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Yoshida, Toshiya; Nakayama, Hiromasa
Nihon Keisan Kogakkai Rombunshu (Internet), 2020, p.20200013_1 - 20200013_9, 2020/07
To quickly and accurately predict the dispersion of hazardous materials released over urban areas, we propose a combined method in which dispersion fields are simulated using a Reynolds-averaged Navier-Stokes model with pre-calculated flow fields from a large-eddy simulation (LES) model. First, the combined model is conducted for dispersion in a simple street canyon. The results of the combined model are compared with those of a wind-tunnel experiment to adjust empirical parameters in the turbulent scalar flux. The horizontal dispersion fields predicted in the combined model with the best parameters are well consistent with those calculated from our LES model. We then apply the combined model to predict the scalar dispersion over a real urban area. The combined model well predicts the results obtained from the LES model with less calculation time. Therefore, we find that the combined model is potentially effective for emergency response to hazardous-material release over urban areas.
Kushida, Noriyuki; Takemiya, Hiroshi
Nihon Keisan Kogakkai Rombunshu (Internet), 2010, 10 Pages, 2010/03
In this study, we introduce a novel implementation of FEM targeting the Cell which has a software controlled local (SCLM) memory. In recent days, developers of scientific or engineering numerical simulation code suffer from the big latency of data transfer between a processor and main memory, and power consumption. To overcome these problems, several researchers have proposed new computer architecture, which combines SCLM and SIMD processing unit. FEM is the one of the most famous numerical simulation method especially for the engineering. Such new computer architecture is, however, less effective for FEM than other applications. The Cell is well known as the accelerator of the Roadrunner which is the fastest computer in the Top500 supercomputer list, and is only existing processor which has software controlled local memory. In this study we developed new FEM implementation method which provides faster computation than conventional method by reducing main memory access.
Kino, Chiaki; Suzuki, Yoshio; Miyamura, Hiroko; Takemiya, Hiroshi; Nakajima, Norihiro
Nihon Keisan Kogakkai Rombunshu (Internet), 2009(22), 12 Pages, 2009/11
Scientific Concept Vocabulary (SCV) has been proposed to actualize Cognitive methodology based Data Analysis System: CDAS which supports researchers to analyze large scale data efficiently and comprehensively. In the information model of SCV, all semantic information is related to substantial data and algorisms. Consequently, SCV enables a data analysis system to process semantic information for physics and engineering. Using SCV, it is hoped that CDAS is able to extract semantic information from numerical simulation data. In this paper, the prototype of SCV has been constructed and applied to actual data of numerical simulation in order to confirm the implementability of the system.
Yamada, Susumu; Imamura, Toshiyuki*; Machida, Masahiko
Nihon Keisan Kogakkai Rombunshu (Internet), 2009(15), 12 Pages, 2009/09
We parallelize the density matrix renormalization group (DMRG) method, which is a groundstate solver for one-dimensional quantum lattice systems. The parallelization allows us to extend the applicable range of the DMRG to multiple leg ladders or quasi two-dimension cases. Such an extension is regarded to bring about several breakthroughs in quantum physics, chemistry, nano-device engineering, and so on. The parallelization requires an all-to-all communication which involves all processes. Such a communication is not suitable for multi-core clusters, which are presently the main stream of the parallel computer, because the network bandwidth should be shared by a large number of processes. Therefore, we propose a new communication strategy to eliminate the all-to-all communication by rearranging a data distribution. We evaluate performance of the new strategy on "SGI Altix 3700Bx2" (single-core system) and "T2K Open Supercomputer (Todai Combined Cluster)" (quad-core system) and confirm that the strategy is quite crucial for typical multi-core systems like T2K.
Yamada, Tomonori; Ogino, Masao*; Yoshimura, Shinobu*
Nihon Keisan Kogakkai Rombunshu (Internet), 2009(14), 7 Pages, 2009/08
Computation efficiency of the balancing domain decomposition method is investigated in this paper. An iterative substructuring method with coarse grid correction is one of the most effective methods for parallel computing of large scale structural finite element analyses. In this study, a prediction curve of parallel computation cost of the balancing domain decomposition method is proposed, and the optimal number of subdomains is estimated. Numerical validation of the optimal number of subdomains is conducted and the measured computation time with the optimal number of subdomains shows better computation performance than those with other numbers of subdomains.
Yamada, Tomonori; Nagashima, Toshio*
Nihon Keisan Kogakkai Rombunshu (Internet), 2009(6), 7 Pages, 2009/03
An integration scheme for finite elements on the boundary of analysis domain in structured finite element analysis is proposed in this paper. In structured finite element analysis, the structured grid is adopted as finite elements and the inconsistency between boundary of finite elements and that of analysis domain occurs. In this paper, Newton-Cotes integration technique with sub-cell evaluation of integration region is proposed and efficient integration of element stiffness matrices on the boundary of analysis domain is achieved.
Kino, Chiaki; Suzuki, Yoshio; Nishida, Akemi; Kushida, Noriyuki; Hayashi, Sachiko; Nakajima, Norihiro
Nihon Keisan Kogakkai Rombunshu (Internet), 2008(18), 8 Pages, 2008/07
We have conducted research and development of the Cognitive methodology based Data Analysis System (CDAS) which supports researchers to analyze large scale data efficiently and comprehensively. Traditionally, much of data analysis process has been carried out by humans. However, when the scale of data is extremely large, data analysis is beyond the recognition capability of humans. The basic idea of CDAS is that computers execute data analysis instead of humans. In the present study, we showed three necessary functions (Verification and Validation: VV, Data Diagnosis: DD and Synthesis) for the design of CDAS. VV and DD functions are executed on gird computing environment and findings output from these functions are integrated on Synthesis functions. Finally CDAS displayed only useful information to human. We have applied the system to the virtual plant vibration simulator and succeeded in analyzing large scale data reaching to 1TB thoroughly for the first time.
Yamada, Susumu; Imamura, Toshiyuki*; Machida, Masahiko
Nihon Keisan Kogakkai Rombunshu (Internet), 2006(27), 8 Pages, 2006/09
no abstracts in English
