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Machida, Masahiko; Yamada, Susumu; Kim, M.; Tanaka, Satoshi*; Tobita, Yasuhiro*; Iwata, Ayako*; Aoki, Yuto; Aoki, Kazuhisa; Yanagisawa, Kenichi*; Yamaguchi, Takashi; et al.
RIST News, (70), p.3 - 22, 2024/09
Inside the Fukushima Daiichi Nuclear Power Plant (1F), there are many locations with high radiation levels due to contamination by radioactive materials that leaked from the reactor. These pose a significant obstacle to the smooth progress of decommissioning work. To help solve this issue, the Japan Atomic Energy Agency (JAEA), under a subsidy from the Ministry of Economy, Trade, and Industry's decommissioning and contaminated water management project, is conducting research and development on digital technologies to improve the radiation environment inside the decommissioning site. This project, titled "Development of Technology to Improve the Environment Inside Reactor Buildings (Enhancing Digital Technology for Environment and Source Distribution to Reduce Radiation Exposure)," began in April of FY 2023. In this project, the aim is to develop three interconnected systems: FrontEnd, Pro, and BackEnd. The FrontEnd system, based on the previously developed 3D-ADRES-Indoor (prototype) from FY 2021-2022, will be upgraded to a high-speed digital twin technology usable on-site. The Pro system will carry out detailed analysis in rooms such as the new office building at 1F, while the BackEnd system will serve as a database to centrally manage the collected and analyzed data. This report focuses on the FrontEnd system, which will be used on-site. After point cloud measurement, the system will quickly create a 3D mesh model, estimate the radiation source from dose rate measurements, and refine the position and intensity of the estimated source using recalculation techniques (re-observation instructions and re-estimation). The results of verification tests conducted on Unit 5 are also presented. Furthermore, the report briefly discusses the future research and development plans for this project.
Machida, Masahiko; Yamada, Susumu; Kim, M.; Okumura, Masahiko; Miyamura, Hiroko; Malins, A.; Shikaze, Yoshiaki; Sato, Tomoki*; Numata, Yoshiaki*; Tobita, Yasuhiro*; et al.
RIST News, (68), p.3 - 19, 2022/09
no abstracts in English
Daido, Hiroyuki
Reza Kenkyu, 31(11), p.696 - 697, 2003/11
no abstracts in English
Daido, Hiroyuki
Reza Kenkyu, 31(11), p.698 - 706, 2003/11
no abstracts in English
Imamura, Toshiyuki; Muramatsu, Kazuhiro; Kitabata, Hideyuki*; Kaneko, Isamu*; Yamagishi, Nobuhiro*; Hasegawa, Yukihiro*; Takemiya, Hiroshi*; Hirayama, Toshio
Joho Shori Gakkai Kenkyu Hokoku 2001-ARC-142, p.49 - 54, 2001/03
no abstracts in English
Sawamura, Sadashi*
PNC TJ1600 94-002, 61 Pages, 1994/02
None
Nihon Genshiryoku Gakkai-Shi, 35(7), p.596 - 599, 1993/07
no abstracts in English
Sunaga, Hiromi
Radioisotopes, 41(3), p.75 - 76, 1992/00
no abstracts in English
; Kubota, Masumitsu; ;
JAERI-M 91-147, 191 Pages, 1991/09
no abstracts in English
Umezawa, Hirokazu
Nihon Genshiryoku Gakkai-Shi, 32(7), p.658 - 660, 1990/07
no abstracts in English
Sunaga, Hiromi; Tanaka, Susumu; ; Agematsu, Takashi; Yotsumoto, Keiichi; Tanaka, Ryuichi; Yoshida, Kenzo; ; ; ; et al.
JAERI-M 89-182, 31 Pages, 1989/11
no abstracts in English
; ;
JAERI-M 8810, 37 Pages, 1980/04
no abstracts in English
; ; ; Machi, Sueo
JAERI-M 7496, 37 Pages, 1978/01
no abstracts in English
Au Grain for Medical Use; ; ; Genka, Tsuguo
JAERI-M 7209, 14 Pages, 1977/08
no abstracts in English
Gosei Jushi, 18(11-12), p.16 - 20,10, 1972/11
no abstracts in English
町田 昌彦
not registered
JP, 2022-083279 
Patent licensing information Patent publication (In Japanese)
【課題】数少ない測定結果から放射線源の分布を精度良く推定する。 【解決手段】線源推定装置1は、対象区域を分割して得られた複数の領域のそれぞれに存在すると仮定された放射線源を示す線源ベクトルωを作成する線源ベクトル作成部13と、測定点における測定値を示す線量ベクトルYを作成する線量ベクトル作成部15と、線源ベクトルωが示す放射線源の数と測定点の数とに対応する行列Xを計算する行列計算部16と、対象区域における放射線源の分布を推定する線源推定部17と、を備える。線源推定部17は、線源ベクトルωと行列Xとの積を線量ベクトルYの擬似ベクトルと見做し、線源ベクトルωをスパースベクトルとして、擬似ベクトルから線源ベクトルωを復元する逆解析を行うことにより、放射線源の分布を推定する。
町田 昌彦
not registered
JP, 2022-083280 Patent licensing information Patent publication (In Japanese)
【課題】観測点数を極力少なくしながら観測対象を確実に観測できるよう観測点の最適化を図る。 【解決手段】観測点決定装置1は、対象区域の構造物の表面を分割して複数の格子面を作成する格子面作成部13と、対象区域内の空間を分割して複数の空間格子点を作成する空間格子点作成部16と、を備える。観測点決定装置1は、観測点における観測結果から観測対象を推定する逆推定が成功する観測点の最少点数を、観測対象の数と格子面の数とに基づいて決定する最少点数決定部15を備える。観測点決定装置1は、各格子面の任意の点と空間格子点とを結ぶ直線が当該空間格子点に直接到達するか否かを、空間格子点毎に判定する直達判定部17と、観測点の最少点数と直達判定部17の判定結果とに基づいて観測点を決定する観測点決定部19と、を備える。
Machida, Masahiko
no journal, ,
no abstracts in English
Takahashi, Tone; Koizumi, Mitsuo; Tomikawa, Hirofumi; Kimura, Yoshiki; Sato, Yuki; Terasaka, Yuta; Torii, Tatsuo; Yamanishi, Hirokuni*; Wakabayashi, Genichiro*
no journal, ,
no abstracts in English
Okumura, Keisuke; Sato, Wakaei; Maeda, Hirobumi; Wakaida, Ikuo; Washiya, Tadahiro; Katakura, Junichi*
no journal, ,
In order to develop the evaluation technology of the most probable radiation source and dose rate distributions in the primary containment vessel (PCV), we evaluated the radiation source distribution based on the results of fuel burn-up calculation, activation calculation of structural materials and severe accident analysis. Then, we built a three-dimensional PCV model for the particle transport Monte Carlo calculation code PHITS. From the PHITS calculation, we obtained the response function of the dose rate distribution due to each unit radiation source.
