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Hasegawa, Yuta; Onodera, Naoyuki; Idomura, Yasuhiro
Proceedings of Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo 2020 (SNA + MC 2020), p.236 - 242, 2020/10
The wind condition and the plume dispersion in urban areas are strongly affected by buildings and plants, which are hardly described in the conventional mesoscale simulations. To resolve this issue, we developed a GPU-based CFD code using a mesh-refined lattice Boltzmann method (LBM), which enables real-time plume dispersion simulations with a resolution of several meters. However, such high resolution simulations are highly turbulent and the time histories of the results are sensitive to various simulations conditions. In order to improve the reliability of such chaotic simulations, we developed an ensemble simulation approach, which enables a statistical estimation of the uncertainty. We examined the developed code against the field experiment JU2003 in Oklahoma City. In the comparison, the wind conditions showed good agreements, and the average values of the tracer gas concentration satisfied the factor 2 agreements between the ensemble simulation data and the experiment.
Hasegawa, Yuta; Onodera, Naoyuki; Idomura, Yasuhiro
Keisan Kogaku Koenkai Rombunshu (CD-ROM), 25, 4 Pages, 2020/06
We developed a GPU-based CFD code using a mesh-refined lattice Boltzmann method (LBM), which enables ensemble simulations for wind and plume dispersion in urban cities. The code is tuned for Pascal or Volta GPU architectures, and is able to perform real-time wind simulations with several kilometers square region and several meters of grid resolution. We examined the developed code against the field experiment JU2003 in Oklahoma City. In the comparison, wind conditions showed good agreements, and the ensemble-averaged and maximum values of tracer concentration satisfied the factor 2 agreements.
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.
Sitompul, Y.*; Aoki, Takayuki*; Watanabe, Seiya*; Sugihara, Kenta; Takaki, Tomohiro*
no journal, ,
A cumulant Lattice Boltzmann Method (LBM) with Multiphase Field (MPF) and Adaptive Mesh Refinement (AMR) has been developed to model foam formation with stable thin liquid films. The proposed method has been successfully employed to simulate 3D foam formation with many bubbles, maintaining mass conservation and using a large density ratio. In addition, we have extended the proposed method to include heat transfer calculations. To demonstrate the effectiveness of the foam as a thermal insulation layer, we simulated 2D foam formation and compared the heat transfer in a cup of water with and without foam. Preliminary results show that the foam effectively acts as a thermal insulator, retaining the water temperature by preventing the natural air convection and acting like a stagnant air layer.