laface
    ESS, Lund, Sweden
  A fast and accurate online model is required for optimal commissioning and reliable operation of the high-power proton linac at the European Spallation Source. The Open XAL framework, initially developed at SNS, is used at ESS for the development of high-level physics applications. The online model we use, known as ESS Linac Simulator (JELS), extends the Open XAL model with several features. This paper describes the latest updates carried out to JELS. Two new elements have been implemented: a solenoid field map for the LEBT and a DTL Tank element that automatically calculates each gap phase. All calculations are now done in the laboratory frame, in agreement with Open XAL convention. A thorough benchmark of the model against TraceWin, which is the tool used for the lattice design, is also presented.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-WEPAF086  
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WEPAL047 Online Optimisation of the MAX IV 3 GeV Ring Dynamic Aperture 2281
SUSPL065   use link to see paper's listing under its alternate paper code  
  • D.K. Olsson
    MAX IV Laboratory, Lund University, Lund, Sweden
  In order to improve the resilience of the MAX IV 3 GeV ring's beam to a horizontal dipole kick while at the design tunes (42.20, 16.28) the optimisation algorithm RCDS (Robust Conjugate Direction Search) was deployed. The algorithm was able to increase the horizontal acceptance by finding new settings for the sextupole and octupole magnets, whilst leaving the vertical acceptance virtually unchanged. Additionally, the optimisation increased the momentum acceptance of the lattice, increasing beam lifetime.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-WEPAL047  
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WEPAL055 TPS Beam Trip Analysis and Dose Distribution 2302
  • B.Y. Chen, F.Y. Chang, S. Fann, C.S. Huang, C.H. Kuo, T.Y. Lee, C.C. Liang, W.Y. Lin, Y.C. Lin, Y.-C. Liu
    NSRRC, Hsinchu, Taiwan
  Failure analysis during TPS users operation is im-portant to improve the performance of the TPS storage ring. In this report, we discuss the particular radiation dose patterns, relevant to different beam trips, and the development of a tool to help us analyse this dose distri-bution. We will use this analysing tool to train our ability for future failure analysis to shorten the time it takes to find the problem.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-WEPAL055  
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WEPAL064 Diagnosis Application by Great Amount Operation Data Analysis Program for Taiwan Photon Source 2323
  • C.C. Liang, B.Y. Chen, C.H. Chen, S. Fann, C.S. Huang, C.H. Kuo, T.Y. Lee, W.Y. Lin, Z.-D. Tsai, Y.C. Yang, T.-C. Yu
    NSRRC, Hsinchu, Taiwan
  To find out abnormal situations of the machine for preventive maintenance or machine trip tracking or instability source diagnosis, a large amount of operating data in an accelerator is thus can be used to build a series data analysis program. When the archived data is classified accordingly, the standard deviation (STD), peak-to-peak value and other statistic indexes within the inspection time zone by the belonging families can be used to point out the especially abnormal signals. The analysis program adopts the techniques of parallel calculation and memory optimization to greatly reduce the time for data transmission and analysis and also displays the correlation signals to opera-tors for deeper analysis. This paper illustrated a simple yet effective method for quickly identifying a not-so-obscure hardware issue by simply using a personal computer (PC).  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-WEPAL064  
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THPML028 Genetic Algorithms for Machine Optimization in the Fair Control System Environment 4712
  • W. Geithner, Z. Andelkovic, S. Appel, O. Geithner, F. Herfurth, S. Reimann, G. Vorobjev
    GSI, Darmstadt, Germany
  • F. Wilhelmstötter
    emarsys, Vienna, Austria
  Due to the massive parallel operation modes at the GSI accelerators, a lot of accelerator setup and re-adjustment have to be made by the operators during a beam time. With the FAIR project the complexity of the accelerator facility increases furthermore and for efficiency reasons it is recommended to establish a high level of automation for future operation. The PEP (parameter evolution project) has been launched at GSI operations group in 2017 to investigate the potential of a settings optimization using evolutionary Algorithms. The working proof of principle has already been tested at the Cryring injector. The latest improvements and the further Development of the Parameter Evolution Project will be shown.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-THPML028  
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THPML078 Web-Based Control Room Applications at TRIUMF 4832
  • C.B. Barquest, P. M. Jung, S. Kiy, K.E. Lucow, T. Planche, S.D. Rädel, B.E. Schultz, D. Sehayek, O. Shelbaya, D. Tattan
    TRIUMF, Vancouver, Canada
  • M. Corwin, S. Marcano
    UW/Physics, Waterloo, Ontario, Canada
  Control room applications are programs that interface with control systems and beam physics models. These tools range from real-time diagnostic visualizations to post-processing data analysis. At TRIUMF, the concept of web-based control room applications has been adopted to advance the capabilities of these applications and facilitate operations. This online model takes advantage of server-based continuous integration and a centralized middleware layer. Continuous integration of server-based applications allows for easy deployment and maintenance. A centralized middleware layer allows a single application to work for many different accelerator configurations. Some motivating examples of web-based applications currenly being developed are presented, demonstrating this online approach to be an effective method for deploying applications for use in the control room and beyond.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-THPML078  
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THPML079 Multipole Tuning Algorithm for the CANREB HRS at TRIUMF 4836
  • D. Sehayek, R.A. Baartman, C.B. Barquest, J.A. Maloney, M. Marchetto, T. Planche
    TRIUMF, Vancouver, Canada
  The TRIUMF CANadian Rare isotope facility with Electron Beam ion source (CANREB) High Resolution Separator (HRS) has been designed to separate rare isotopes with mass/charge differences of only one part in 20,000 for beams with transverse emittances of 3 μm. To reach this resolution, high-order aberrations must be corrected using a multipole corrector. From experience, tuning such a multipole is very challenging. The unique geometry of our multipole motivated a novel tuning method based on determining the desired pole voltages directly from measured emmitance. This novel tuning algorithm is presented alongside a web application which has been developed in anticipation of the commissioning of the HRS.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-THPML079  
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THPML084 Validating the COBEA Algorithm at the DELTA Storage Ring 4851
  • B. Riemann, B.D. Isbarn, S. Khan, S. Koetter, T. Weis
    DELTA, Dortmund, Germany
  Closed-Orbit Bilinear-Exponential Analysis (COBEA) is an algorithm to decompose monitor-corrector response matrices into (scaled) beta optics values, phase advances, scaled dispersion and betatron tunes. No explicit magnetic lattice model is required for COBEA - only the sequence of monitors and correctors along the beam path (no lengths, no strengths approach). To obtain absolute beta values, the length of one drift space can be provided as optional input. In this work, the application of COBEA to the DELTA storage ring, operated by TU Dortmund University, is discussed, and its results for betatron tunes and scaled dispersion are compared with those of conventional, direct measurement methods. COBEA is also put in a historical perspective to other diagnostic algorithms. Improvements in the Python implementation of COBEA, which is available as free software, are presented. Due to COBEA being relatively modest regarding its requirements on input data respectively hardware, it should be applicable to the majority of existing storage rings.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-THPML084  
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THPML094 New Methods for Dispersion Measurement and Correction for 12 GeV CEBAF 4882
  • D.L. Turner
    JLab, Newport News, Virginia, USA
  Funding: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under contract DE-AC05-06OR23177.
This paper discusses methods for dispersion measurement and correction for the Continuous Electron Beam Accelerator Facility (CEBAF) for the 12GeV era. New methods will be compared with methods used during the 6GeV era. New software tools which implement the new methods will be discussed, along with a method for automating dispersion measurement and correction. New dispersion measurement and correction methods and tools are being implemented to provide more deterministic results and to reduce machine setup time.
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-THPML094  
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THPML116 AutoTuner: A General Graphical User Interface for Automated Tuning 4939
  • X. Huang
    SLAC, Menlo Park, California, USA
  • T. Zhang
    USTC/NSRL, Hefei, Anhui, People's Republic of China
  AutoTuner is a general graphical user interface (GUI) that we developed for automated tuning or online optimization. The GUI provides a convenient interface to select tuning knobs, objectives, and optimization algorithms and to change the tuning control parameters. Tuning setup can be created and saved for reuse. The progress of the tuning processing is plotted in real time. The tuning process can be paused, aborted, or resumed. We have tested the program for real-life accelerator tuning problems.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2018-THPML116  
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