Cosylab

The ITER interlock control system (ICS) assumes a crucial role in the tokamak operation to protect the investment against machine protection hazards. Consequently, it must be developed in compliance with the most challenging requirements. The National Instruments CompactRIO (NI cRIO) technology was chosen by ITER as the field-programmable gate array (FPGA)-based platform to develop the investment protection functions, with strict time constraints. This contribution focuses on the specific requirements for the ITER advanced protection system (APS) where the disruption mitigation control function requires a sequenced release of hydrogen ice pellets with an accuracy of less than 1 ms. These requirements are an evolution of previous protection system designs based on CompactRIO (cRIO) and motivated this feasibility study. The cRIO platform used at ITER is the NI9159, which provides an MXIe interface between a Virtex 5 LX110 FPGA and a host computer running a Linux preemptive kernel. ITER decided to improve two important requirements: 1) the MXIe interface communication latency’s jitter by redesigning the ITER National Instruments (NI)-RIO Linux device driver and 2) the ability to timestamp events in the FPGA logic by designing a specific firmware module based on the precision time protocol (PTP) as used in the ITER time communication network (TCN). This contribution reports the design methodology that is followed, the firmware and software elements implemented, and the time-keeping performance obtained from the approach.

The Cherenkov Telescope Array Observatory (CTAO) is the next generation ground-based observatory for gamma-ray astronomy at very-high energies. The CTAO will combine telescopes of different designs plus a large number of scientific instruments to achieve unprecedented performance and energy coverage. The Array Control and Data Acquisition (ACADA) system provides the means to execute observations and to handle the acquisition of scientific data in CTAO. The Resource Manager (RM) and Central Control (CC) subsystems are core components of the ACADA system. The RM subsystem provides infrastructure services concerning the administration of various resources to all ACADA subsystems. The CC subsystem implements the execution of observation requests received from the scheduler subsystem. CC interprets the received requests and sends appropriate commands to telescopes and other controllable array elements, supervises ongoing operations and coordinates the dynamic allocation and management of concurrent operations of telescopes to subarrays, which are logical groupings of individual CTAO telescopes performing coordinated scientific operations. This contribution provides a summary of the main design features, current status and future implementation plans for the ACADA RM and CC subsystems.

The Cooler Synchrotron COSY operated at the Research Center Jülich is undergoing staged machine control upgrades driven by the requirements of the JEDI (Jülich Electric Dipole moment Investigations) collaboration. The upgrades aim towards better beam control e.g. beam orbit, tune, and chromaticity control improvements. A better orbit control was achieved through the upgrade of BPM electronics and migration from initial Tcl/Tk based control system to Control System Studio (CSS) utilizing EPICS. Currently, a design for improved beam tune control is in development. The main part of work is the transition towards a faster and less restrictive magnet control. It further includes improved tune measurement tools as well as the migration of control for quadrupole magnets to EPICS. Ultimately the control of all systems should be centralized around EPICS to enable ease of operation, automation, setup of services, etc. The decision path, technical details of the upgrade and performance of the upgraded sub-systems are presented. We also showcase how the COSY team’s physics and research goals are complemented by Cosylab’s technical design and implementation to form a synergetic collaboration.

The Experimental Physics and Industrial Control System (EPICS), is an open-source software framework for high-performance distributed control, and is at the heart of many of the world’s large accelerators and telescopes. Recently, EPICS has undergone a major revision, with the aim of better computing supporting for the next generation of machines and analytical tools. Many new data types, such as matrices, tables, images, and statistical descriptions, plus users’ own data types, now supplement the simple scalar and waveform types of the former EPICS. New computational architectures for scientific computing have been added for high-performance data processing services and pipelining. Python and Java bindings have enabled powerful new user interfaces. The result has been that controls are now being integrated with modelling and simulation, machine learning, enterprise databases, and experiment DAQs. We introduce this new EPICS (version 7) from the perspective of accelerator physics and review early adoption cases in accelerators around the world.

The first phase of FLUTE, a new linac based test facility and THz source is currently being commissioned at the Karlsruhe Institute of Technology (KIT). It consist of an RF photo gun and a traveling wave linac accelerating electrons to beam energies of 40 to 50 MeV. The control system is based on a virtualized infrastructure running Ubuntu Linux and Linux KVM. As base for the SCADA system we use EPICS 3.15 with Control System Studio (CSS) for the GUI. The long term data storage is provided by a Cassandra NoSQL database. This contribution will present the architecture and the current status of the FLUTE control system.

Python interface to Epics Channel Access

Three-dimensional to two-dimensional (3D-2D) image registration is a key to fusion and simultaneous visualization of valuable information contained in 3D pre-interventional and 2D intra-interventional images with the final goal of image guidance of a procedure. In this paper, the authors focus on 3D-2D image registration within the context of intracranial endovascular image-guided interventions (EIGIs), where the 3D and 2D images are generally acquired with the same C-arm system. The accuracy and robustness of any 3D-2D registration method, to be used in a clinical setting, is influenced by (1) the method itself, (2) uncertainty of initial pose of the 3D image from which registration starts, (3) uncertainty of C-arm's geometry and pose, and (4) the number of 2D intra-interventional images used for registration, which is generally one and at most two. The study of these influences requires rigorous and objective validation of any 3D-2D registration method against a highly accurate reference or "gold standard" registration, performed on clinical image datasets acquired in the context of the intervention. The registration process is split into two sequential, i.e., initial and final, registration stages. The initial stage is either machine-based or template matching. The latter aims to reduce possibly large in-plane translation errors by matching a projection of the 3D vessel model and 2D image. In the final registration stage, four state-of-the-art intrinsic image-based 3D-2D registration methods, which involve simultaneous refinement of rigid-body and C-arm parameters, are evaluated. For objective validation, the authors acquired an image database of 15 patients undergoing cerebral EIGI, for which accurate gold standard registrations were established by fiducial marker coregistration. Based on target registration error, the obtained success rates of 3D to a single 2D image registration after initial machine-based and template matching and final registration involving C-arm calibration were 36%, 73%, and 93%, respectively, while registration accuracy of 0.59 mm was the best after final registration. By compensating in-plane translation errors by initial template matching, the success rates achieved after the final stage improved consistently for all methods, especially if C-arm calibration was performed simultaneously with the 3D-2D image registration. Because the tested methods perform simultaneous C-arm calibration and 3D-2D registration based solely on anatomical information, they have a high potential for automation and thus for an immediate integration into current interventional workflow. One of the authors' main contributions is also comprehensive and representative validation performed under realistic conditions as encountered during cerebral EIGI.