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JAEA Reports

Review of research on Advanced Computational Science in FY2021

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.

JAEA Reports

Assessment report of research on development activities in FY 2021 Activity; "Computational Science and Technology Research" (Result and in-advance evaluation)

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.

Journal Articles

Machine learning potentials of kaolinite based on the potential energy surfaces of GGA and meta-GGA density functional theory

Kobayashi, Keita; Yamaguchi, Akiko; Okumura, Masahiko

Applied Clay Science, 228, p.106596_1 - 106596_11, 2022/10

 Times Cited Count:0 Percentile:0.03(Chemistry, Physical)

no abstracts in English

Journal Articles

Path integral Brownian chain molecular dynamics; A Simple approximation of quantum vibrational dynamics

Shiga, Motoyuki

Journal of Computational Chemistry, 43(27), p.1864 - 1879, 2022/10

 Times Cited Count:0 Percentile:0(Chemistry, Multidisciplinary)

A new approximate method for quantum vibrational dynamics (Brownian chain molecular dynamics: BCMD) based on the path integral method is proposed. Conventional methods such as centroid molecular dynamics and ring polymer dynamics cannot correctly calculate quantum vibration spectra under low temperature conditions. Thus, I introduce an over-damped Langevin equation for the non-centroid degrees of freedom of atoms to suppress unphysical resonances and vibrational rotational couplings, which are the source of the problem. I verify this approximation through applications to infrared absorption spectra of light and heavy water. I also demonstrate the feasibility of ab initio BCMD simulations by the combination with electronic structure theory.

Journal Articles

Zeeman effects on Yu-Shiba-Rusinov states

Machida, Tadashi*; Nagai, Yuki; Hanaguri, Tetsuo*

Physical Review Research (Internet), 4(3), p.033182_1 - 033182_12, 2022/09

no abstracts in English

Journal Articles

VR extension of particle-based remote visualization application

Kawamura, Takuma; Sakamoto, Naohisa*

Proceedings of 41st JSST Annual International Conference on Simulation Technology (JSST 2022) (Internet), p.266 - 269, 2022/09

Visualization of the large CFD dataset in remote locations by VR, especially using volume rendering, is one of the issues in the visualization field. The visualization library KVS supports PBVR, a unique particle-based visualization method suitable for large-scale data, and we have developed an extension of KVS for VR. In this paper, we present a design for VR extension of CS-PBVR, a remote visualization application based on KVS. The developed CS-PBVR for VR is then applied to test data and shown to be capable of VR visualization at interactive frame rates.

Journal Articles

Intrinsic vortex pinning in superconducting quasicrystals

Nagai, Yuki

Physical Review B, 106(6), p.064506_1 - 064506_10, 2022/08

 Times Cited Count:0

no abstracts in English

Journal Articles

Extended X-ray absorption fine structure spectroscopy measurements and ${it ab initio}$ molecular dynamics simulations reveal the hydration structure of the radium(II) ion

Yamaguchi, Akiko; Nagata, Kojiro*; Kobayashi, Keita; Tanaka, Kazuya; Kobayashi, Toru; Tanida, Hajime; Shimojo, Kojiro; Sekiguchi, Tetsuhiro; Kaneta, Yui; Matsuda, Shohei; et al.

iScience (Internet), 25(8), p.104763_1 - 104763_12, 2022/08

no abstracts in English

Journal Articles

Molecular dynamics simulations to quantify the interaction of a rigid and impenetrable precipitate with an edge dislocation in Cu

Tsugawa, Kiyoto*; Hayakawa, Sho*; Iwase, Yuki*; Okita, Taira*; Suzuki, Katsuyuki*; Itakura, Mitsuhiro; Aichi, Masaatsu*

Computational Materials Science, 210, p.111450_1 - 111450_9, 2022/07

 Times Cited Count:2 Percentile:0(Materials Science, Multidisciplinary)

Journal Articles

Artificial neural network-based path integral simulations of hydrogen isotope diffusion in palladium

Kimizuka, Hajime*; Thomsen, B.; Shiga, Motoyuki

Journal of Physics; Energy (Internet), 4(3), p.034004_1 - 034004_13, 2022/07

 Times Cited Count:0 Percentile:0(Energy & Fuels)

Artificial neural network-based interatomic potential for a system of palladium and hydrogen was developed, and path integral molecular dynamics simulations were performed to study the quantum diffusion of hydrogen isotopes in palladium crystals. Diffusion coefficients of light and heavy hydrogen were calculated over a wide temperature range of 50-1500 K to clarify the difference in diffusion mechanisms at low and high temperatures.

Journal Articles

Atomistic weak interaction criterion for the specificity of liquid metal embrittlement

Yamaguchi, Masatake; Tsuru, Tomohito; Itakura, Mitsuhiro; Abe, Eiji*

Scientific Reports (Internet), 12(1), p.10886_1 - 10886_7, 2022/07

 Times Cited Count:0 Percentile:0(Multidisciplinary Sciences)

no abstracts in English

Journal Articles

One-week lesson of numerical calculations in Julia language

Nagai, Yuki

Julia Programming for Numerical Computation; A One-week Course, 244 Pages, 2022/06

no abstracts in English

Journal Articles

GPU implementation of local ensemble transform Kalman filter (LETKF) with two-dimensional lattice Boltzmann method

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.

Journal Articles

Optimization of phase field variables in gas-liquid two-phase flow problems

Sugihara, Kenta; Onodera, Naoyuki; Idomura, Yasuhiro; Yamashita, Susumu

Keisan Kogaku Koenkai Rombunshu (CD-ROM), 27, 5 Pages, 2022/06

The phase-field method has been successfully applied to various multi-phase flow problems as an interface tracking method for gas-liquid interfaces. However, the accuracy of the phase-field method depends on hyper-parameters, which are empirically adjusted for each problem. The phase-field method sustains sharp interfaces by the balance between the numerical viscosity of the advection term and the interface modification by the diffusion and anti-diffusion terms. Based on this fact, we propose a method for deriving the optimal hyper-parameters in a non-empirical manner by performing a basic error analysis of the interface advection.

Journal Articles

Parameter optimization for generating atmospheric boundary layers by using the locally mesh-refined lattice Boltzmann method

Onodera, Naoyuki; Idomura, Yasuhiro; Hasegawa, Yuta; Shimokawabe, Takashi*; Aoki, Takayuki*

Keisan Kogaku Koenkai Rombunshu (CD-ROM), 27, 4 Pages, 2022/06

We have developed a wind simulation code named CityLBM to realize wind digital twins. Mesoscale wind conditions are given as boundary conditions in CityLBM by using a nudging data assimilation method. It is found that conventional approaches with constant nudging coefficients fail to reproduce turbulent intensity in long time simulations, where atmospheric stability conditions change significantly. We propose a dynamic parameter optimization method for the nudging coefficient based on a particle filter. CityLBM was validated against plume dispersion experiments in the complex urban environment of Oklahoma City. The nudging coefficient was updated to reduce the error of the turbulent intensity between the simulation and the observation, and the atmospheric boundary layer was reproduced throughout the day.

Journal Articles

Performance measurement of an urban wind simulation code with the Locally Mesh-Refined Lattice Boltzmann Method over NVIDIA and AMD GPUs

Asahi, Yuichi; Onodera, Naoyuki; Hasegawa, Yuta; Shimokawabe, Takashi*; Shiba, Hayato*; Idomura, Yasuhiro

Keisan Kogaku Koenkai Rombunshu (CD-ROM), 27, 5 Pages, 2022/06

We have ported the GPU accelerated Lattice Boltzmann Method code "CityLBM" to AMD MI100 GPU. We present the performance of CityLBM achieved on NVIDIA P100, V100, A100 GPUs and AMDMI100 GPU. Using the host to host MPI communications, the performance on MI100 GPU is around 20% better than on V100 GPU. It has turned out that most of the kernels are successfully accelerated except for interpolation kernels for Adaptive Mesh Refinement (AMR) method.

Journal Articles

Multi-scale turbulence simulation suggesting improvement of electron heated plasma confinement

Maeyama, Shinya*; Watanabe, Tomohiko*; Nakata, Motoki*; Nunami, Masanori*; Asahi, Yuichi; Ishizawa, Akihiro*

Nature Communications (Internet), 13, p.3166_1 - 3166_8, 2022/06

 Times Cited Count:1 Percentile:76.92(Multidisciplinary Sciences)

Turbulent transport is a key physics process for confining magnetic fusion plasma. Recent theoretical and experimental studies of existing fusion experimental devices revealed the existence of cross-scale interactions between small (electron)-scale and large (ion)-scale turbulence. Since conventional turbulent transport modelling lacks cross-scale interactions, it should be clarified whether cross-scale interactions are needed to be considered in future experiments on burning plasma, whose high electron temperature is sustained with fusion-born alpha particle heating. Here, we present supercomputer simulations showing that electron scale turbulence in high electron temperature plasma can affect the turbulent transport of not only electrons but also fuels and ash. Electron-scale turbulence disturbs the trajectories of resonant electrons responsible for ion-scale micro-instability and suppresses large-scale turbulent fluctuations. Simultaneously, ion-scale turbulent eddies also suppress electron-scale turbulence. These results indicate a mutually exclusive nature of turbulence with disparate scales. We demonstrate the possibility of reduced heat flux via cross-scale interactions.

Journal Articles

Effect of uniaxial tensile strain on binding energy of hydrogen atoms to vacancy-carbon-hydrogen complexes in $$alpha$$-iron

Hirayama, Shintaro*; Sato, Koichi*; Kato, Daiji*; Iwakiri, Hirotomo*; Yamaguchi, Masatake; Watanabe, Yoshiyuki*; Nozawa, Takashi*

Nuclear Materials and Energy (Internet), 31, p.101179_1 - 101179_9, 2022/06

 Times Cited Count:0 Percentile:0.02(Nuclear Science & Technology)

no abstracts in English

Journal Articles

Machine learning molecular dynamics simulations toward exploration of high-temperature properties of nuclear fuel materials; Case study of thorium dioxide

Kobayashi, Keita; Okumura, Masahiko; Nakamura, Hiroki; Itakura, Mitsuhiro; Machida, Masahiko; Cooper, M. W. D.*

Scientific Reports (Internet), 12(1), p.9808_1 - 9808_11, 2022/06

 Times Cited Count:0 Percentile:0(Multidisciplinary Sciences)

no abstracts in English

Journal Articles

Fourier interpolation method in phase space of Hamiltonian systems

Sasa, Narimasa

Journal of the Physical Society of Japan, 91(5), p.054001_1 - 054001_8, 2022/05

 Times Cited Count:0 Percentile:0.01(Physics, Multidisciplinary)

2727 (Records 1-20 displayed on this page)