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Takagi, Hirotaka*; Takagi, Rina*; Minami, Susumu*; Nomoto, Takuya*; Oishi, Kazuki*; Suzuki, Michito*; Yanagi, Yuki*; Hirayama, Motoaki*; Khanh, N.*; Karube, Kosuke*; et al.
Nature Physics, 19(7), p.961 - 968, 2023/07
Times Cited Count:0 Percentile:95.71(Physics, Multidisciplinary)Otsuka, Yusuke*; Kanazawa, Naoya*; Hirayama, Motoaki*; Matsui, Akira*; Nomoto, Takuya*; Arita, Ryotaro*; Nakajima, Taro*; Hanashima, Takayasu*; Ukleev, V.*; Aoki, Hiroyuki; et al.
Science Advances (Internet), 7(47), p.eabj0498_1 - eabj0498_9, 2021/11
Times Cited Count:3 Percentile:42.29(Multidisciplinary Sciences)Handa, Yuichi; Nakajima, Ryota; Yonekawa, Akihisa*; Takatsu, Kazuki; Kinoshita, Junichi; Irie, Hirobumi; Suzuki, Hisao*
JAEA-Technology 2020-005, 22 Pages, 2020/06
The Evaporator-II is installed in Waste Treatment Facility No.2. The evaporator system treats intermediate level radioactive liquid waste for Nuclear Science Research Institute and more. It is maintenance the evaporator can once/3years by the maintenance plan. The evaporator can is important unit of the Evaporator-II system. This report summarizes record of maintenance the Evaporator-II in FY2015.
Sakanaka, Shogo*; Akemoto, Mitsuo*; Aoto, Tomohiro*; Arakawa, Dai*; Asaoka, Seiji*; Enomoto, Atsushi*; Fukuda, Shigeki*; Furukawa, Kazuro*; Furuya, Takaaki*; Haga, Kaiichi*; et al.
Proceedings of 1st International Particle Accelerator Conference (IPAC '10) (Internet), p.2338 - 2340, 2010/05
Future synchrotron light source using a 5-GeV energy recovery linac (ERL) is under proposal by our Japanese collaboration team, and we are conducting R&D efforts for that. We are developing high-brightness DC photocathode guns, two types of cryomodules for both injector and main superconducting (SC) linacs, and 1.3 GHz high CW-power RF sources. We are also constructing the Compact ERL (cERL) for demonstrating the recirculation of low-emittance, high-current beams using above-mentioned critical technologies.
Tsuchimochi, Ryota; Kato, Masato; Nakajima, Tatsuya; Hirooka, Shun; Watanabe, Masashi; Nakamichi, Shinya; Murakami, Tatsutoshi; Ishii, Katsunori
no journal, ,
Uranium and Plutonium mixed oxide (MOX) pellets used as fast reactor fuels have been produced from several raw materials by mechanical blending method. It is essential to control the pellet density which is one of the important fuel specifications, but it is difficult to understand relationships among many parameters in the production. Database for MOX production was prepared from production results of JOYO and MONJU. The input data of eighteen types were chosen from production process and made a data set. A machine learning model for predicting the sintered density of MOX pellets was derived by gradient boosting regressor.