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Takahashi, Shigeo*; Sakurai, Daisuke*; Nagao, Fumiya; Kurikami, Hiroshi; Sanada, Yukihisa
Shimyureshon, 42(2), p.68 - 75, 2023/06
This paper introduces a case in which scientific knowledge on understanding the deposition process of radionuclides and evaluating the dose rate reduction due to decontamination work was obtained through visual analysis based on data on the spatio-temporal distribution of air dose rates accumulated through radiation monitoring after the accident. We will discuss the prospects for future efforts to effectively obtain important knowledge that will assist in the planning of policies for reconstruction from the nuclear power plant accident in the future.
Takahashi, Shigeo*; Kurikami, Hiroshi; Sanada, Yukihisa; Sakurai, Daisuke*
ERAN FY2022 Annual Report (Internet), 1 Pages, 2023/04
This study aims to establish a highly accurate evaluation technique for decontamination effects through multilateral and quantitative evaluation of decontamination effects. The applicability of the visual analysis technique was confirmed through a trial analysis.
Takahashi, Shigeo*; Sakurai, Daisuke*; Sasaki, Miyuki; Miyamura, Hiroko; Sanada, Yukihisa
Visual Computer, 37(12), p.3039 - 3050, 2021/12
Times Cited Count：0 Percentile：0.01(Computer Science, Software Engineering)The Fukushima nuclear accident in 2011 raised awareness on the importance of radioactive deposition processes, especially for proposing aerosol measures against possible air pollution. However, identifying these types of processes is often difficult due to complicated terrains. This paper presents an application study for identifying radioactive deposition processes by taking advantage of visual interaction with topographic data. The idea is to visually investigate the correspondence of the spatial positions to the air dose rate along with relevant attributes. This is accomplished by composing scatterplots of pairwise attributes, onto which we project terrain areas to interactively find specific patterns of such attributes. We applied our approach to the analysis of air dose rate distribution data around the Fukushima nuclear plant after the accident. Our visualization technique clearly distinguished contamination areas derived from different deposition processes, and thus is useful for elucidation of the deposition process.
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Sakurai, Daisuke; Saeki, Osamu*; Carr, H.*; Wu, H.-Y.*; Yamamoto, Takahiro*; Duke, D.*; Takahashi, Shigeo*
IEEE Transactions on Visualization and Computer Graphics, 22(1), p.945 - 954, 2016/01
Times Cited Count：5 Percentile：41.49(Computer Science, Software Engineering)Scalar topology in the form of Morse theory has provided computational tools that analyze and visualize data from scientific and engineering tasks. Contracting isocontours to single points encapsulates variations in isocontour connectivity in the Reeb graph. For multivariate data, isocontours generalize to fibers inverse images of points in the range, and this area is therefore known as fiber topology. However, fiber topology is less fully developed than Morse theory, and current efforts rely on manual visualizations. This paper therefore shows how to accelerate and semi-automate this task through an interface for visualizing fiber singularities of multivariate functions : . This interface exploits existing conventions of fiber topology, but also introduces a 3D view based on the extension of Reeb graphs to Reeb spaces. Validation of the interface is performed by assessing whether the interface supports the mathematical workflow both of experts and of less experienced mathematicians.
Miyamura, Hiroko; Idomura, Yasuhiro; Takemiya, Hiroshi; Sakurai, Daisuke*; Wu, H.-Y.*; Takahashi, Shigeo*
no journal, ,
We survey the distribution of accumulated radioactive substances and assess the air dose rate. The surveyed datasets are stored in a database and are made available to the public. In addition, we develop a visualization tool that enables ones to download the datasets and then visualize them on one's computer environment. Recently, the size of the datasets have been significantly extended as more detailed measurements in space and time are available, and effective reduction of the size of the datasets is necessary for analyzing such large scale datasets. However, if the datasets are not carefully reduced, we often miss a part of important features in the distribution data. Therefore, we develop an effective Level of Detail control (LoD) method for retaining critical features of the distribution. In the method, the structure of two dimensional data that represents a global feature of the distribution is extracted by means of differential topology analyses. The data size is reduced by considering local features of the data, while retaining its global structure.
Takahashi, Shigeo*; Sakurai, Daisuke*; Kurikami, Hiroshi; Sanada, Yukihisa
no journal, ,
This study aims to establish a highly accurate evaluation technique for decontamination effects through multilateral and quantitative evaluation of decontamination effects. The applicability of the visual analysis technique was confirmed through a trial analysis.
