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Miyamura, Hiroko; Kawamura, Takuma; Suzuki, Yoshio; Idomura, Yasuhiro; Takemiya, Hiroshi
Joho Shori Gakkai Rombunshi, 55(9), p.2216 - 2224, 2014/09
In numerical simulations, variations of calculation results with respect to a variable axis are often observed. When the target model is given in 3D, the simulation results become 4D. Such a multi-dimensional dataset given in more than 4D space is analyzed by detailed explorations of regions of interest (ROIs) in multi-dimensional space. However, for high-dimensional and large-scale datasets, this approach requires enormous processing time and effort, and may have difficulty in capturing all the ROIs. Therefore, we propose a technique that is based on a concept of spatiotemporal image. In our technique, a space axis is created by octree, a variable axis is defined in the direction perpendicular to the space axis. Our technique is applied to the results of 3D seismic simulations of a nuclear plant, and regions with characteristic frequency responses of each region are analyzed. Through the analyses, it is demonstrated that our technique can effectively capture ROIs from 4D datasets.
Ueshima, Yutaka
i-Net, (13), p.6 - 9, 2005/05
no abstracts in English
Tani, Keiji; *; *
JAERI-M 89-166, 81 Pages, 1989/10
no abstracts in English
; *; *
JAERI-M 84-078, 56 Pages, 1984/05
no abstracts in English
; ; ;
JAERI-M 5597, 37 Pages, 1974/03
no abstracts in English
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JAERI-M 5596, 33 Pages, 1974/03
no abstracts in English
Miyamura, Hiroko; Kawamura, Takuma; Suzuki, Yoshio; Idomura, Yasuhiro; Takemiya, Hiroshi
no journal, ,
In this paper, we propose an information visualization tool for the analysis of multivariate time series simulation datasets. For the implementation of this tool, we use a spatio-temporal map. The spatio-temporal map provides a method for mapping the distribution of physical data in a two-dimensional visualization space for space and time axis. It is possible to use parallel coordinate visualization technique of multivariate dataset for analysis of time series and multivariate datasets. In this tool, the physical data to be observed are first selected from the parallel coordinates, then, the spatial-temporal distribution of the selected physical data is observed using a spatio-temporal map. We also describe the effects of this tool by applying the simulation results of earthquake response of a nuclear test reactor.
