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HPC Technology Promotion Office
JAEA-Review 2023-018, 159 Pages, 2023/12
JAEA-Review-2023-018.pdf:13.62MB
Japan Atomic Energy Agency (JAEA) conducts research and development (R&D) in various fields related to nuclear power as a comprehensive institution of nuclear energy R&Ds, and utilizes computational science and technology in many activities. Over the past 10 years or so, the publication of papers utilizing computational science and technology at JAEA has accounted for about 20 percent of the total publications each fiscal year. The supercomputer system of JAEA has become an important infrastructure to support computational science and technology. In FY2022, the system was used for R&D of light water reactors, high-temperature gas reactors, and fast reactors to contribute to carbon neutrality as a priority issue, as well as for JAEA's major projects such as Various R&D related to nuclear science and technology, R&D related to the response to the accident at TEPCO's Fukushima Daiichi Nuclear Power Station, Development of technology for treatment and disposal of high-level radioactive waste, Support of nuclear safety regulation and nuclear disaster prevention, and safety research for this purpose. This report presents a great number of R&D results accomplished by using the system in FY2022, as well as user support, operational records and overviews of the system, and so on.
states in the electronic structure of the intermediate-valence superconductor CeIr
Fujimori, Shinichi; Kawasaki, Ikuto; Takeda, Yukiharu; Yamagami, Hiroshi; Sasabe, Norimasa*; Sato, Yoshiki*; Shimizu, Yusei*; Nakamura, Ai*; Maruya, A.*; Homma, Yoshiya*; et al.
Electronic Structure (Internet), 5(4), p.045009_1 - 045009_7, 2023/11
Takeda, Takeshi
JAEA-Data/Code 2023-012, 75 Pages, 2023/10
JAEA-Data-Code-2023-012.pdf:4.45MB
An experiment denoted as TR-LF-15 was conducted on June 11, 2014 using the Large Scale Test Facility (LSTF) in the Rig of Safety Assessment-V (ROSA-V) Program. The ROSA/LSTF experiment TR-LF-15 simulated accident management (AM) actions during a station blackout transient with TMLB' scenario with pump seal loss-of-coolant accident (LOCA) in a pressurized water reactor (PWR). This scenario is featured by loss of auxiliary feedwater functions. The pump seal LOCA was simulated by a 0.1% cold leg break. The test assumptions included total failure of both high pressure injection system and low pressure injection system of emergency core cooling system (ECCS). Also, it was presumed non-condensable gas (nitrogen gas) inflow to the primary system from accumulator (ACC) tanks of ECCS. When steam generator (SG) secondary-side collapsed liquid level dropped to a certain low liquid level, the primary pressure turned to rise. After the SG secondary-side became voided, the safety valve of a pressurizer cyclically opened which led to loss of primary coolant. Core uncovery thus took place owing to core boil-off at high pressure. When an increase of 10 K was confirmed in cladding surface temperature of simulated fuel rods, SG secondary-side depressurization was started as the first AM action. At that time, the safety valves in both SGs were fully opened. Primary depressurization was initiated by completely opening the pressurizer safety valve as the second AM action with some delay after the first AM action onset. When the SG secondary-side pressure lowered to 1.0 MPa following the first AM action, water was injected into the secondary-side of both SGs via feedwater lines with low-head pumps as the third AM action. A reduction in the primary pressure was accelerated because the heat removal from the SG secondary-side system resumed shortly after the third AM action initiation.
Shimada, Taro; Sasagawa, Tsuyoshi; Miwa, Kazuji; Takai, Shizuka; Takeda, Seiji
Proceedings of International Conference on Environmental Remediation and Radioactive Waste Management (ICEM2023) (Internet), 7 Pages, 2023/10
Nuclear regulatory inspection should be performed on the basis of the risk information during the decommissioning phase of the nuclear power plant. However, it is difficult because the methodology for quantitatively assessing the radiation exposure risk during decommissioning activities has not been established. Therefore, a decommissioning risk assessment code, DecAssess-R, has been developed based on the decommissioning safety assessment code, DecAssess, which creates event trees from initiating events and evaluates the radiation risk resulting from public exposure dose for each accident sequence. The assessment took into account that mobile radioactive inventories that can be easily dispersed in the work area, such as radioactive dust accumulated in HEPA filters attached to a contamination control enclosure, will fluctuate with the progress of the decommissioning work. Initiating events were selected based on the investigation of accidents and malfunctions during dismantling, disassembly, and component replacement activities around the world, and event trees were created from the initiating events to indicate the progress scenario. The frequencies of occurrence were determined with reference to general industry data in addition to the above accidents and malfunctions, and the probabilities of event progression were determined with reference to failure data during the operation phase. The exposure risks during dismantling of components in the reference BWR were evaluated. As a result, the public exposure dose was maximum in case of fire during dismantling of reactor internals and fire spread to combustibles and filters, including radioactivity temporarily stored in the work area. The exposure risk was also maximum because the probability of occurrence of this accident sequence was greater than that of other scenarios.
Yokoyama, Miki*; Onuma, Susumu*; Osawa, Hideaki; Otomo, Shoji*; Hirose, Yukio*
Humanities & Social Sciences Communications (Internet), 10(1), p.623_1 - 623_10, 2023/09
This study demonstrates that a decision-making process utilising "the veil of ignorance" concept, defined in process terms as beginning from a blank slate encompassing the entire country as potential sites and shortlisting candidate sites based on scientific (geological) safety, promotes public acceptance of siting a repository for the geological disposal of high-level radioactive waste and fosters procedural fairness.
Hironaka, Kota; Lee, J.; Koizumi, Mitsuo; Ito, Fumiaki*; Hori, Junichi*; Terada, Kazushi*; Sano, Tadafumi*
Nuclear Instruments and Methods in Physics Research A, 1054, p.168467_1 - 168467_5, 2023/09
Times Cited Count：0 Percentile：0.02(Instruments & Instrumentation)Center for Computational Science & e-Systems
JAEA-Evaluation 2023-001, 38 Pages, 2023/07
JAEA-Evaluation-2023-001.pdf:1.04MB
Research on advanced computational science for nuclear applications, based on "the plan to achieve the medium- and long-term goal of the Japan Atomic Energy Agency", has been performed by Center for Computational Science & e-Systems (CCSE), Japan Atomic Energy Agency. CCSE established a committee consisting of external experts and authorities which evaluates and advises toward the future research and development. This report summarizes the results of the R&D performed by CCSE in FY2022 (April 1st, 2022 - March 31st, 2023) and their evaluation by the committee.
Tsai, T.-H.; Sasaki, Shinji; Maeda, Koji
Journal of Nuclear Science and Technology, 60(6), p.715 - 723, 2023/06
Times Cited Count：1 Percentile：31.61(Nuclear Science & Technology)Nemoto, Takahiro; Arakawa, Ryoki; Kawakami, Satoru; Nagasumi, Satoru; Yokoyama, Keisuke; Watanabe, Masashi; Onishi, Takashi; Kawamoto, Taiki; Furusawa, Takayuki; Inoi, Hiroyuki; et al.
JAEA-Technology 2023-005, 33 Pages, 2023/05
JAEA-Technology-2023-005.pdf:5.25MB
During shut down of the HTTR (High Temperature engineering Test Reactor) RS-14 cycle, an increasing trend of filter differential pressure for the helium gas circulator was observed. In order to investigate this phenomenon, the blower of the primary helium purification system was disassembled and inspected. As a result, it is clear that the silicon oil mist entered into the primary coolant due to the deterioration of the charcoal filter performance. The replacement and further investigation of the filter are planning to prevent the reoccurrence of the same phenomenon in the future.
Onodera, Naoyuki; Idomura, Yasuhiro; Hasegawa, Yuta; Asahi, Yuichi; Inagaki, Atsushi*; Shimose, Kenichi*; Hirano, Kohin*
Keisan Kogaku Koenkai Rombunshu (CD-ROM), 28, 4 Pages, 2023/05
We have developed a multi-scale wind simulation code named CityLBM that can resolve entire cities to detailed streets. CityLBM enables a real time ensemble simulation for several km square area by applying the locally mesh-refined lattice Boltzmann method on GPU supercomputers. On the other hand, real-world wind simulations contain complex boundary conditions that cannot be modeled, so data assimilation techniques are needed to reflect observed data in the simulation. This study proposes an optimization method for ground surface temperature bias based on an ensemble Kalman filter to reproduce wind conditions within urban city blocks. As a verification of CityLBM, an Observing System Simulation Experiment (OSSE) is conducted for the central Tokyo area to estimate boundary conditions from observed near-surface temperature values.
Ota, Hirokazu*; Ogata, Takanari*; Yamano, Hidemasa; Futagami, Satoshi; Shimada, Sadae*; Yamada, Yumi*
Proceedings of 30th International Conference on Nuclear Engineering (ICONE30) (Internet), 8 Pages, 2023/05
Li, C.-Y.; Watanabe, Akira*; Uchibori, Akihiro; Okano, Yasushi
Proceedings of 30th International Conference on Nuclear Engineering (ICONE30) (Internet), 10 Pages, 2023/05
Collaborative Laboratories for Advanced Decommissioning Science; National Institute of Maritime, Port and Aviation Technology*
JAEA-Review 2022-070, 70 Pages, 2023/03
JAEA-Review-2022-070.pdf:5.27MB
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 FY2020, this report summarizes the research results of the "Research and development of the sample-return technique for fuel debris using the unmanned underwater vehicle" conducted in FY2021. The present study aims to develop a fuel debris sampling device that comprises a neutron detector with radiation resistance and enhanced neutron detection efficiency, an end-effector with powerful cutting and collection capabilities, and a manipulator under the Japan-UK joint research team. We will also develop a fuel debris sampling system that can be mounted on an unmanned vehicle. In addition, we will develop a positioning system to identify the system position, and a technique to project the counting information of optical cameras, sonar, and neutron detectors to be developed ...
Asahi, Yuichi; Onodera, Naoyuki; Hasegawa, Yuta; Shimokawabe, Takashi*; Shiba, Hayato*; Idomura, Yasuhiro
Boundary-Layer Meteorology, 186(3), p.659 - 692, 2023/03
Times Cited Count：0 Percentile：0.01(Meteorology & Atmospheric Sciences)We develop a Transformer-based deep learning model to predict the plume concentrations in the urban area under uniform flow conditions. Our model has two distinct input layers: Transformer layers for sequential data and convolutional layers in convolutional neural networks (CNNs) for image-like data. Our model can predict the plume concentration from realistically available data such as the time series monitoring data at a few observation stations and the building shapes and the source location. It is shown that the model can give reasonably accurate prediction with orders of magnitude faster than CFD simulations. It is also shown that the exactly same model can be applied to predict the source location, which also gives reasonable prediction accuracy.
Yoshida, Yukihiko
IL Nuovo Cimento, 46(2), p.33_1 - 33_8, 2023/03
Fukaya, Yuji; Goto, Minoru; Ohashi, Hirofumi
Annals of Nuclear Energy, 181, p.109534_1 - 109534_10, 2023/02
Times Cited Count：0 Percentile：0.01(Nuclear Science & Technology)Feasibility of reprocessing of High Temperature Gas-cooled Reactor (HTGR) spent fuel by existing Plutonium Uranium Redox EXtraction (PUREX) plant and technology has been investigated. The spent fuel dissolved solution includes approximately 3 times amount of uranium-235 and 1.5 times amount of protonium because of the 3 times higher burnup compared with that of Light Water Reactor (LWR). Then, the heavy metal of the spent fuel is planned to be diluted to 3.1 times by depleted uranium to satisfy the limitation of Rokkasho Reprocessing Plant (RRP) plant. In the present study, recoverability of uranium and plutonium with the dilution is confirmed by a simulation with a reprocessing process calculation code. Moreover, the case without the dilution from the economic perspective is investigated. As a result, the feasibility is confirmed without the dilution, and it is expected that the reprocessed amount is reduced to 1/3 compared with a diluted case even though the facility should be optimized from the perspective of mass flow and criticality.
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.
HPC Technology Promotion Office
JAEA-Review 2022-035, 219 Pages, 2023/01
JAEA-Review-2022-035.pdf:10.94MB
Japan Atomic Energy Agency (JAEA) conducts research and development (R&D) in various fields related to nuclear power as a comprehensive institution of nuclear energy R&Ds, and utilizes computational science and technology in many activities. As shown in the fact that about 20 percent of papers published by JAEA are concerned with R&D using computational science, the supercomputer system of JAEA has become an important infrastructure to support computational science and technology. In FY2021, the system was used for R&D aiming to restore Fukushima (environmental recovery and nuclear installation decommissioning) as a priority issue, as well as for JAEA's major projects such as research and development of fast reactor cycle technology, research for safety improvement in the field of nuclear energy, and basic nuclear science and engineering research. This report presents a great number of R&D results accomplished by using the system in FY2021, as well as user support, operational records and overviews of the system, and so on.
Davies, S. J. C.*; Bolea-Alamanac, B.*; Endo, Kaori*; Yamamoto, Yu*; Yamasaki, Shudo*; Malins, A.; Evans, J.*; Sullivan, S.*; Ando, Shuntaro*; Nishida, Atsushi*; et al.
Journal of Transport & Health, 28, p.101564_1 - 101564_11, 2023/01
Hasegawa, Yuta; Onodera, Naoyuki; Asahi, Yuichi; Idomura, Yasuhiro
Dai-36-Kai Suchi Ryutai Rikigaku Shimpojiumu Koen Rombunshu (Internet), 5 Pages, 2022/12
This study implemented and tested the ensemble data assimilation (DA) of turbulent flows using the lattice Boltzmann method and the local ensemble transform Kalman filter (LBM-LETKF). The computational code was implemented fully on GPUs. The test was carried out for the 3D turbulent flow around a square cylinder with 
meshes and 32 ensemble members using 32 GPUs. The time interval of the DA in the test was a half of the period of the Kalman vortex shedding. The normalized mean absolute errors (NMAE) of the lift coefficient were 132%, 148%, and 13.2% for the non-DA case, the nudging case (a simpler DA algorithm), and the LETKF case, respectively. It was found that the LETKF achieved good DA accuracy even though the observation was not frequent enough for the small scale turbulence, while the nudging showed systematic delays in its solution, and could not keep the DA accurately.
