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Center for Computational Science & e-Systems
JAEA-Evaluation 2026-003, 41 Pages, 2026/06
JAEA-Evaluation-2026-003.pdf:1.08MB
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 FY2024 (April 1st, 2024 - March 31st, 2025) and their evaluation by the committee.
Zheng, X.; Tamaki, Hitoshi; Shibamoto, Yasuteru; Maruyama, Yu
Nihon Genshiryoku Gakkai-Shi ATOMO
, 66(11), p.565 - 569, 2024/11
no abstracts in English
Center for Computational Science & e-Systems
JAEA-Evaluation 2024-001, 40 Pages, 2024/10
JAEA-Evaluation-2024-001.pdf:1.46MB
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 FY2023 (April 1st, 2023 - March 31st, 2024) and their evaluation by the committee.
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HRLSawada, Atsushi; Sakamoto, Kazuhiko*; Watahiki, Takanori*; Imai, Hisashi*
SKB P-17-06, 154 Pages, 2023/08
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.
Center for Computational Science & e-Systems
JAEA-Evaluation 2022-004, 38 Pages, 2022/11
JAEA-Evaluation-2022-004.pdf:1.38MB
Research on advanced computational science for nuclear applications, based on "the plan to achieve the mid- 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 FY2021 (April 1st, 2021 - March 31st, 2022) and their evaluation by the committee.
Center for Computational Science & e-Systems
JAEA-Evaluation 2022-003, 61 Pages, 2022/11
JAEA-Evaluation-2022-003.pdf:1.42MB
JAEA-Evaluation-2022-003-appendix(CD-ROM).zip:6.16MB
Japan Atomic Energy Agency (hereinafter referred to as "JAEA") consults an assessment committee, "Evaluation Committee of Research Activities for Computational Science and Technology Research" (hereinafter referred to as "Committee") for result and in-advance evaluation of "Computational Science and Technology Research", in accordance with "General Guideline for the Evaluation of Government Research and Development (R&D) Activities" by Cabinet Office, Government of Japan, "Guideline for Evaluation of R&D in Ministry of Education, Culture, Sports, Science and Technology" and "Regulation on Conduct for Evaluation of R&D Activities" by the JAEA. In response to the JAEA's request, the Committee assessed the research program of the Center for Computational Science and e-Systems (hereinafter referred to as "CCSE"). The Committee evaluated the management and research activities of the CCSE based on explanatory documents prepared by the CCSE, and oral presentations with questions-and answers.
Togawa, Orihiko; Okura, Takehisa; Kimura, Masanori; Nagai, Haruyasu
JAEA-Review 2021-021, 61 Pages, 2021/11
JAEA-Review-2021-021.pdf:3.72MB
Triggered by the Fukushima Daiichi Nuclear Power Station accident, there have been a lot of arguments among various situations and levels about utilization of atmospheric dispersion models for a nuclear emergency preparedness and response. Most of these arguments, however, were alternative and extreme discussions on whether predictions by computational models could be applied or not for protective measures in a nuclear emergency, and it was hard to say that these arguments were politely conducted, based on scientific verification in an emergency response. It was known, on the other hand, that there were not a few potential users of atmospheric dispersion models and/or calculation results by the models within the Japan Atomic Energy Agency (JAEA) and outside. However, they seemed to have a lack of understanding and a misunderstanding on proper use of different kinds of atmospheric dispersion models. This report compares an outline of models and calculation method in atmospheric dispersion models for a nuclear emergency preparedness and response, with a central focus on the models which have been developed and used in the JAEA. Examples of calculations by these models are also described in the report. This report aims at contributing to future consideration and activities for potential users of atmospheric dispersion models within the JAEA and outside.
Center for Computational Science & e-Systems
JAEA-Evaluation 2021-001, 66 Pages, 2021/11
JAEA-Evaluation-2021-001.pdf:1.66MB
Research on advanced computational science for nuclear applications, based on "the plan to achieve the mid- 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 does research evaluation and advice for the assistance of the future research and development. This report summarizes the results of the R&D performed by CCSE in FY2020 (April 1st, 2020 - March 31st, 2021), the results expected at the end of the 3rd mid and long-term goal period, and the evaluation by the committee on them.
Center for Computational Science & e-Systems
JAEA-Evaluation 2020-002, 37 Pages, 2020/12
JAEA-Evaluation-2020-002.pdf:1.59MB
Research on advanced computational science for nuclear applications, based on "the plan to achieve the mid and long term goal of the Japan Atomic Energy Agency", has been performed at Center for Computational Science & e-Systems (CCSE), Japan Atomic Energy Agency. CCSE established a committee consisting of outside experts and authorities which does research evaluation and advice for the assistance of the future research and development. This report summarizes the results of the R&D performed at CCSE in FY2019 (April 1st, 2019 - March 31st, 2020) and the evaluation by the committee on them.
Zheng, X.; Mandelli, D.*; Alfonsi, A.*; Smith, C.*; Sugiyama, Tomoyuki
Proceedings of 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL 2020 and PSAM-15) (Internet), p.2176 - 2183, 2020/11
Cs concentrations from the Fukushima Daiichi Nuclear Power Plant accident, phase III; Simulation with an identical source term and meteorological field at 1-km resolutionSato, Yosuke*; Sekiyama, Tsuyoshi*; Fang, S.*; Kajino, Mizuo*; Qu
rel, A.*; Qulo, D.*; Kondo, Hiroaki*; Terada, Hiroaki; Kadowaki, Masanao; Takigawa, Masayuki*; et al.
Atmospheric Environment; X (Internet), 7, p.100086_1 - 100086_12, 2020/10
The third model intercomparison project for investigating the atmospheric behavior of Cs emitted during the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident (FDNPP-MIP) was conducted. A finer horizontal grid spacing (1 km) was used than in the previous FDNPP-MIP. Nine of the models used in the previous FDNPP-MIP were also used, and all models used identical source terms and meteorological fields. Our analyses indicated that most of the observed high atmospheric Cs concentrations were well simulated, and the good performance of some models improved the performance of the multi-model ensemble. The analyses also confirmed that the use of a finer grid resolution resulted in the meteorological field near FDNPP being better reproduced. The good representation of the wind field resulted in the reasonable simulation of the narrow distribution of high deposition amount to the northwest of FDNPP and the reduction of the overestimation over the area to the south of FDNPP. In contrast, the performance of the models in simulating plumes observed over the Nakadori area, the northern part of Gunma, and the Tokyo metropolitan area was slightly worse.
Sheikh, M. A. R.*; Liu, X.*; Matsumoto, Tatsuya*; Morita, Koji*; Guo, L.*; Suzuki, Toru*; Kamiyama, Kenji
Energies (Internet), 13(19), p.5018_1 - 5018_15, 2020/10
Times Cited Count：13 Percentile：30.19(Energy & Fuels)Yamashita, Takuya; Sawada, Noriyoshi*
JAEA-Research 2019-010, 227 Pages, 2020/03
JAEA-Research-2019-010.pdf:21.44MBJAEA-Research-2019-010(errata).pdf:0.5MB
In order to support the decontamination activities proceeded by the national government and municipalities in terms of technology, we have developed a simulation system "RESET" which predicts the effect of decontamination. We also developed a "two-component model" for the purpose of predicting long-term changes in the air dose rate. We use these tools to perform decontamination simulation and predictive analysis of the air dose rate after decontamination, and provide information to the national government and municipalities aiming for reconstruction. In this report, the verification result of the prediction methods implemented using actual measurement data obtained in the "Decontamination model demonstration project in difficult-to-return zone" and "Survey result on transition of air dose rate after decontamination model demonstration project" conducted by Ministry of the Environment. In addition, the decontamination simulation conducted for the entire difficult-to-return area and the results of future prediction of the air dose rate after decontamination are shown.
Furuta, Takuya; El Basha, D.*; Iyer, S. S. R.*; Correa Alfonso, C. M.*; Bolch, W. E.*
Journal of Radiological Protection, 39(3), p.825 - 837, 2019/09
Times Cited Count：3 Percentile：21.87(Environmental Sciences)Despite large variation of human eye, only one computational eye model has been adopted in almost all the radiation transport simulation studies. We thus adopted a new scalable and deformable eye model and studied the radiation exposure by electrons, photons, and neutrons in the standard radiation fields such as AP, PA, RLAT, ROT, by using Monte Carlo radiation transport code PHITS. We computed the radiation exposure for 5 eye models (standard, large, small, myopic, hyperopic) and analyzed influence of absorbed dose in ocular structures on eye size and shape. Dose distribution of electrons is conformal and therefore the absorbed doses in ocular structures depend on the depth location of each ocular structure. We thus found a significant variation of the absorbed doses for each ocular structure for electron exposure due to change of the depth location affected by eye size and shape. On the other hand only small variation was observed for photons and neutrons exposures because of less conformal dose distribution of those particles.
Malins, A.; Kurikami, Hiroshi; Kitamura, Akihiro; Machida, Masahiko
Remediation Measures for Radioactively Contaminated Areas, p.259 - 272, 2019/00
Kinase, Sakae; Mohammadi, A.*; G
mez-Ros, J.-M.*
Computational Anatomical Animal Models; Methodological Developments and Research Applications, p.5_1 - 5_9, 2018/12
Times Cited Count：0 Percentile：0.00(Anatomy & Morphology)Ono, Ayako; Suzuki, Takayuki*; Yoshida, Hiroyuki
Proceedings of 12th International Topical Meeting on Nuclear Reactor Thermal-Hydraulics, Operation and Safety (NUTHOS-12) (USB Flash Drive), 9 Pages, 2018/10
The mechanism of Critical Heat Flux (CHF) remains to be clarified, even though it is important to evaluate the CHF for super high heat flux components such as light water reactors (LWRs). Some theoretical models to predict the CHF is proposed so far. A macrolayer formation model which is proposed in order to predict the CHF based on the macrolayer dryout model. In this model, it is assumed that the liquid is captured inside vapor mass at coalescence. In this study, the verification of the assumption of a macrolayer formation model by the numerical simulation of CMFD code, TPFIT, from the view point of hydrodynamics.
Cs plumes from the Fukushima Daiichi Nuclear Power Plant; Evaluation of the model intercomparison data of the Science Council of JapanKitayama, Kyo*; Morino, Yu*; Takigawa, Masayuki*; Nakajima, Teruyuki*; Hayami, Hiroshi*; Nagai, Haruyasu; Terada, Hiroaki; Saito, Kazuo*; Shimbori, Toshiki*; Kajino, Mizuo*; et al.
Journal of Geophysical Research; Atmospheres, 123(14), p.7754 - 7770, 2018/07
Times Cited Count：29 Percentile：63.81(Meteorology & Atmospheric Sciences)We compared seven atmospheric transport model results for Cs released during the Fukushima Daiichi Nuclear Power Plant accident. All the results had been submitted for a model intercomparison project of the Science Council of Japan in 2014. We assessed model performance by comparing model results with observed hourly atmospheric concentrations of Cs, focusing on nine plumes over the Tohoku and Kanto regions. The results showed that model performance for Cs concentrations was highly variable among models and plumes. We also assessed model performance for accumulated Cs deposition. Simulated areas of high deposition were consistent with the plume pathways, though the models that best simulated Cs concentrations were different from those that best simulated deposition. The ensemble mean of all models consistently reproduced Cs concentrations and deposition well, suggesting that use of a multimodel ensemble results in more effective and consistent model performance.
Shen, X.*; Schlegel, J. P.*; Hibiki, Takashi*; Nakamura, Hideo
Nuclear Engineering and Design, 333, p.87 - 98, 2018/07
Times Cited Count：15 Percentile：32.21(Nuclear Science & Technology)