Guest
With the advent of powerful computing capabilities and data analysis tools, the nuclear power industry is embracing artificial intelligence, machine learning and deep learning techniques to streamline and optimize nuclear power plant operation and maintenance, while supporting the development of new advanced nuclear power technologies. Nuclear power is undoubtedly a clean and large source of energy that can provide emission-free power generation to meet the current growing energy demands. However, in order to be competitive as well as integrated into the mix of modern energy systems, nuclear power plants – in addition to being safe, reliable, and sustainable – also need to be economical and efficient. More, with the advancement of new reactor designs in the market, and with a capability of operating multiple units, there is a need for more robust models for operations and predictive analysis. Artificial Intelligence (AI) methodologies and tools can be applied for physics-based predictive analysis that can be used to perform design, manufacturing and construction optimization, operation effectiveness, improved new reactor design iterations, model-based fault detection and, advanced control systems. These applications can reduce the operation and maintenance costs of nuclear power plants and make them safer using intelligent data-driven or physics-based model-driven analysis. Application of AI can also be used for accident evolution prediction and to suggest better severe accident management guidelines. A combination of physics-based models as well as data coming from sensors, drones, etc., make a unique digital twin and serves as a foundation for several applications including automation, in-service inspection, evaluation and characterization of structure, system and component defects, real-time risk monitoring, reactor designing, predictive maintenance, etc.. Use of augmented and virtual reality could also support nuclear personnel training and development, helping to reduce human-related errors during operation and maintenance. AI can provide solutions in this era of digitalization and can pave the path forward to a sustainable future of the nuclear power industry. This session will invite some of the key developers and nuclear power industry leaders in this area and discuss the vision and path forward to Nuclear 4.0 with the help of AI. Opening Remarks: Chaesub Lee, Director of the Telecommunication Standardization Bureau, International Telecommunication Union (ITU) Mikhail Chudakov, Deputy Director-General and Head of the Department of Nuclear Energy, International Atomic Energy Agency (IAEA) How do we use Digital Twins for nuclear plant monitoring? Aurélien Schwartz, CEO, METROSCOPE AI for operation and maintenance of nuclear reactors: Heather Feldman, Director of Innovation in the Nuclear Sector, Electric Power Research Institute (EPRI) Develop International Standards on AI for Nuclear Energy: Daowei Bi, Director of the Department of Digitalization Engineering, Shanghai Nuclear Engineering Research and Design Institute (SNERDI) AI application for nuclear energy: Boris Makevnin, CEO, Cifrum Private Enterprise Panel Discussion on AI for Nuclear Energy: Boris Makevnin, CEO, Cifrum Private Enterprise Daowei Bi, Director of the Department of Digitalization Engineering, Shanghai Nuclear Engineering Research and Design Institute (SNERDI) Heather Feldman, Director of Innovation in the Nuclear Sector, Electric Power Research Institute (EPRI) Aurélien Schwartz, CEO, METROSCOPE Moderators: Chirayu Batra, Nuclear Engineer and a Project Officer, International Atomic Energy Agency (IAEA) Alina Constantin, Project Officer for Non-Electric Applications of Nuclear Energy, International Atomic Energy Agency Watch the latest #AIforGood videos: Explore more #AIforGood content: Discover what's next on our programme! Social Media: Website: Twitter: LinkedIn Page: LinkedIn Group: Instagram: Facebook: Disclaimer: The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU. #AIforNuclearEnergy #AIforGoodWebinars
