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dc.contributor.authorVázquez Rodríguez, Víctor
dc.contributor.authorValenzuela Segura, Elio
dc.contributor.authorShepstone, Ricardo
dc.contributor.authorMegías Núñez, Carlos
dc.contributor.authorMiccichè, Gioacchino
dc.contributor.authorRos Vidal, Eduardo 
dc.contributor.authorBarranco Expósito, Francisco 
dc.date.accessioned2026-03-20T09:48:43Z
dc.date.available2026-03-20T09:48:43Z
dc.date.issued2026-03-20
dc.identifier.citationVíctor Vázquez et al 2026 Nucl. Fusion 66 046029es_ES
dc.identifier.urihttps://hdl.handle.net/10481/112339
dc.description.abstractExperimental fusion research facilities, such as the International Fusion Materials Irradiation Facility-DEMO Oriented Neutron Source (IFMIF-DONES), require advanced remote handling (RH) systems to perform maintenance and inspection tasks in a safe and reliable manner, due to their intrinsic high-radiation nature. The mixed-criticality requirements of the data streams used in these systems force the deployment of separate networks and communication technologies. Commonly, it includes fieldbuses for traffic control, standard Ethernet for video and general-purpose traffic, and dedicated networks for the most critical safety-related signals. This fragmentation leads to complex and costly deployments and also prevents the application of models for predictive maintenance or advanced monitoring. The time-sensitive networking (TSN) technology stack aims to provide deterministic behaviour for data transmission over standard Ethernet, allowing for convergence on a single network and ensuring bounded latencies for critical traffic. In this work, we propose a design and validate the TSN-based communication architecture for the RH system of IFMIF-DONES. The design ensures bounded delivery times for safety-critical interlock signals, achieving a worst-case delay under 30 us even under high network load. The proposed network is also validated in a real robotic teleoperation task, where artificial intelligence is applied for object detection and tracking, using mixed-criticality video streams. Our results show that TSN traffic shapers are essential in providing the necessary latency and bandwidth guarantees for such teleoperation tasks, enabling network convergence in this kind of deployments.es_ES
dc.description.sponsorshipEuropean Union via the Euratom Research and Training Programme (Grant 101052200—EUROfusion)es_ES
dc.description.sponsorshipMICIU/AEI/10.13039/501100011033 and ERDF/EU (Grant PID2022-141466OB-I00)es_ES
dc.description.sponsorshipMICIU/AEI/10.13039/501100011033, FPU PhD Fellowship (Grant FPU20/05842)es_ES
dc.description.sponsorshipMICIU/AEI/10.13039/501100011033, FPU PhD Fellowship (Grant FPU20/01857)es_ES
dc.description.sponsorshipUniversidad de Granada, Programa de Contratos-Puente (Grant CP-2025-37)es_ES
dc.description.sponsorshipFunding for open access charge: Universidad de Granadaes_ES
dc.language.isoenges_ES
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 Licensees_ES
dc.rightsAtribución-NoComercial-CompartirIgual 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectIFMIF-DONESes_ES
dc.subjecttime-sensitive networkinges_ES
dc.subjectremote handlinges_ES
dc.subjectartificial intelligence es_ES
dc.titleRemote handling operation for IFMIF-DONES supported by time-sensitive networkinges_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1088/1741-4326/ae511e
dc.type.hasVersionVoRes_ES


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