Summary
SUMMARY
High-energy physics and photon Research Infrastructures (RIs), such as particle accelerators, synchrotrons, and free-electron lasers, are central to European scientific excellence. However, they are highly complex and notoriously energy-intensive, requiring thousands of perfectly synchronized components. GreenBeam-AI addresses the critical need for "greening and resilience" by pioneering the next generation of real-time, AI-informed Digital Twins (DTs) coupled with advanced Edge-Computing sensor networks. By transitioning RIs from manual/static beam tuning to autonomous, dynamic optimization, GreenBeam-AI will drastically reduce energy consumption, minimize thermal stress on critical components, and prevent costly beamtime losses, thereby advancing the state-of-the-art in RI digitalisation.
The overarching ambition of GreenBeam-AI is to transform the operation of European high-energy RIs through intelligent digitalisation, making them more resilient, sustainable, and scientifically competitive.
Description
Target Call: HORIZON-INFRA-2026-TECH-01-01 (R&D for the next generation of scientific instrumentation, tools, methods, digitalisation and solutions for research infrastructure upgrades)
Estimated Duration: 36 Months
Target TRL: TRL 4 to TRL 6 (for Research Infrastructures); TRL 2 to TRL 4 (for industrial applications)
Specific Objectives:
1. Develop an architecture for High-Fidelity Digital Twins: Create a bi-directional, real-time digital replica of accelerator and laser beamlines capable of simulating beam dynamics, space charge, and component thermal states in milliseconds.
2. Deploy Advanced Edge-Computing Instrumentation: Integrate new, low-latency Edge-AI IoT sensors directly onto legacy RI hardware (magnets, RF cavities, power supplies) to capture environmental variations and equipment states without overwhelming central data networks.
3. Achieve Autonomous Beam Optimization & Energy Throttling: Train surrogate Machine Learning (ML) models to autonomously align beams, predict component degradation, and dynamically throttle power during micro-interruptions or idle states.
4. Foster Industrial Technology Transfer: Translate the Edge-AI and continuous-learning models developed for RIs into predictive maintenance and energy-saving tools for European SMEs in energy-intensive sectors (e.g., semiconductor lithography, advanced manufacturing).
TYPE OF PARTNER:
1. European SME (Edge Computing & IoT) - A hardware startup specializing in low-latency, ruggedized edge-computing sensors to co-develop the instrumentation.
2. European SME/Mid-cap (Industrial Integration) - A technology company bridging the gap between scientific instrumentation and commercial manufacturing,
Deadline for EoI: April 16th
Should you have any questions, feel free to contact Mar Coromina mcoromina@secartys.org | 623 35 59 80 and we'll do our best to help you.
