R&D status of digital technology on inverse estimation of radioactive source distributions and related source countermeasures; Fast Digital Twin Tech. in Decommissioning Field: 3D-ADRES-Indoor FrontEnd

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.

Development of time-series point cloud data changes and automatic structure recognition system using Unreal Engine

Kato, Toru*; Takahashi, Hiroki*; Yamashita, Meguru*; Doi, Akio*; Imabuchi, Takashi

Proceedings of 29th International Symposium on Artificial Life and Robotics (AROB 29th 2024) (Internet), p.1097 - 1100, 2024/01

Toward faster 3D environment modeling based on feature extraction results from movies; Research overview and initiatives

Nakamura, Keita*; Hanari, Toshihide; Madokoro, Hirokazu*; Imabuchi, Takashi; Kawabata, Kuniaki; Nix, S.*; Doi, Akio*

no journal, , 

This paper introduces a research effort for faster 3D environment modeling of the workspace for decommissioning activities at the Fukushima Daiichi Nuclear Power Plant, applying as input video images shot during an investigation of the reactor containment vessel and reactor building. Especially, we construct a system that allows the selection of a 3D reconstruction method with as much information as possible within a specified time limit. We challenge this study with three methods: photogrammetry, simulation, and AI technology. Finally, we aim to integrate the results of each research to build a prototype system that automatically generates a more informative 3D reconstruction result within a specified time and according to the extracted feature values.

Development of exposure reduction technologies by digitalization of environment and radioactive source distribution; Understanding and 3D modeling of working environmental data by using deep learning

Doi, Akio*; Yamashita, Meguru*; Takahashi, Hiroki*; Kato, Toru*; Imabuchi, Takashi; Hanari, Toshihide; Tanifuji, Yuta; Ito, Rintaro

no journal, , 

no abstracts in English

None

Kato, Toru*; Takahashi, Hiroki*; Yamashita, Meguru*; Doi, Akio*; Imabuchi, Takashi

no journal, , 

None

Takahashi, Hiroki*; Kato, Toru*; Yamashita, Meguru*; Doi, Akio*; Imabuchi, Takashi

no journal, ,