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Maruyama, Shuhei; Endo, Tomohiro*; Yamamoto, Akio*
Journal of Nuclear Science and Technology, 61(1), p.31 - 43, 2024/01
Times Cited Count：0 Percentile：0.01(Nuclear Science & Technology)This study investigated the feasibility of reducing the uncertainty associated with fast-reactor-core design by sharing an experimental database between different fields (e.g., reactor physics and radiation shielding) using data assimilation techniques. As the first step in this study, we focused on the ORNL sodium shielding experiment and investigated the possibility of using the experimental data to reduce the uncertainty in sodium void reactivity (SVR), which is the most important safety parameter for sodium-cooled fast reactors. A sensitivity analysis based on the Generalized Perturbation Theory was performed for the sodium shielding experiment. Using the sensitivity coefficients evaluated here and those of the sodium void reactivity previously evaluated by the JAEA, we showed that sodium shielding experimental data can contribute to the uncertainty reduction of SVR by adopting the cross-section adjustment method. Based on this study, the uncertainty reduction effect is expected to be significant, especially for SVR dominated by neutron-leakage phenomena. Although new reactor physics experimental data on SVR may be difficult to obtain, the results of this study suggest that data from sodium shielding experiments can partially substitute for this role. This study demonstrated the value of the mutual use of integral experimental data in fast reactor designs.
Hasegawa, Yuta; Onodera, Naoyuki; Asahi, Yuichi; Ina, Takuya; Imamura, Toshiyuki*; Idomura, Yasuhiro
Fluid Dynamics Research, 55(6), p.065501_1 - 065501_25, 2023/11
Times Cited Count：0 Percentile：0.01(Mechanics)We investigate the applicability of the data assimilation (DA) to large eddy simulations (LESs) based on the lattice Boltzmann method (LBM). We carry out the observing system simulation experiment of a two-dimensional (2D) forced isotropic turbulence, and examine the DA accuracy of the nudging and the local ensemble transform Kalman filter (LETKF) with spatially sparse and noisy observation data of flow fields. The advantage of the LETKF is that it does not require computing spatial interpolation and/or an inverse problem between the macroscopic variables (the density and the pressure) and the velocity distribution function of the LBM, while the nudging introduces additional models for them. The numerical experiments with 
grids and 10% observation noise in the velocity showed that the root mean square error of the velocity in the LETKF with 
observation points (
of the total grids) and 64 ensemble members becomes smaller than the observation noise, while the nudging requires an order of magnitude larger number of observation points to achieve the same accuracy. Another advantage of the LETKF is that it well keeps the amplitude of the energy spectrum, while only the phase error becomes larger with more sparse observation. From these results, it was shown that the LETKF enables robust and accurate DA for the 2D LBM with sparse and noisy observation data.
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.
Hasegawa, Yuta; Onodera, Naoyuki; Asahi, Yuichi; Idomura, Yasuhiro
Keisan Kogaku Koenkai Rombunshu (CD-ROM), 27, 4 Pages, 2022/06
We developed GPU implementation of ensemble data assimilation (DA) using the local ensemble transform Kalman filter (LETKF) with the lattice Boltzmann method (LBM). The performance test was carried out upto 32 ensembles of two-dimensional isotropic turbulence simulations using the D2Q9 LBM. The computational cost of the LETKF was less than or nearly equal to that of the LBM upto eight ensembles, while the former exceeded the latter at larger ensembles. At 32 ensembles, their computational costs per cycle were respectively 28.3 msec and 5.39 msec. These results suggested that further speedup of the LETKF is needed for practical 3D LBM simulations.
In, Teiji*; Shima, Shigeki*; Nakayama, Tomoharu*; Ishikawa, Yoichi*; Togawa, Orihiko; Kobayashi, Takuya; Kawamura, Hideyuki
Gekkan Kaiyo, 37(9), p.674 - 680, 2005/09
no abstracts in English
Kamachi, Masafumi*; Kawamura, Hideyuki; Ishikawa, Yoichi*; Usui, Norihisa*
no journal, ,
A drift simulation on the movement of the marine debris has been conducted by a Japanese modeling group (JAMSTEC, JAEA, and MRI) in order to examine the positions of the marine debris in the North Pacific, landing positions on the coast, and landing date after the Great East Japan Earthquake on March 11, 2011. The simulation has been conducted under the Japanese national project and MoE-PICES ADRIFT project. The potential locations of the marine debris were determined by numerical simulations with an ocean data assimilation system MOVE/MRI.COM-WNP and -NP, a coupled atmosphere-ocean data assimilation system K7, and an oceanic dispersion model SEA-GEARN. Data assimilation, dispersion method, current and wind fields, effect of windage, and comparison with sighting observation will be reported.
Yamamoto, Shinya*; Sakurai, Hideyuki*; Onoe, Hironori; Masumoto, Kiyoshi*
no journal, ,
The result of groundwater flow simulation includes the epistemic uncertainty due to the limited hydrogeological data available. Ensemble-based data assimilation scheme can reduce the uncertainty. Additionally, the analysis result of the data assimilation gives useful information for the layout design of the groundwater monitoring. We showed that the layouts determined by the ensemble of the assimilated results in the synthetic experiments are effective in reducing the uncertainty of hydrogeological model.
Machida, Masahiko; Iwata, Ayako; Yamada, Susumu
no journal, ,
no abstracts in English
Onodera, Naoyuki; Idomura, Yasuhiro; Kawamura, Takuma; Nakayama, Hiromasa; Shimokawabe, Takashi*; Aoki, Takayuki*
no journal, ,
The simulation for dispersion of radioactive substances attract high social interest, and it is required to satisfy both the speed and the accuracy. To perform a real-time simulation with high resolution mesh for the scale of human living area involving alleyways and buildings, it is required to develop simulation schemes which can fully utilize high computational performance. In this study, we introduced a nudging-based data assimilation method and a plant canopy model into the lattice Boltzmann method (LBM), and confirmed the accuracy of plume dispersion simulations for urban areas is improved.
Yokoyama, Kenji
no journal, ,
no abstracts in English
Hasegawa, Yuta; Onodera, Naoyuki; Asahi, Yuichi; Idomura, Yasuhiro
no journal, ,
We implemented an ensemble data assimilation called local ensemble transform Kalman Filter (LETKF) into the turbulent flow simulation based on Lattice Boltzmann Method (LBM). The code was implemented on GPU, using CUDA for the LBM, and cuBLAS/cuSOLVER libraries for the matrix calculation and eigenvalue decomposition in the LETKF. The data assimilation experiment was carried out on the two-dimensional isotropic turbulence. The experiment showed that the LETKF realized more accurate results compared with the nudging, which is a simple data assimilation scheme.
Fukui, Yuhei*; Endo, Tomohiro*; Yamamoto, Akio*; Maruyama, Shuhei
no journal, ,
no abstracts in English
Onodera, Naoyuki; Hasegawa, Yuta; Idomura, Yasuhiro; Asahi, Yuichi; Kawamura, Takuma; Ina, Takuya; Shimomura, Kazuya; Inagaki, Atsushi*; Suzuki, Shinichi*; Hirano, Kohin*; et al.
no journal, ,
Wind prediction based on digital twin is a promising technology that can contribute to the construction of new social infrastructures, including applications to smart city design and operation. In this poster presentation, we will introduce wind simulations based on data assimilation with observations and mesoscale meteorological data for the realization of a digital twin of wind conditions in urban areas.
Maruyama, Shuhei; Endo, Tomohiro*; Yamamoto, Akio*
no journal, ,
no abstracts in English
Maruyama, Shuhei; Endo, Tomohiro*; Yamamoto, Akio*
no journal, ,
In this study, nuclear data-induced uncertainty reduction of sodium void reactivity was performed by a data assimilation method using a sodium shielding experiment. The analysis reveals that a large reduction is achieved especially for the uncertainty in the sodium void reactivity, which is dominated by the neutron leakage component.
Onodera, Naoyuki; Shimokawabe, Takashi*; Idomura, Yasuhiro; Kawamura, Takuma; Asahi, Yuichi; Hasegawa, Yuta; Ina, Takuya; Shimomura, Kazuya; Inagaki, Atsushi*; Hirano, Kohin*; et al.
no journal, ,
The project goal is to realize real-time wind prediction in urban areas by assimilating observed data into real-time wind simulations on GPU supercomputers. In FY2022, the first year of the project, we developed a dynamic optimization method for model variables by applying a particle filter (PF) based data assimilation method to reproduce wind conditions in the atmospheric boundary layer with high accuracy. The numerical simulations for the field experiment in Oklahoma City showed improvements of about 10 % for the standard deviation error of the all-day velocity compared to the results without the application of PF. In addition, a multi-scale analysis based on boundary conditions given by a geographic information system (GIS) and a cloud-resolving numerical model (CReSS) was realized for the Tokyo metropolitan area.
Hasegawa, Yuta; Idomura, Yasuhiro; Onodera, Naoyuki
no journal, ,
Towards the digital twin of the wind environment of urban cities, the authors are developing the GPU-oriented efficient fluid dynamics and data assimilation code. We are implementing the lattice Boltzmann method (LBM), which is a fully explicit scheme and thus scalable for large-scale simulations, as a scheme to analyze fluid dynamics. The local ensemble transform Kalman filter (LETKF), which is widely used and applied to large-scale data assimilation with CPU-based supercomputers in the meteorological community, is adopted as a data assimilation method. In this presentation, we show the validation results of the LBM-LETKF against basic two-dimensional and three-dimensional turbulence systems, and discuss the accuracy of the data assimilation and the computing performance of the GPU implementation.
Harada, Yoshinari*; Yamaguchi, Hibiki*; Endo, Tomohiro*; Yamamoto, Akio*; Tada, Kenichi
no journal, ,
The data assimilation using the prompt neutron decay constant was performed to reduce the uncertainty in nuclear calculations due to the thermal neutron scattering law (TSL) for light water. The uncertainty in the effective multiplication factor due to TSL for light water can be reduced using the bias factor method based on the deterministic sampling method when there is a strong correlation between nuclear properties through TSL for light water.
Onodera, Naoyuki
no journal, ,
The Center for Computational Science and Engineering Center of Japan Atomic Energy Agency (CCSE) is developing real-time wind simulation and data assimilation methods as a wind digital twin for nuclear disaster prevention. In this presentation, we will show urban wind simulations and data assimilation of wind tunnel experiments on a GPU supercomputer SGI8600.
