Development of machine learning force fields of clay minerals

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Title	Development of machine learning force fields of clay minerals
Alternative title	粘土鉱物の機械学習力場の開発
Author	Okumura, Masahiko(Japan Atomic Energy Agency)
Author	Kobayashi, Keita(Research Organization for Information Science and Technology)
Author	Yamaguchi, Akiko(Japan Atomic Energy Agency)
Issued date	2020-03-18
Language	jpn
Page	p. 2H04
Type	proceedings
File Format	PDF
Taxonomy	6-2-1-1 Separation
Taxonomy(Computer Assigned)	6-2-1 Decontamination
Subject/Session_name	Session III. Fission Energy Engineering
Information source	Go to external webpage Relation URL
Meeting title	2020 Annual Meeting of Atomic Energy Society of Japan
Related content	Significance in this session - Fukushima Dai-ichi Nuclear Power Station accident and code of ethics Development status of accident tolerant fuel: challenges and prospects 1 - development of accident tolerant fuel for BWR Development status of accident tolerant fuel: challenges and prospects 2 - development of accident tolerant fuel for BWR Development status of accident tolerant fuel: challenges and prospects - development of accident tolerant fuel for PWR Piping system, risk management based on wall thinning monitoring and prediction PYRAMID 6 - evaluation of probability of failure using Bayesian method with multi-point piping inner surface monitoring
URI	https://f-archive.jaea.go.jp/dspace/handle/faa/209917
collect date(WARP)	2020-11-30

Fukushima Nuclear Accident Archive