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Hasegawa, Yuta; Aoki, Takayuki*; Kobayashi, Hiromichi*; Idomura, Yasuhiro; Onodera, Naoyuki
Keisan Kogaku Koenkai Rombunshu (CD-ROM), 26, 6 Pages, 2021/05
We introduce an improved domain partitioning method called "tree cutting approach" for the aerodynamics simulation code based on the lattice Boltzmann method (LBM) with the forest-of-octrees-based local mesh refinement (LMR). The conventional domain partitioning algorithm based on the space-filling curve (SFC), which is widely used in LMR, caused a costly halo data communication which became a bottleneck of our aerodynamics simulation on the GPU-based supercomputers. Our tree cutting approach adopts a hybrid domain partitioning with the coarse structured block decomposition and the SFC partitioning in each block. This hybrid approach improved the locality and the topology of the partitioned sub-domains and reduced the amount of the halo communication to one-third of the original SFC approach. The code achieved 
speedup on 8 GPUs, and achieved 
speedup at the performance of 2207 MLUPS (mega-lattice update per second) on 128 GPUs with strong scaling test.
Matsushita, Kentaro; Fujisaki, Tatsuya*; Ezure, Toshiki; Tanaka, Masaaki; Uchida, Mao*; Sakai, Takaaki*
Keisan Kogaku Koenkai Rombunshu (CD-ROM), 26, 6 Pages, 2021/05
For the gas entrainment vortex at the free surface in sodium-cooled fast reactors, development of the numerical analysis method to evaluate amount of the gas entrainment from the free surface has been developing. In this paper, the automatic creation of analysis meshes which can suppress the calculation cost while maintaining the prediction accuracy of the vortex shape is investigated, and the adaptive mesh refinement (AMR) method is examined to the creation of analysis mesh applying to the unsteady vortex system. The refined mesh based on the criterion evaluated by vorticity, Q-value as second invariant of the velocity and the discriminant for the eigen equation of the velocity gradient tensor is considered, and it found that the AMR method based on Q-value can refine the analysis meshes most efficiently.
Doda, Norihiro; Uwaba, Tomoyuki; Nemoto, Toshiyuki*; Yokoyama, Kenji; Tanaka, Masaaki
Keisan Kogaku Koenkai Rombunshu (CD-ROM), 26, 4 Pages, 2021/05
For design optimization of fast reactors, in order to consider the feedback reactivity due to thermal deformation of the core when the core temperature rises, which could not be considered in the conventional design analysis, a neutronics, thermal-hydraulics, and structure mechanics coupled analysis method has been developed. Neutronics code, plant dynamics code, and structural mechanics code are coupled by a control module in python script. This paper outlines the coupling method of analysis codes and the results of its application to an experiment in an actual plant.
Onodera, Naoyuki; Idomura, Yasuhiro; Hasegawa, Yuta; Shimokawabe, Takashi*; Aoki, Takayuki*
Keisan Kogaku Koenkai Rombunshu (CD-ROM), 26, 3 Pages, 2021/05
We develop a mixed-precision preconditioner for the pressure Poisson equation in a two-phase flow CFD code JUPITER-AMR. The multi-grid (MG) preconditioner is constructed based on the geometric MG method with a three- stage V-cycle, and a cache-reuse SOR (CR-SOR) method at each stage. The numerical experiments are conducted for two-phase flows in a fuel bundle of a nuclear reactor. The MG-CG solver in single-precision shows the same convergence histories as double-precision, which is about 75% of the computational time in double-precision. In the strong scaling test, the MG-CG solver in single-precision is accelerated by 1.88 times between 32 and 96 GPUs.
Asahi, Yuichi; Hatayama, Sora*; Shimokawabe, Takashi*; Onodera, Naoyuki; Hasegawa, Yuta; Idomura, Yasuhiro
Keisan Kogaku Koenkai Rombunshu (CD-ROM), 26, 4 Pages, 2021/05
We develop a convolutional neural network model to predict the multi-resolution steady flow. Based on the state-of-the-art image-to-image translation model Pix2PixHD, our model can predict the high resolution flow field from the signed distance function. By patching the high resolution data, the memory requirements in our model is suppressed compared to Pix2PixHD.