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Arai, Tsuyoshi*; Nakamura, Fumiya*; Abe, Ryoji*; Ueno, Fuga*; Seko, Noriaki*; Arai, Yoichi; Watanabe, So
Progress in Nuclear Science and Technology (Internet), 7, p.147 - 153, 2025/03
no abstracts in English
Sogabe, Joji; Ishida, Shinya; Tagami, Hirotaka; Okano, Yasushi; Kamiyama, Kenji; Onoda, Yuichi; Matsuba, Kenichi; Yamano, Hidemasa; Kubo, Shigenobu; Kubota, Ryuzaburo*; et al.
Proceedings of International Conference on Nuclear Fuel Cycle (GLOBAL2024) (Internet), 4 Pages, 2024/10
In the frame of France-Japan collaboration, the calculational methodologies were defined and assessed, and the phenomenology and the severe accident consequences were investigated in a pool-type sodium-cooled fast reactor.

Kinjo, Katsuki*; Fujibayashi, Hiroki*; Matsumura, Hiroki*; Hori, Fumiya*; Kitagawa, Shunsaku*; Ishida, Kenji*; Tokunaga, Yo; Sakai, Hironori; Kambe, Shinsaku; Nakamura, Ai*; et al.
Science Advances (Internet), 9(30), p.2736_1 - 2736_6, 2023/07
Times Cited Count:17 Percentile:89.84(Multidisciplinary Sciences)Arai, Yoichi; Watanabe, So; Ono, Shimpei; Nomura, Kazunori; Nakamura, Fumiya*; Arai, Tsuyoshi*; Seko, Noriaki*; Hoshina, Hiroyuki*; Hagura, Naoto*; Kubota, Toshio*
Nuclear Instruments and Methods in Physics Research B, 477, p.54 - 59, 2020/08
Times Cited Count:7 Percentile:52.49(Instruments & Instrumentation)Arai, Yoichi; Watanabe, So; Ono, Shimpei; Nomura, Kazunori; Nakamura, Fumiya*; Arai, Tsuyoshi*; Seko, Noriaki*; Hoshina, Hiroyuki*; Kubota, Toshio*
QST-M-23; QST Takasaki Annual Report 2018, P. 59, 2020/03
Arai, Yoichi; Watanabe, So; Ono, Shimpei; Nakamura, Masahiro; Shibata, Atsuhiro; Nakamura, Fumiya*; Arai, Tsuyoshi*; Seko, Noriaki*; Hoshina, Hiroyuki*; Hagura, Naoto*; et al.
International Journal of PIXE, 29(1&2), p.17 - 31, 2019/00
The spent PUREX solvent containing U and Pu is generated from the reprocessing process of spent nuclear fuel. The nuclear material removal is important for the safe storage or disposal of the spent solvent. Our previous study revealed that the adsorbent with the iminodiacetic acid (IDA) functional group is one of the most promising materials for designing the nuclear material recovery process. Accordingly, an IDA-type adsorbent was synthesized by using graft polymerization technology or a chemical reaction to improve the adsorption rate and capacity. The synthesized IDA-type adsorbent was characterized by micro particle-induced X-ray emission (PIXE) and extended X-ray absorption fine structure (EXAFS) analyses. The micro-PIXE analysis revealed that Zr was adsorbed on the whole synthesized adsorbents and quantified the microamount of adsorbed Zr. Moreover, EXAFS suggested that Zr in the aqueous solution and solvent can be trapped by the IDA group with different mechanisms.
Nakamura, Shinichi*; Suzui, Nobuo; Nagasaka, Toshinori*; Komatsu, Fumiya*; Ishioka, Noriko; Ito, Sayuri*; Kawachi, Naoki; Rai, Hiroki*; Hattori, Hiroyuki*; Chino, Mitsuo*; et al.
Journal of Experimental Botany, 64(4), p.1073 - 1081, 2013/02
Times Cited Count:58 Percentile:85.23(Plant Sciences)Nakamura, Fumiya*; Arai, Tsuyoshi*; Seko, Noriaki*; Arai, Yoichi; Watanabe, So; Nomura, Kazunori
no journal, ,
no abstracts in English
Kida, Fukuka*; Nakamura, Fumiya*; Arai, Tsuyoshi*; Matsushima, Ryotatsu; Saito, Yasuo
no journal, ,
no abstracts in English
Arai, Yoichi; Watanabe, So; Ono, Shimpei; Nomura, Kazunori; Nakamura, Fumiya*; Arai, Tsuyoshi*; Seko, Noriaki*; Hoshina, Hiroyuki*; Kubota, Toshio*
no journal, ,
no abstracts in English
Nakamura, Fumiya*; Arai, Tsuyoshi*; Arai, Yoichi; Watanabe, So; Nomura, Kazunori; Seko, Noriaki*
no journal, ,
no abstracts in English

dust monitor for high-dose environments based on machine learning of track informationTsubota, Yoichi; Laffolley, H.; Tsuji, Tomoya; Honda, Fumiya; Nakamura, Hiroki; Suzuki, Masahiro
no journal, ,
Remote monitoring of radioactive dust in high-dose environments, such as the Fukushima Daiichi Nuclear Power Station (1F), is essential for ensuring the safety of decommissioning work. JAEA has prototyped "DICAS-OS" as a remote dust measurement instrument. Premised on mounting onto a quadruped robot, the device was lightened (approx. 3 kg) and equipped with an 
dust monitor using a semiconductor pixel detector and auxiliary measurement devices (particle sensor, ultrasonic anemometer), enabling unified continuous remote monitoring of dust information. However, due to its shield-free design, high ambient dose rates result in measurement noise. To address this, we developed the machine learning system "DICAS-ML". Based on the characteristics of radiation track data captured by the semiconductor pixel detector, it uses the LightGBM algorithm to discriminate 

rays and subtracts the influence of ambient dose, making it possible to accurately evaluate the 
radioactivity of the dust. Through the combination of both systems, we successfully conducted demonstration measurements of airborne radioactive material concentration and wind conditions inside the 1F Unit 3 Reactor Building in January 2025, confirming their effectiveness.
Nakamura, Fumiya*; Abe, Ryoji*; Arai, Tsuyoshi*; Seko, Noriaki*; Arai, Yoichi; Watanabe, So; Nomura, Kazunori
no journal, ,
Nakamura, Fumiya*; Arai, Tsuyoshi*; Hoshina, Hiroyuki*; Seko, Noriaki*; Arai, Yoichi; Watanabe, So; Nomura, Kazunori
no journal, ,
no abstracts in English