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contributor authorOhshima, Hiroyuki;Asayama, Tai;Furukawa, Tomohiro;Tanaka, Masaaki;Uchibori, Akihiro;Takata, Takashi;Seki, Akiyuki;Enuma, Yasuhiro
date accessioned2022-12-27T23:19:41Z
date available2022-12-27T23:19:41Z
date copyright6/15/2022 12:00:00 AM
date issued2022
identifier issn2332-8983
identifier otherners_009_02_025001.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4288387
description abstractThis paper describes the outline and development plan for “Advanced Reactor Knowledge- and Artificial Intelligence (AI)-aided design integration approach through the whole plant lifecycle (ARKADIA),” which the Japan Atomic Energy Agency has begun developing to transform advanced nuclear reactor design to meet expectations of a safe, economic, and sustainable carbon-free energy source. ARKADIA will realize AI-aided integrated numerical analysis to offer the best possible solutions for any challenge that could arise in the design and operation of a nuclear plant, including optimization of safety equipment as well as structures, systems, and components. State-of-the-art numerical simulation technologies and a knowledge base that stores data and insights from past nuclear reactor development projects and R&D are integrated with AI. In the first phase of development, ARKADIA-design and ARKADIA-safety will be constructed individually, with the first target of a sodium-cooled reactor. In a subsequent phase, everything will be integrated into a single entity that is technology inclusive and applicable not only to advanced rectors with a variety of concepts, coolants, configurations, and output levels but also to existing light-water reactors.
publisherThe American Society of Mechanical Engineers (ASME)
titleARKADIA—For the Innovation of Advanced Nuclear Reactor Design
typeJournal Paper
journal volume9
journal issue2
journal titleJournal of Nuclear Engineering and Radiation Science
identifier doi10.1115/1.4054726
journal fristpage25001
journal lastpage25001_12
page12
treeJournal of Nuclear Engineering and Radiation Science:;2022:;volume( 009 ):;issue: 002
contenttypeFulltext


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