Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Onodera, Naoyuki; Idomura, Yasuhiro; Hasegawa, Yuta; Nakayama, Hiromasa
Dai-35-Kai Suchi Ryutai Rikigaku Shimpojiumu Koen Rombunshu (Internet), 3 Pages, 2021/12
A detailed wind simulation is very important for designing smart cities. Since a lot of tall buildings and complex structures make the air flow turbulent in urban cities, large-scale CFD simulations are needed. We develop a GPU-based CFD code based on a Lattice Boltzmann Method (LBM) with a block-based Adaptive Mesh Refinement (AMR) method. In order to reproduce real wind conditions, the wind condition and ground temperature of the mesoscale weather forecasting model are given as boundary conditions. In this research, a surface heat flux model based on the Monin-Obukhov similarity theory was introduced to improve the calculation accuracy. We conducted a detailed wind simulation in Oklahoma City. By executing this computation, wind conditions in the urban area were reproduced with good accuracy.
Asahi, Yuichi; Onodera, Naoyuki; Hasegawa, Yuta; Idomura, Yasuhiro
no journal, ,
We have developed a convolutional neural network (CNN) model to predict the plume concentrations in the urbanarea under uniform flow condition. By combining the Transformer or Multilayer Perceptron (MLP) layers with CNN model, our model can predict the plume concentrations from the building shapes, release points of plumeand time series data at observation stations.
Ina, Takuya; Idomura, Yasuhiro; Imamura, Toshiyuki*; Yamashita, Susumu; Onodera, Naoyuki
no journal, ,
We have developed mixed-precision preprocessing for the preconditioned conjugate gradients (PCG) method in the multi-phase multi-component thermal-hydraulic code JUPITER. The preconditioner employs a hybrid mixed-precision approach which combines FP16 data and FP32 operations. The roundoff errors are reduced by converting FP16 data to FP32 on cache, holding the intermediate result in FP32, converting the final result to FP16, and returning it to the memory. The developed preconditioner was tested for large-scale problems with 3D structured grids of 3,200
2,00014,160. The convergence of the PCG method was maintained even when the FP16 data format was used for ill-condition matrices, and the computational speed was dramatically increased by reducing the memory access. The hybrid FP16/32 mixed-precision implementation achieved 1.79 speedup from the FP64 implementation at 2,000 nodes on Fugaku.