Novel mechanical manipulator for efficient fuel debris retrieval (Contract research); FY2021 Nuclear Energy Science & Technology and Human Resource Development Project

Collaborative Laboratories for Advanced Decommissioning Science; The University of Tokyo*

JAEA-Review 2022-040, 70 Pages, 2023/01

JAEA-Review-2022-040.pdf:3.17MB

The Collaborative Laboratories for Advanced Decommissioning Science (CLADS), Japan Atomic Energy Agency (JAEA), had been conducting the Nuclear Energy Science & Technology and Human Resource Development Project (hereafter referred to "the Project") in FY2021. The Project aims to contribute to solving problems in the nuclear energy field represented by the decommissioning of the Fukushima Daiichi Nuclear Power Station, Tokyo Electric Power Company Holdings, Inc. (TEPCO). For this purpose, intelligence was collected from all over the world, and basic research and human resource development were promoted by closely integrating/collaborating knowledge and experiences in various fields beyond the barrier of conventional organizations and research fields. The sponsor of the Project was moved from the Ministry of Education, Culture, Sports, Science and Technology to JAEA since the newly adopted proposals in FY2018. On this occasion, JAEA constructed a new research system where JAEA-academia collaboration is reinforced and medium-to-long term research/development and human resource development contributing to the decommissioning are stably and consecutively implemented. Among the adopted proposals in FY2021, this report summarizes the research results of the "Novel mechanical manipulator for efficient fuel debris retrieval" conducted in FY2021. The present study aims to the development of a collision-tolerant robotic manipulator with the mechanical variable impedance actuators in an unknown environment. Another research target is the system architecture of an artificial intelligence-based control method for efficient exploration and decommissioning. In addition to conducting an investigation in the area deep inside the aperture, which has been difficult with conventional investigations, we aim to recover pebble-shaped fuel debris at the bottom of the pedestal using a gripper at the tip of the manipulator.

Virtual environment for integrated design support (VINDS) for conceptual design of a space power reactor core

*; *; *; *; Kugo, Teruhiko;

PHYSOR 96: Int. Conf. on the Physics of Reactors, 1, p.B92 - B101, 1996/00

no abstracts in English

Neural network with an expert system for real-time nuclear power plant monitoring

Nabeshima, Kunihiko; Suzuki, Katsuo; E.Tuekcan*

SMORN-VII,Symp. on Nuclear Reactor Surveillance and Diagnostics,Vol. 1, 0, P. 4_1, 1995/00

no abstracts in English

A Study on intelligent nuclear systems(HASP: Human Acts Simulation Program); Progress report 1991

; Higuchi, Kenji; ; Kume, Etsuo; ; Ebihara, Kenichi

JAERI-M 92-198, 129 Pages, 1993/01

JAERI-M-92-198.pdf:3.93MB

no abstracts in English

What is the supercomputing ?

Genshiryoku Kogyo, 38(3), p.9 - 14, 1992/00

http://ci.nii.ac.jp/naid/40001074006

no abstracts in English

Multivariate analysis approach to predicting event timing based on temporal knowledge base for application to computerized system for radiological emergency response

Ishigami, Tsutomu; *; *; *; Kobayashi, Kensuke

Probabilistic Safety Assessment and Management,Vol. 2, p.947 - 952, 1991/00

no abstracts in English

Application of artifical intelligence to radiation control, I; Development of expert system for transport of radioactive material with UTI-LISP programming language

*; ; Ikezawa, Yoshio

Hoken Butsuri, 25, p.11 - 17, 1990/00

https://doi.org/10.5453/jhps.25.11

no abstracts in English

A Plan for intelligent robots at JAERI

UTNL-R-0232, p.20 - 25, 1989/00

no abstracts in English

Prediction of the operating control rod position of the HTTR with supervised machine learning

Ho, H. Q.; Nagasumi, Satoru; Shimazaki, Yosuke; Hamamoto, Shimpei; Iigaki, Kazuhiko; Goto, Minoru; Simanullang, I. L.*; Fujimoto, Nozomu*; Ishitsuka, Etsuo

no journal, ,