Summary
Fred Werner introduces the AI for Good webinar by ITU aiming to identify AI applications for sustainable development goals. Key highlights include discussions on AI in nuclear energy by various experts, focusing on efficiency, sustainability, and optimizing operations in power plants. The session emphasized on applications of AI for operations and maintenance, anomaly detection, digital twins for monitoring, and automation in the nuclear power industry. Strategies for successful adoption of AI technologies in the nuclear sector, challenges faced, training programs available, and importance of data accessibility and cybersecurity measures were also discussed during the webinar. The session concluded with insights on developing international standards for AI in nuclear energy and the importance of expertise, data analytics, and cloud deployment for successful AI adoption in the industry.
Chapters
Introduction to AI for Good
Housekeeping Issues
Opening Remarks on AI for Nuclear Energy
Remarks on AI Applications
AI for Nuclear Energy Episode
Applying AI at ROSATOM
AI for Industrial Monitoring
AI for Operations and Maintenance
Automation Opportunities in Nuclear Power Plants
Broader Application of Artificial Intelligence
Development of a Nuclear-Powered Dictionary
Automating Review of Corrective Actions
Monitoring Flow Accelerated Corrosion Prediction
Machine Vision for Concrete Inspection
Developing International Standards on AI for Nuclear Energy
Challenges Related to Adopting AI in Nuclear Energy
Scaling AI Projects Efficiently
Accessibility of Data and Cybersecurity Concerns
Maturity of Nuclear Industry in AI
AI Training Availability
AI for Knowledge Management and Transfer
Introduction to AI for Good
Fred Werner introduces the AI for Good webinar organized by ITU and its goal to identify practical applications of AI for sustainable development goals.
Housekeeping Issues
Instructions for participation and introduction of session moderators, Chirayu Batra and Alina Constantine, from IAEA.
Opening Remarks on AI for Nuclear Energy
Dino Alvarz Bart provides an overview of AI applications in nuclear energy, emphasizing the impact on the nuclear power industry's efficiency and sustainability.
Remarks on AI Applications
Mr. Lee discusses ITU's AI initiatives and collaborations, highlighting machine learning competitions and focus groups for environmental efficiency and automation.
AI for Nuclear Energy Episode
Mr. Lee introduces the AI for nuclear energy episode and the exploration of AI in nuclear power with distinguished speakers sharing insights and thoughts.
Applying AI at ROSATOM
Boris McEvenin presents an AI project at ROSATOM focusing on anomaly detection for power plants, showing the impact of predictive maintenance in optimizing operations.
AI for Industrial Monitoring
Aurelia Alvarez Bart discusses the usage of digital twins for nuclear plant monitoring, showcasing how AI technology can provide diagnostic value to improve operations.
AI for Operations and Maintenance
Heather Feldman delves into EPRI's initiative on AI for operations and maintenance at nuclear power plants, emphasizing efficiency and reliability enhancements through AI technology.
Automation Opportunities in Nuclear Power Plants
Efforts are underway to automate chemistry, radiation monitoring, pipe monitoring, and various processes at nuclear power plants using AI.
Broader Application of Artificial Intelligence
Discussing the application of AI in gaining insights, optimizing processes, prognostics, and automation in the electric power industry.
Development of a Nuclear-Powered Dictionary
Efforts to create a nuclear power dictionary for natural language processing applications tailored to the nuclear power industry's unique terminology.
Automating Review of Corrective Actions
Using natural language processing to automate the review of corrective action reports in nuclear reactors to improve efficiency and accuracy.
Monitoring Flow Accelerated Corrosion Prediction
Utilizing AI to predict degradation in pipes and components, specifically focusing on flow accelerated corrosion in power plants.
Machine Vision for Concrete Inspection
Employing machine vision models to automatically detect damages in concrete structures, facilitating inspection processes in nuclear facilities.
Developing International Standards on AI for Nuclear Energy
Exploring the development of international standards for Artificial Intelligence in nuclear energy and the collaboration between different standardization bodies.
Challenges Related to Adopting AI in Nuclear Energy
Discussions on challenges like change management, expertise, and trust necessary for successful adoption of AI technologies in the nuclear industry.
Scaling AI Projects Efficiently
Strategies for scaling AI projects efficiently, emphasizing starting small, building expertise, and gaining organizational buy-in for enterprise-wide implementation.
Accessibility of Data and Cybersecurity Concerns
Addressing the accessibility of data for AI applications in nuclear energy and the importance of cybersecurity measures to protect sensitive information.
Maturity of Nuclear Industry in AI
Assessing the maturity of the nuclear industry in AI adoption compared to other industries, focusing on expertise, cloud deployment, and data analytics capabilities.
AI Training Availability
Exploring the training programs available for AI in the electric power industry to enhance expertise and skills among professionals.
AI for Knowledge Management and Transfer
Utilizing AI for knowledge transfer in critical areas like steam generator inspections, demonstrating automation of data analysis to transfer expertise within organizations.
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