Keyword: diagnostics
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MOAL02 Status of the National Ignition Facility (NIF) Integrated Computer Control and Information Systems controls, laser, target, experiment 9
  • M. Fedorov, A.I. Barnes, L. Beaulac, G.K. Brunton, A.D. Casey, J.R. Castro Morales, J. Dixon, C.M. Estes, M.S. Flegel, V.K. Gopalan, S. Heerey, R. Lacuata, V.J. Miller Kamm, M. Paul, B.M. Van Wonterghem, S. Weaver
    LLNL, Livermore, California, USA
  Funding: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344
The National Ignition Facility (NIF) is the world’s most energetic laser system used for Inertial Confinement Fusion (ICF) and High Energy Density Physics (HEDP) experimentation. Each laser shot delivers up to 1.9 MJ of ultraviolet light, driving target temperatures to in excess of 180 million K and pressures 100 billion times atmospheric ’ making possible direct study of conditions mimicking interiors of stars and planets, as well as our primary scientific applications: stockpile stewardship and fusion power. NIF control and diagnostic systems allow physicists to precisely manipulate, measure and image this extremely dense and hot matter. A major focus in the past two years has been adding comprehensive new diagnostic instruments to evaluate increasing energy and power of the laser drive. When COVID-19 struck, the controls team leveraged remote access technology to provide efficient operational support without stress of on-site presence. NIF continued to mitigate inevitable technology obsolescence after 20 years since construction. In this talk, we will discuss successes and challenges, including NIF progress towards ignition, achieving record neutron yields in early 2021.
slides icon Slides MOAL02 [5.014 MB]  
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About • Received ※ 10 October 2021       Accepted ※ 30 November 2021       Issue date ※ 24 February 2022  
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MOPV020 Digitisation of the Analogue Waveform System at ISIS controls, Linux, timing, real-time 169
  • W.A. Frank, B.R. Aljamal, R.A. Washington
    STFC/RAL/ISIS, Chilton, Didcot, Oxon, United Kingdom
  Funding: UKRI/STFC
The Analogue Waveform System (AWS) at the ISIS Neutron and Muon Source is a distributed system that allows operators to select and monitor analogue waveforms from equipment throughout the facility on oscilloscopes in the Main Control Room (MCR). These signals originate from key accelerator systems in the linear accelerator and synchrotron such as the ion source, magnets, beam diagnostics, and radio frequency (RF) systems. Historical data for ISIS is available on the control system for many relevant channels. However, at present, to avoid disrupting the oscilloscope displays in the MCR, only an hourly image capture of the AWS waveforms is stored. This is largely inadequate for potential data-intensive applications such as anomaly detection, predictive maintenance, post-mortem analysis, or (semi-)automated machine setup, optimization, and control. To address this, a new digital data acquisition (DAQ) system is under development based on the principle of large channel count, simultaneous DAQ. This paper details the proposed architecture of the system and the results of initial prototyping, testing, and commissioning.
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About • Received ※ 08 October 2021       Revised ※ 21 October 2021       Accepted ※ 16 December 2021       Issue date ※ 04 February 2022
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TUPV016 Design and Development of the New Diagnostics Control System for the SPES Project at INFN-LNL controls, hardware, EPICS, emittance 428
  • G. Savarese, G. Arena, D. Bortolato, F. Gelain, D. Marcato, V. Martinelli, E. Munaron, M. Roetta
    INFN/LNL, Legnaro (PD), Italy
  The need to get finer data to describe the beam is a relevant topic for all laboratories. For the SPES project at Laboratori Nazionali di Legnaro (LNL) a new diagnostic control system with more performing hardware, with respect to the one used in legacy accelerators based on Versabus Module Eurocard (VME) ADCs, has been developed. The new system uses a custom hardware to acquire signals in real time. These data and ancillary operations are managed by a control system based on the Experimental Physics and Industrial Control System (EPICS) standard and shown to users on a Control System Studio (CSS) graphical user interface. The new system improves the basic functionalities, current read-back over Beam Profilers (BP) and Faraday Cups (FC) and handlings control, with new features such as: multiple hardware gain levels selection, broken wires correction through polynomial interpolation and roto-translations taking into account alignment parameters. Another important feature, integrated with the usage of a python Finite State Machine (FSM), is the capability to control an emittance meter to quickly acquire data and calculate beam longitudinal phase space through the scubeex method.  
poster icon Poster TUPV016 [2.235 MB]  
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About • Received ※ 28 September 2021       Revised ※ 02 November 2021       Accepted ※ 20 November 2021       Issue date ※ 08 March 2022
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TUPV028 The Control and Archiving System for the Gamma Beam Profile Station at ELI-NP controls, EPICS, GUI, software 450
  • G. Chen, V. Iancu, C. Matei, F. Ramirez, G. Turturica
    IFIN-HH, Bucharest - Magurele, Romania
  The Variable Energy Gamma (VEGA) System of Extreme Light Infrastructure - Nuclear Physics (ELI-NP) is based on the Inverse Compton Scattering of laser light on relativistic electron bunches provided by a warm radio-frequency accelerator. The system will deliver quasi-monochromatic gamma-ray beams with a high spectral density and a high degree of linear polarization. The Beam Profile Station, which will be used for ’ner target alignment and spatial characterization of the gamma-ray beam, is one of the diagnostics stations under implementation at ELI-NP. An EPICS Control and Archiving System (CAS) has been developed for the Beam Profile Station at ELI-NP. This paper describes the design and the implementation of the EPICS CAS for the Beam Profile Station, including the device modular integration of the low-level IOCs for the CCD camera Trius-SX674 and Mclennan PM600 Stepper Motor Controller, the design of the high-level GUI for real-time image acquisition and motion control, as well as the configuration of the archiving system for browsing the historic images and parameters.
* The work is supported by ELI-NP Project (
poster icon Poster TUPV028 [0.782 MB]  
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About • Received ※ 08 October 2021       Revised ※ 13 January 2022       Accepted ※ 25 January 2022       Issue date ※ 06 February 2022
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WEPV020 Learning to Lase: Machine Learning Prediction of FEL Beam Properties network, simulation, FEL, electron 677
  • A.E. Pollard, D.J. Dunning
    STFC/DL/ASTeC, Daresbury, Warrington, Cheshire, United Kingdom
  • M. Maheshwari
    STFC/DL, Daresbury, Warrington, Cheshire, United Kingdom
  Accurate prediction of longitudinal phase space and other properties of the electron beam are computationally expensive. In addition, some diagnostics are destructive in nature and/or cannot be readily accessed. Machine learning based virtual diagnostics can allow for the real-time generation of longitudinal phase space and other graphs, allowing for rapid parameter searches, and enabling operators to predict otherwise unavailable beam properties. We present a machine learning model for predicting a range of diagnostic screens along the accelerator beamline of a free-electron laser facility, conditional on linac and other parameters. Our model is a combination of a conditional variational autoencoder and a generative adversarial network, which generates high fidelity images that accurately match simulation data. Work to date is based on start-to-end simulation data, as a prototype for experimental applications.  
poster icon Poster WEPV020 [1.330 MB]  
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About • Received ※ 10 October 2021       Revised ※ 22 October 2021       Accepted ※ 28 December 2021       Issue date ※ 25 February 2022
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WEPV026 Multi-Channel Heaters Driver for Sirius Beamline’s Optical Devices controls, synchrotron, hardware, experiment 705
  • M.M. Donatti, D.H.C. Araujo, F.H. Cardoso, G.B.Z.L. Moreno, L. Sanfelici, G.T. Semissatto
    LNLS, Campinas, Brazil
  Thermal management of optomechanical devices, such as mirrors and monochromators, is one of the main bottlenecks in the overall performance of many X-Rays beamlines, particularly for Sirius: the new 4th generation Brazilian synchrotron light source. Due to high intensity photon beams some optical devices need to be cryogenically cooled and a closed-loop temperature control must be implemented to reduce mechanical distortions and instabilities. This work aims to describe the hardware design of a multi-channel driver for vacuum-ready ohmic heaters used in critical optical elements. The device receives PWM signals and can control up to 8 heaters individually. Interlocks and failure management can be implemented using digital signals input/outputs. The driver is equipped with a software programmable current limiter to prevent load overheating and it has voltage/current diagnostics monitored via EPICS or an embedded HTTP server. Enclosed in a 1U rack mount case, the driver can deliver up to 2A per channel in 12V and 24V output voltage versions. Performance measurements will be presented to evaluate functionalities, noise, linearity and bandwidth response.  
poster icon Poster WEPV026 [2.174 MB]  
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About • Received ※ 09 October 2021       Accepted ※ 21 November 2021       Issue date ※ 06 December 2021  
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THAL04 Machine Learning Based Tuning and Diagnostics for the ATR Line at BNL quadrupole, network, simulation, controls 803
  • J.P. Edelen, K. Bruhwiler, E.G. Carlin, C.C. Hall
    RadiaSoft LLC, Boulder, Colorado, USA
  • K.A. Brown, V. Schoefer
    BNL, Upton, New York, USA
  Funding: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Award Number DE-SC0019682.
Over the past several years machine learning has increased in popularity for accelerator applications. We have been exploring the use of machine learning as a diagnostic and tuning tool for transfer line from the AGS to RHIC at Brookhaven National Laboratory. In our work, inverse models are used to either provide feed-forward corrections for beam steering or as a diagnostic to illuminate quadrupole magnets that have excitation errors. In this talk we present results on using machine learning for beam steering optimization for a range of different operating energies. We also demonstrate the use of inverse models for optical error diagnostics. Our results are from studies that use combine simulation and measurement data.
slides icon Slides THAL04 [4.845 MB]  
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About • Received ※ 10 October 2021       Revised ※ 22 October 2021       Accepted ※ 06 February 2022       Issue date ※ 01 March 2022
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THPV041 Innovative Methodology Dedicated to the CERN LHC Cryogenic Valves Based on Modern Algorithm for Fault Detection and Predictive Diagnostics cryogenics, controls, operation, experiment 959
  • M. Pezzetti, A. Amodio, Y. Donon, L. Iodice
    CERN, Geneva, Switzerland
  • P. Arpaia
    Naples University Federico II, Science and Technology Pole, Napoli, Italy
  • F. Gargiulo
    University of Naples Federico II, Naples, Italy
  The European Organization for Nuclear Research (CERN) cryogenic infrastructure is composed of many equipment, among them there are the cryogenic valves widely used in the Large Hadron Collider (LHC) cryogenic facility. At present time, diagnostic solutions that can be integrated into the process control systems, capable to identify leak failures in valves bellows, are not available. The authors goal has been the development of a system that allows the detection of helium leaking valves during normal operation using available data extracted from the control system. The design constraints has driven the development towards a solution integrated in the monitoring systems in use, not requiring manual interventions. The methodology presented in this article is based on the extraction of distinctive features (analyzing the data in time and frequency domain) which are exploited in the next phase of machine learning. The aim is to identify a list of candidate valves with a high probability of helium leakage. The proposed methodology, which is at very early stage now, with the evolution of the data set and the iterative approach is aiming toward a cryogenic valves targeted maintenance.  
poster icon Poster THPV041 [1.120 MB]  
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About • Received ※ 06 October 2021       Revised ※ 26 October 2021       Accepted ※ 22 December 2021       Issue date ※ 02 March 2022
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FRAL01 The Laser MegaJoule Facility Status Report target, laser, experiment, operation 989
  • H. Cortey
    CEA, LE BARP cedex, France
  The Laser MegaJoule (LMJ), the French 176-beam laser facility, is located at the CEA CESTA Laboratory near Bordeaux (France). It is designed to deliver about 1.4 MJ of energy on targets, for high energy density physics experiments, including fusion experiments. The first bundle of 8-beams was commissioned in October 2014. By the end of 2021, ten bundles of 8-beams are expected to be fully operational. In this paper, we will present: - The LMJ Bundles Status report - The main evolutions of the LMJ facility since ICALEPS 2019: the new target diagnostics commissioned and a new functionality to manage final optic damage with the implementation of blockers in the beam. - the result of a major milestone for the project : ‘Fusion Milestone’  
slides icon Slides FRAL01 [7.812 MB]  
DOI • reference for this paper ※  
About • Received ※ 09 October 2021       Revised ※ 01 February 2022       Accepted ※ 22 February 2022       Issue date ※ 01 March 2022
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