Hosted by Brookhaven National Laboratory
October 5 - 11
New York, NY
17th Biennial International Conference on Accelerator
and Large Experimental Physics Control Systems

ICALEPCS 2019 Tracks

 Project Status Reports
 Control System Upgrades
 Device Control and Integrating Diverse Systems
 Experiment Control
 Software Technology Evolution
 User Interfaces, User Perspective, and User Experience(UX)
 Data Management
 Data Analytics
 Hardware Technology
 Timing and Synchronization
 Control System Infrastructure
 Systems Engineering, Collaborations, Project Management
 Functional Safety Systems for Machine Protection, Personnel Safety
 Feedback Control and Process Tuning


Project Status Reports

This track presents an overview of new or upgraded experimental physics facilities from a control system perspective. Project Status Reports typically cover the stages of a project from the conceptual design through commissioning. Presentations should include descriptions of the most challenging controls issues facing the facility. Projects with novel, complex and/or very demanding control system requirements are strongly encouraged.

Topics covered in this track include:

  • Reports on control system design and development for facilities such as particle accelerators and detectors, fusion devices, light and photon sources, neutron sources, telescopes, gravitational wave detectors

Keywords: high energy physics (HEP), accelerator, detector, telescope, synchrotron, free electron laser (FEL), neutron, ion, neutrino, spallation, laser, tokamak, therapy, facility design, installation, commissioning, project

Control System Upgrades

This track focuses on upgrades to existing control systems for the purpose of improving sustainability and/or the provision of additional capabilities. Upgrades can include extensions or improvements of control system hardware, software, infrastructure or frameworks. Submissions are encouraged to include management of the change control process and transition of upgraded systems to operations.

Topics covered in this track include:

  • Upgrades to existing control systems
  • Technologies and tools used to facilitate the upgrade process
  • Approach to selection and/or adoption of new technologies, and negotiations with stakeholders
  • Design approach to optimize system flexibility, maintainability and sustainability
  • Strategies for upgrade transitions (e.g. change management, testing, new operational models, new maintenance paradigms, operator training)
  • Risk analysis and mitigation, strategy for minimizing downtime during the transition
  • Lessons learned during the upgrade process
  • Return On Investment (ROI) analysis, with considerations on Total Cost of Ownership (TCO) models

Keywords: Legacy systems, upgrade, obsolete, maintainability, long-term support, shutdown periods, operations, risk analysis and mitigation, strategy, change management

Device Control and Integrating Diverse Systems

Large-scale experimental control systems are frequently built from the aggregation of many heterogeneous components comprised of in-house and commercial off-the-shelf systems. Component selection is driven by decisions of technical requirements, industrial standards, institutional policy, community best practices, and financial or resource considerations.

This track aims to present the experiences, issues and lessons learned related to the design, construction and evolution of diverse control system elements and their integration, covering architectures, technologies and methods.

Topics covered in this track include:

  • Design paradigms and technology evolution (e.g. Industrial Internet of Things, interoperability)
  • Control system coupling
  • Low-level control component integration
  • Integrating subsystems (e.g. vacuum, LLRF, power supplies)
  • Customization levels of commercial off-the-shelf components
  • Scalability and real-time performance

Keywords: drivers, scalability, customization, integration, process control, SCADA, PLC, PAC, IPC, industrial communications, fieldbus, smart sensors, alarms, motion control, robotics, digital twin, dynamic simulation, virtual commissioning, fault detection, wireless, system-on-chip, IIoT

Experiment Control

This track focuses on the domain specific control systems and data acquisition for user facility experiments. Experiment control systems must interact with a variety of instrument hardware, sample environment equipment, detectors, data acquisition electronics, and external systems such as accelerators. These control systems must be flexible and easy to use for experiments with quick turnaround and a heterogeneous user community.

Topics covered in this track include:

  • Intelligent systems and automation applications and techniques
  • Interactive and scripting/macro environments for scanning, sequencing and run control (e.g. SPEC, GDA, CSS, Sardana, Bluesky, BLISS)
  • Sample environment control including robotic sample changers
  • User interfaces and remote monitoring and access
  • Live feedback and on-line data reduction (e.g. on-line reduction of large waveform or image data to figures of merit) and visualization
  • Detector and data acquisition (e.g. Lima, areaDetector)
  • User information systems and databases

Keywords: intelligent systems, automation, macros, scan, metadata, remote operation, data acquisition, macro environment, sequencer, image acquisition, data reduction, data visualization, detectors, pixel array detector, CCD


Software Technology Evolution

This track covers new and/or innovative software technologies used to build control systems. Of particular interest is experience gained and lessons learned from applying new approaches in practical software development.

Topics covered in this track include:

  • New control system frameworks and evolution of existing control system toolkits (e.g. EPICS, TANGO, DOOCS, ACS)
  • Reports on performance and scalability of middleware technology and the usage of web services and service-oriented architecture (SOA) (e.g. ZeroMQ, ActiveMQ, DDS, Kafka, NATS, ReactiveX)
  • Advances in software development techniques including new programming languages, design and code for easy debugging, refactoring in practice, model-driven development, test-driven development, domain-specific languages and code generation, and/or new operating systems or extensions

Note: GUI toolkits, web tools and integration of low and high-level components are covered in other tracks.

Keywords: Middleware, control system frameworks, web-services, SCADA

User Interfaces, User Perspective and User eXperience (UX)

This track focuses on how human beings interact with computer-based systems. This includes the user perspective, what humans expect from their experience, how humans control hardware as well as how humans interact with user interfaces

Topics covered in this track include:

  • User perspective and ease of use
  • User-oriented design
  • UX (User eXperience)
  • Style guides, look and feel
  • Interface building toolkits (e.g. CSS, JDDD, Taurus, ATK) and programming languages
  • Web interfaces and applications
  • Data visualization tools
  • Reporting tools
  • Mobile device development to enable remote operation and monitoring
  • Emerging interface trends

Keywords: GUI (Graphical User Interface), data visualization, synoptic, plotting, archive viewers, dashboards, web frameworks, touch screens, CLI (Command Line Interfaces), mobile apps, electronics logbooks, alarm handlers, intelligent data display, virtual displays, augmented reality, voice control

Data Management

This track aims to collect contributions that focus on management of scientific, operations, and engineering data; policies (e.g. open data) and processes, infrastructure for staging and managing, monitoring the management systems, and remote data handling. This includes issues arising from the storage, processing, indexing, search, and retrieval of datasets as well as metadata related to samples, experiments, processes and publications.

Topics covered in this track include:

  • Data Governance
  • Data formats, metadata systems, ontologies
  • Distributed database management
  • Public and private clouds
  • High performance data storage systems
  • Hardware and software architectures, network and tools for scientific data management
  • Laboratory Information Management Systems
  • Data Architecture (standards, data model)
  • Data Quality (integrity, quality, QA)
  • Master Data (integration, reference, replication, criticality, reduction)
  • Data Warehousing (mining, extraction, transform, deploy)
  • Best Practices

Note: Technology should be cited that supports the data management application and its benefit to this field. Installation and management of IT infrastructure (not related to data management) is covered in 'Control System Infrastructure'. Data interpretation and detailed descriptions of algorithms is covered in 'Data Analytics'.

Keywords: cloud computing, metadata catalogues, open access, data standards, data models, preservation, scrubbing, shaping, decimation and culling, data tiers, restrictions, data security, SQL, NoSQL, Multi-Platform, edge, replication

Data Analytics

This track focuses on interpreting and examining datasets. This includes scientific data analysis, uncovering hidden patterns, correlations and other insights from different data sources. Use cases can cover experiment types, the plants under control, or the control systems themselves. Data can be analyzed online, offline or in a combination of both. Analytics also favors data visualization to communicate insights, inferring conclusions and representing the results in a comprehensible form.

Topics covered in this track include:

  • Scientific Data Modeling
  • Analytics ecosystems (e.g. Hadoop), frameworks (e.g. Spark)
  • Data mining (e.g. ElasticSearch)
  • NoSQL and time series databases (e.g. Cassandra, MongoDB)
  • Predictive analytics.
  • Machine learning.
  • Statistics, and statistical models.
  • Dependability.
  • Risk, Bayes analysis.
  • Real time analytics.
  • Searching and retrieval.

Note: Online Analysis might better fit the tracks 'Experiment Control' or 'Feedback Control', data formats and metadata the track 'Data Management', and experiment simulation the track 'Integrating Diverse Systems'.

Keywords: data analysis, analytics, Kaggle, Tensorflow, NoSQL, big data, notebooks.


Hardware Technology

This track focuses on hardware design as applied to the operation of large physics facilities, with an emphasis on collaborative efforts among laboratories and companies using Open Source Hardware practices

Topics covered in this track include:

  • Hardware platforms: microTCA.4, xTCA, FMC, VME, VXS, VPX, PCI/PCIe, PXI/PXIe, Network Attached Devices (NAD)
  • Printed circuit board (PCB) design
  • Programmable logic design, System-on-Chip (SoC) design, including embedded processors and interconnects in Field Programmable Gate Arrays (FPGA)
  • Hardware/software co-design
  • Hardware and gateware simulation, verification and testing
  • Data links for distributed controls and data acquisition
  • Radiation-hardened design
  • Collaborative design tools
  • Reliability and Electromagnetic Compatibility (EMC), availability and redundancy
  • Integrated self-diagnostics
  • Upgrade and maintenance strategies and life cycle management

Keywords: xTCA, FMC, VME, PCI, PCIe, PCB, FPGA, HDL, SoC, EMC, Open

Timing and Synchronization

This track focuses on timing and synchronization challenges in particle and light beams, interferometry, data acquisition or pump-probe configurations. Submissions to this track should demonstrate the way precision, stability or jitter of the systems are managed to fulfill system requirements.

Topics covered in this track include:

  • Architectures for timing distribution
  • Timing protocols such as NTP, PTP, or IEEE 802.1AS
  • Timing systems such as MRF, Greenfield or White Rabbit
  • Facility specific timing systems and protocols
  • Methods for transmission delay compensation
  • Solutions for extremely high precision (sub-picosecond) timing requirements
  • Beam synchronous trigger techniques for Data Acquisition

Keywords: Synchronization, NTP, PTP, MRF, White Rabbit, Delay Compensation, Event Systems, Distributed Clock Systems, beam synchronous triggering, pump-probe, timestamp

Control Systems Infrastructure

This track addresses the IT infrastructure of networks, processing nodes, data storage systems and database architecture used in Controls Systems. This includes cloud computing solutions as well as a special focus on cyber security as it is becoming a major issue in our facilities.

Topics covered in this track include:

  • Ethernet networks, VLAN, switches, topology and administration
  • Data center design and architectures including power management and cooling
  • Storage systems architectures, files systems, hierarchical storage management
  • Database engines
  • High performance computing
  • Application hosting: virtualization, container management, orchestration
  • Configuration management and code deployment, patch management and security, software installation methods and tools for distributed processors
  • Disaster recovery strategy, vulnerability management
  • Remote access, related security measures, intrusion detection and prevention
  • Monitoring infrastructure (Security Operations Center, log analysis)

Keywords: Operating Systems and Proprietary Operating Systems, Hypervisors, Containers, Orchestration, Virtual Machines, HPC, Network, Switches, Multi-Core Processor, TCP/IP, VPN, Firewall, VLAN, Backup, Storage, Cybersecurity


Systems Engineering, Collaborations, Project Management

This track focuses on project management and collaboration techniques; including the tools, processes and analytics used to effectively support facility operations and maintenance, and accomplish complex engineering projects over full life cycles.

Topics covered in this track include:

  • Systems engineering and design of complex systems
  • Risk management (identification, evaluation, prioritization, and tracking) in design, construction and commissioning processes
  • Requirements and interface management (defining, controlling, and communicating the information)
  • Validation and verification techniques
  • Collaborative processes and tools (e.g. teleconferencing, social media, joint document creation and sharing) enabling effective interactions between diverse institutes and countries
  • Shared, collaborative and distributed leadership
  • Processes and analytics to efficiently support the operations & maintenance of an existing facility (e.g. data driven maintenance)
  • Lessons learned through project lifecycle phases and their application in future projects
  • Team building in diverse and/or multicultural environments
  • Scope, schedule, budget, and quality assurance management techniques
  • System engineering and project management tools
  • Leadership, management and coaching of people
  • Human factors such as diversity at the work place and work-life balance
  • Educating and attracting the next generation of controls engineers

Keywords: systems engineering, risk management, project management, quality assurance, integration, collaborative tools, operational support, human factors, diversity, education, succession planning

Functional Safety Systems for Machine Protection, Personnel Safety

This track presents the role and implications of functional safety systems. This includes machine protection systems used for the protection of equipment, personnel safety systems used for the protection of people, and patient protection systems to protect people where radiation is used in medical diagnosis and treatment.

Topics covered in this track include:

  • Choice and application of standards: this considers the selection of international standards for functional safety, and their application in the specification, design and life cycle of such systems
  • Aspects of functional safety such as specification, design, implementation and commissioning processes (e.g. FMEA's) along with interlock considerations, interactions with other facility control systems, required reliability, machine up-time, availability and maintainability
  • Operational experience and lessons learned such as assessment of failures, including potential failures in safety systems and what can be learned. Additionally, evaluation of incorrect specifications, omitted safety requirements, random hardware failures, systematic hardware failures, software errors, common cause failures and environmental influences
  • Human factors as it pertains to how the man/machine interface contributes positively to successful, reduced-risk operation and ease of use

Keywords: PSS, EPS, MPS, PLC, SIL, radiation protection, risk analysis, safety PLCs, relays, interlock, operation permits, patient safety, human factors.

Feedback Control and Process Tuning

Modern experimental physics facilities are very complex machines that cannot be operated without the use of sophisticated systems to automate tasks where manual management by physicists or operators is not reasonable or possible.

Examples are optimization tools for tuning and improving machine performance, as well as feedback/feed-forward systems assuring the stability of critical parameters during operation. In some cases these systems require dedicated real-time platforms with deterministic communication capabilities perhaps employing parallel processing techniques using GPUs or FPGAs.

Of particular interest are systems featuring human-like capabilities, able to learn and adapt to different situations. These systems can benefit from the acquired knowledge and gained experience to understand behaviors and recognize phenomena, and eventually support humans in solving complex problems.

Topics covered in this track include:

  • Software or hardware feedback and feed-forward systems
  • Use of models and simulators
  • Predictive and adaptive correction systems
  • Automatic tuning and optimization techniques, multi objective optimization, genetic algorithms
  • Artificial intelligence, expert systems, machine learning, neural networks

Keywords: feedback, feed forward, model, simulation, predictive correction, adaptive correction, automatic tuning, automatic optimization, genetic algorithm, predictive and adaptive correction, artificial intelligence, expert system, machine learning, neural network