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High Performance Computing platform for predictive interlocks using PLCs at ESS

This paper presents a high performance computing platform using PLCs for predictive interlocks at the European Spallation Source. It discusses the architecture, implementation, and evaluation of the platform.

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High Performance Computing platform for predictive interlocks using PLCs at ESS

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  1. High Performance Computing platform for predictive interlocks using PLCs at ESS Manuel Zaera-Sanz, Annika Nordt ICS - Protection Systems www.europeanspallationsource.se 16-01-29

  2. Table of contents • Introduction and Mission Statement • Target Station at ESS • High Performance Computing platform using PLCs • Conclusions and further work

  3. 1. Introduction and Mission statement • In the last PLC workshop we presented the concept of predictive interlocks and HPC using PLCs, now we show how the HPC platform can be built and a prototype in our PS lab at ESS • Just to remember from our last PLC workshop… • Avoid stopping the machine (or beam) being predictive and taking the proper actions instead of just being reactive => High availability • Minimize machine downtime => Saving cost (equipment & labor) • Issues: • Speed may or may not be an issue: Real-time (deterministic) & High Performance Computing (complex prediction tasks) • Safety is an issue (SIL 3) • Certification could be an issue (needed for Personnel Safety according to IEC-61508, not needed for Machine Protection)

  4. Introduction and Mission statement Mission statement “Design, implement and evaluate HPC architectures using PLCs, able to fulfil safety critical and/or real-time constraints imposed by the machine protection system at ESS” Tools: - Using PLC technology: robustness + safety + real-time • AI software (complex computation) + HPC solution (support platform) AI definition by R. Kurzweil1990, “The art of creating machines that perform functions that require intelligence when performed by people”

  5. 2. European Spallation Source Target Neutron instruments Linear proton accelerator

  6. Target Station Systems at ESS Neutrons Protons Target monitoring plug Safety valve Target drive housing Proton beam instrumentation plug Proton beam window Moderator and reflector plug Target wheel Neutron beam extraction Shutter Neutron beam window

  7. Predictive ESS Target Protection System

  8. 3. High Performance Computing using PLCs

  9. High Performance Computing using PLCs • Cluster instantiation: • Cluster type: Scalable Multiprocessor, with physically distributed memory but logically shared memory • Programming model: shared memory, using shared memory areas in i-Devices • Each processor (S7-1518) acting as I/O controller and shared i-Device, is able to address all the memory areas • The processing information (database) comes from an additional PLC (S7-1516) configured as shared i-Device • An internal mechanism provided by Siemens for shared i-Devices, ensures coherence of the shared memory areas • Topologies built: Bus (Profinet port to port) and Star (using a Scalanceprofinet switch) • Real-time profinet profile defined for the communications between processors and database

  10. High Performance Computing using PLCs 3 x CPU S7-1518F 3 x CP 1543-1 1 x SCALANCE IRT Switch 1 x SCALANCE Switch Scalable Multiprocessor 1 x CPU S7-1516 1 x CP 1543-1 3 x IM155-5 3 x AI 3 x AQ 3 x DI 3 x DQ 3 x DQ Relay Process Database + Actuation P. Supply SITOP Redundant Powering 20A SCADA SIMATIC HMI TP 1200 Comfort

  11. 4. Conclusions • Particle Accelerators and Accelerator Driven Facilities are time and cost critical facilities and predictive interlocks could play a key role in: • Avoiding to stop the machine=>High availability • Minimizing machine downtime =>Saving cost • Speed-up machine tuning and provide advanced fault detection and fault recovery • Perform preventive maintenance (structural health) • A Real-Time High Performance Computing platform using PLCsis currently up and running at ESS being the basis for predictive interlocking

  12. Further work • Definition of the communications and synchronization primitives for distributed processing • Application development for Target protection following the predictive approach, which involves the parallelization of the tasks • Evaluation of the interlocks response time for the above program • Failsafe i-Devices possible but not “shared devices” which implies a different approach for cluster construction Real-Time High Performance Computation to run AI predictive interlocks software for machine protection is perhaps a good way to increase dependability

  13. THANK YOU !!!

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