Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Hasegawa, Yuta; Onodera, Naoyuki; Idomura, Yasuhiro
Dai-34-Kai Suchi Ryutai Rikigaku Shimpojiumu Koen Rombunshu (Internet), 3 Pages, 2020/12
We developed a real-time ensemble simulation code for analyzing urban wind conditions and plume dispersion using a locally mesh-refined lattice Boltzmann method. We validated the developed code against the wind tunnel experiment by AIST, and against the field experiment JU2003 in Oklahoma City. In the case of the wind tunnel experiment, the wind condition showed a good agreement with the experiment, and 61.2% of the tracer gas concentration data observed on the ground satisfied the FACTOR2 condition, that is an accuracy criterion given by the environmental assessment guideline. In the case of the field experiment JU2003, the instantaneous wind speed showed a good agreement with the experiment, while the wind direction showed a difference up to 100
. The means of the tracer gas concentration satisfied the FACTOR2 condition at all observation interval. These results demonstrate that the developed code is accurate enough for the environmental assessment.
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
no journal, ,
Towards the prediction of the plume dispersion in the urban area, we are developing the urban wind simulation code CityLBM which is based on the lattice Boltzmann method with GPU computing. In this presentation, we implemented the ensemble simulation with MPI parallelization, and estimated the uncertainty of the plume dispersion simulation. The ensemble simulation with 100 members was performed, and the dependency of the simulation against the number of ensemble members was tested. We confirmed that the ensemble simulation can be statistically assessed with the number of ensemble members being 10.
Yano, Midori; Kawamura, Takuma; Hasegawa, Yuta; Idomura, Yasuhiro
no journal, ,
Uncertainty quantification in numerical simulations is important for improving the reliability of simulation results. In-Situ visualization techniques that visualize simulations at runtime are available to evaluate large-scale, high-speed, and cutting-edge ensemble simulations using supercomputers. This study proposes an in-situ visualization method for ensemble simulations and applies it to analyze statistical properties in ensemble calculations of real-time plume dispersion analysis.