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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.
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.
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.
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.
Doda, Norihiro; Nakamine, Yoshiaki*; Igawa, Kenichi*; Iwasaki, Takashi*; Murakami, Satoshi*; Tanaka, Masaaki
Keisan Kogaku Koenkai Rombunshu (CD-ROM), 27, 6 Pages, 2022/06
As a part of the development of the "Advanced Reactor Knowledge- and AI-aided Design Integration Approach through the whole plant lifecycle (ARKADIA)" to automatically optimize the life cycle of innovative nuclear reactors including fast reactors, ARKADIA-design is being developed to support the optimization of fast reactor design in the conceptual stage. ARKADIA-Design consists of three systems (Virtual plant Life System (VLS), Evaluation assistance and Application System (EAS), and Knowledge Management System (KMS)). A design optimization framework controls the cooperation between the three systems through the interfaces in each system. This paper reports on the development status of the "VLS interface," which has a control function of coupling analysis codes in VLS.