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Sato, Ikken; Yoshikawa, Shinji; Yamashita, Takuya; Cibula, M.*; Mizokami, Shinya*
Nuclear Engineering and Design, 404, p.112205_1 - 112205_21, 2023/04
Times Cited Count:0Based on updated knowledge from plant-internal investigations, experiments and model simulations until now, the in-vessel phase of Fukushima-Daiichi Nuclear Power Station Unit 2 was analyzed using the MAAP code. In Unit 2, it is considered that the core material enthalpy was relatively low when it relocated to the lower plenum of the pressure vessel, then, cooled by the coolant and solidified there. Although the MAAP code tended to underestimate the degree of core-material oxidation during the relocation, this probable underestimation was compensated for by an existing study that was considered more reliable, so that more realistic debris conditions in the lower plenum could be obtained. Basic validity of the former prediction of the Unit 2 accident progression behavior was confirmed and detailed boundary condition for the later phase was provided. This boundary condition should be utilized for future studies addressing debris reheating process leading to lower head failure and debris relocation toward the pedestal.
Shimomura, Kenta; Yamashita, Takuya; Nagae, Yuji
JAEA-Data/Code 2022-012, 270 Pages, 2023/03
In a light water reactor, which is a commercial nuclear power plant, a severe accident such as loss of cooling function in the reactor pressure vessel (RPV) and exposure of fuel rods due to a drop in the water level in the reactor can occur when a trouble like loss of all AC power occurs. In the event of such a severe accident, the RPV may be damaged due to in-vessel conditions (temperature, molten materials, etc.) and leakage of radioactive materials from the reactor may occur. Verification and estimation of the process of RPV damage, molten fuel debris spillage and expansion, etc. during accident progression will provide important information for decommissioning work. Possible causes of RPV failure include failure due to loads and restraints applied to the RPV substructure (mechanical failure), failure due to the current eutectic state of low-melting metals and high-melting oxides with the RPV bottom members (failure due to inter-material reactions), and failure near the melting point of the structural members at the RPV bottom. Among the failure factors, mechanical failure is verified by numerical analysis (thermal hydraulics and structural analysis). When conducting such a numerical analysis, the heat transfer properties (thermal conductivity, specific heat, density) and material properties (thermal conductivity, Young's modulus, Poisson's ratio, tensile, creep) of the materials (zirconium, boron carbide, stainless steel, nickel-based alloy, low alloy steel, etc.) constituting the RPV and in-core structures to near the melting point are required to evaluate the creep failure of the RPV. In this document, we compiled data on the properties of base materials up to the melting point of each material constituting the RPV and in-core structures, based on published literature. In addition, because welds exist in the RPV and in-core structures, the data on welds are also included in this report, although they are limited.
Madokoro, Hiroshi; Yamashita, Takuya; Gaus-Liu, X.*; Cron, T.*; Fluhrer, B.*; Sato, Ikken; Mizokami, Shinya*
Nuclear Technology, 209(2), p.144 - 168, 2023/02
Times Cited Count:0 Percentile:0.01(Nuclear Science & Technology)Yamashita, Takuya; Honda, Takeshi*; Mizokami, Masato*; Nozaki, Kenichiro*; Suzuki, Hiroyuki*; Pellegrini, M.*; Sakai, Takeshi*; Sato, Ikken; Mizokami, Shinya*
Nuclear Technology, 26 Pages, 2023/00
Times Cited Count:0Yamashita, Takuya; Sato, Takumi; Madokoro, Hiroshi; Nagae, Yuji
Annals of Nuclear Energy, 173, p.109129_1 - 109129_15, 2022/08
Times Cited Count:0 Percentile:0.01(Nuclear Science & Technology)Yamashita, Takuya; Madokoro, Hiroshi; Sato, Ikken
Journal of Nuclear Engineering and Radiation Science, 8(2), p.021701_1 - 021701_13, 2022/04
Pshenichnikov, A.; Shibata, Hiroki; Yamashita, Takuya; Nagae, Yuji; Kurata, Masaki
Journal of Nuclear Science and Technology, 59(3), p.267 - 291, 2022/03
Times Cited Count:0 Percentile:0.01(Nuclear Science & Technology)Madokoro, Hiroshi; Yamashita, Takuya; Sato, Ikken; Gaus-Liu, X.*; Cron, T.*; Fluhrer, B.*; Stngle, R.*; Wenz, T.*; Vervoortz, M.*; Mizokami, Shinya
Proceedings of 19th International Topical Meeting on Nuclear Reactor Thermal Hydraulics (NURETH-19) (Internet), 16 Pages, 2022/03
Ina, Takuya*; Idomura, Yasuhiro; Imamura, Toshiyuki*; Yamashita, Susumu; Onodera, Naoyuki
Proceedings of 12th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems ScalA21) (Internet) , 8 Pages, 2021/11
Times Cited Count:0 Percentile:0.02A new mixed-precision preconditioner based on the iterative refinement (IR) method is developed for preconditioned conjugate gradient (P-CG) and multigrid preconditioned conjugate gradient (MGCG) solvers in a multi-phase thermal-hydraulic CFD code JUPITER. In the IR preconditioner, all data is stored in FP16 to reduce memory access, while all computation is performed in FP32. The hybrid FP16/32 implementation keeps the similar convergence property as FP32, while the computational performance is close to FP16. The developed solvers are optimized on Fugaku (A64FX), and applied to ill-conditioned matrices in JUPITER. The P-CG and MGCG solvers with the new IR preconditioner show excellent strong scaling up to 8,000 nodes, and at 8,000 nodes, they are respectively accelerated up to 4.86 and 2.39
from the conventional ones on Oakforest-PACS (KNL).
Yamashita, Takuya
Enerugi Rebyu, 41(4), p.14 - 16, 2021/03
no abstracts in English
Yamashita, Takuya; Sato, Ikken; Honda, Takeshi*; Nozaki, Kenichiro*; Suzuki, Hiroyuki*; Pellegrini, M.*; Sakai, Takeshi*; Mizokami, Shinya*
Nuclear Technology, 206(10), p.1517 - 1537, 2020/10
Times Cited Count:11 Percentile:88.08(Nuclear Science & Technology)Idomura, Yasuhiro; Onodera, Naoyuki; Yamada, Susumu; Yamashita, Susumu; Ina, Takuya*; Imamura, Toshiyuki*
Supa Kompyuteingu Nyusu, 22(5), p.18 - 29, 2020/09
A communication avoiding multigrid preconditioned conjugate gradient method (CAMGCG) is applied to the pressure Poisson equation in a multiphase CFD code JUPITER, and its computational performance and convergence property are compared against the conventional Krylov methods. The CAMGCG solver has robust convergence properties regardless of the problem size, and shows both communication reduction and convergence improvement, leading to higher performance gain than CA Krylov solvers, which achieve only the former. The CAMGCG solver is applied to extreme scale multiphase CFD simulations with 90 billion DOFs, and its performance is compared against the preconditioned CG solver. In this benchmark, the number of iterations is reduced to , and
speedup is achieved with keeping excellent strong scaling up to 8,000 nodes on the Oakforest-PACS.
Abe, Yuta; Yamashita, Takuya; Sato, Ikken; Nakagiri, Toshio; Ishimi, Akihiro
Journal of Nuclear Engineering and Radiation Science, 6(2), p.021113_1 - 021113_9, 2020/04
Yamashita, Takuya; Sawada, Noriyoshi*
JAEA-Research 2019-010, 227 Pages, 2020/03
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.
Yamashita, Takuya; Sato, Ikken
Proceedings of 9th Conference on Severe Accident Research (ERMSAR 2019) (Internet), 13 Pages, 2019/03
For decommissioning the Fukushima Daiichi Nuclear Power Station Accident (1F), understanding the final distribution of core materials and their characteristics is important. These characteristics obviously depend on the accident progression in each of the units. However, a large uncertainty is present in BWR accident progression behavior. This uncertainty, which was clarified by the MAAP-MELCOR Crosswalk, cannot be resolved with existing experimental data and knowledge. Once coolant is lost from the BWR core for some time, the following scenario can be divided symbolically into TMI-2 Like Path and Continuous Drainage Path. Main uncertainties for this branching point are summarized as two questions: How is gas permeability of high-temperature degraded core approaching fuel melting ? (Q1). How is downward relocation of hot core materials before fuel melting and its effect on structure heating? (Q2). To address these questions, the core-material melting and relocation experiments were conducted. In the CMMR-4 test, useful information on core state just before slumping was obtained. Presence of macroscopic gas permeability of the core approaching ceramic fuel melting was confirmed (A1) and the fuel columns stayed standing suggesting that collapse of fuel columns, which is likely in the reactor condition, would not allow effective relocation of the hottest fuel away to the bottom of the core thereby limiting the core maximum temperature and significantly heating the support structures (A2).
Yamashita, Takuya; Yamashita, Hayato; Nagae, Yuji
Tetsu To Hagane, 105(1), p.96 - 104, 2019/01
Times Cited Count:1 Percentile:7.95(Metallurgy & Metallurgical Engineering)no abstracts in English
Idomura, Yasuhiro; Ina, Takuya*; Yamashita, Susumu; Onodera, Naoyuki; Yamada, Susumu; Imamura, Toshiyuki*
Proceedings of 9th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA 2018) (Internet), p.17 - 24, 2018/11
Times Cited Count:6 Percentile:91.99A communication avoiding (CA) multigrid preconditioned conjugate gradient method (CAMGCG) is applied to the pressure Poisson equation in a multiphase CFD code JUPITER, and its computational performance and convergence property are compared against CA Krylov methods. In the JUPITER code, the CAMGCG solver has robust convergence properties regardless of the problem size, and shows both communication reduction and convergence improvement, leading to higher performance gain than CA Krylov solvers, which achieve only the former. The CAMGCG solver is applied to extreme scale multiphase CFD simulations with billion DOFs, and it is shown that compared with a preconditioned CG solver, the number of iterations is reduced to
, and
speedup is achieved with keeping excellent strong scaling up to 8,000 nodes on the Oakforest-PACS.
Yamashita, Takuya; Sato, Ikken; Abe, Yuta; Nakagiri, Toshio; Ishimi, Akihiro; Nagae, Yuji
Proceedings of International Conference on Dismantling Challenges; Industrial Reality, Prospects and Feedback Experience (DEM 2018) (Internet), 11 Pages, 2018/10
no abstracts in English
Abe, Yuta; Yamashita, Takuya; Sato, Ikken; Nakagiri, Toshio; Ishimi, Akihiro; Nagae, Yuji
Proceedings of 26th International Conference on Nuclear Engineering (ICONE-26) (Internet), 9 Pages, 2018/07
Yamashita, Takuya; Sato, Ikken; Abe, Yuta; Nakagiri, Toshio; Ishimi, Akihiro; Nagae, Yuji
Proceedings of 12th International Conference of the Croatian Nuclear Society; Nuclear Option for CO Free Energy Generation (USB Flash Drive), p.109_1 - 109_15, 2018/06
no abstracts in English