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SUMMARY:Joint ICRP & NPO Fukushima Dialogue Webinar
DESCRIPTION:15th Anniversary of the Fukushima Nuclear Accident: Testimonies on the Past\, Present\, and Future\nThis year marks the fifteenth anniversary of the Fukushima Daiichi Nuclear Power Plant accident. From 2011 to 2019\, the International Commission on Radiological Protection (ICRP) continuously organised the Fukushima Dialogue meetings in Fukushima. Since 2019\, the organisation of the Dialogues has been taken over by the non-profit organisation Fukushima Dialogue\, which was established by participants in Fukushima. \nThe main aim of this initiative was to establish a dialogue between experts and stakeholders in affected areas to identify the problems and the challenges they are confronted with and to express their expectations\, particularly as regard the human dimension affected by the accident. These dialogues have significantly contributed to the development of the co-expertise process of the recovery of the Fukushima Daiichi Nuclear Power Plant accident. As time has passed\, radiation levels have gradually decreased\, daily life has regained a degree of stability\, and protective measures have become routine. At the same time\, however\, evacuation zones still remain\, severe population decline persists\, and there are areas where radiation levels are relatively high. The impacts of the accident therefore continue to be strongly felt. In addition\, new challenges have emerged in the course of the recovery process itself. \nThis webinar aims to share the current situation in Fukushima fifteen years after the nuclear accident\, as well as expectation and challenges for the future\, through testimonies from residents.
URL:https://bvsabr.be/event/joint-icrp-npo-fukushima-dialogue/
LOCATION:Online
CATEGORIES:ICRP
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DTSTART;TZID=Europe/Paris:20260312T120000
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DTSTAMP:20260514T181939
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SUMMARY:SRP webinar: Teaching AI the Laws of Physics – Paradigm Shift in Radiation Protection
DESCRIPTION:Free SRP Webinar:  \nTeaching AI the Laws of Physics – Paradigm Shift in Radiation Protection\n12 March 2026 12:00 – 13:00 (BST) \n\n\nAs Artificial Intelligence (AI) becomes increasingly integrated into the physical world\, its application within nuclear safety–critical domains has come under heightened scrutiny. While AI has demonstrated considerable effectiveness in perception-based tasks—such as processing data\, images\, patterns\, and speech—its deployment in nuclear safety applications presents significant challenges. In particular\, the data-driven and often opaque “black box” nature of conventional AI systems limits their ability to provide transparent\, auditable rationales for their outputs. This lack of explainability raises regulatory and industry concerns\, as it may introduce unknown or unacceptable safety risks if AI-generated recommendations are implemented without sufficient understanding or validation. \nTo address these challenges\, an emerging field of research is focused on the development of Explainable and Physics-Informed Artificial Intelligence. In this approach\, AI models are explicitly constrained and guided by the Laws of Physics\, system dynamics\, and governing equations embedded directly within the neural network architecture. This paradigm supports the development of trustworthy AI systems that are capable of delivering accurate\, rapid\, robust\, and interpretable solutions while remaining consistent with established physical principles. \nThis presentation will describe the methodology and challenges associated with training AI systems to recognise\, respect\, and enforce physical laws when formulating predictions and decisions. It will demonstrate how Physics-Informed AI can transform radiation protection by ensuring that AI outputs remain physically plausible and scientifically defensible\, thereby improving accuracy\, reliability\, and interpretability in complex and safety-critical environments. Finally\, emerging applications across nuclear and environmental safety\, as well as medical physics\, will be discussed\, highlighting the potential of this approach to support regulatory acceptance and operational deployment.
URL:https://bvsabr.be/event/srp-webinar-teachingai/
LOCATION:Online
CATEGORIES:SRP
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