• Korean Journal of Computational Design and Engineering
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• v.10 no.5
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• pp.314-327
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• 2005

This paper describes the volumetric data modeling and analysis methods that employ volumetric NURBS or VNURBS that represents heterogeneous objects or fields in multidimensional space. For volumetric data modeling, we formulate the construction algorithms involving the scattered data approximation and the curvilinear grid data interpolation. And then the computational algorithms are presented for the geometric and mathematical analysis of the volume data set with the VNURBS model. Finally, we apply the modeling and analysis methods to various field applications including grid generation, flow visualization, implicit surface modeling, and image morphing. Those application examples verify the usefulness and extensibility of our VNUBRS representation in the context of volume modeling and analysis.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.1081-1089
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• 1999

Volume data modeling is concerned with finding a mathematical function which represents the relationship implied by the 3D data. Modeling a volume data geometrically can visualize a volume data using surface graphics without voxelization. It has many merits in that it is fast and requires little memory. We proposes, a method based on wavelet transformation and tetrahedrization. we implement a prototype system based on the proposed method. Last, we evaluated the proposed method comparing it with marching cube algorithm. the evaluation results show that though the proposed method uses only 13% of the volume data, the images generated is as good as the images generated by the marching cubes algorithm.

• The KIPS Transactions:PartA
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• v.10A no.1
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• pp.59-68
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• 2003

3-D data modeling of a volumetric scattered data is highly demanded for geological structure inspection, environment visualization and supersonic testing. The data used in these area are generally irregularly scattered in a volume data space, which are much different from the structured points data (cuberille data) used in Marching cube algorithm. In this paper, first we explore a volume modeling method for the scattered data based on tetrahedral domain. Next we propose a method for solving the ambiguity of tetrahedral domain decision using asymptotic decider criterion. Last we implement a simple visualization system based on the proposed asymptotic decider criterion and compare it with a system based on sphere criterion. In deciding tetrahedral domain, sphere criterion considers only positional values but asymptotic decider criterion considers not only positional values but also functional values, so asymptotic decider criterion is more accurate on deciding tetrahedral domain than sphere criterion.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3
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• pp.394-401
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• 2013

A new Rockwell hardness (HRC) model using a volumetric parameter by a least square and fractal interpolation method is suggested. The results are also investigated in comparison to real measured hardness data. For this purpose, the measurement of an indented volume is performed using a confocal laser scanning microscope (CLSM), and the captured height encoded image (HEI) is used as an original surface for the calculation of the indented volume. After configuring the surface, the constructed volume is calculated and used as an independent variable for HRC hardness modeling. The hardness model is established using an experimental modeling technique involving a least square algorithm and fractal interpolating model, and this suggested model can be used to reliably predict the Rockwell hardness. These techniques can also be applied to the modeling of the Brinnell and Vickers hardnesses using a volumetric variable.

• Korean Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.11-18
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• 1997

Scientific volume visualization addresses the representation, manipulation, and rendering of volumetric data sets, providing mechanisms for looking closely into structures and understanding their complexity and dynamics. In the past several years, a tremendous amount of research and development has been directed toward algorithms and data modeling methods for a scientific data visualization. But there has been very little work on developing a mathematical volume model that feeds this visualization. Especially, in flow visualization, the volume model has long been required as a guidance to display the very large amounts of data resulting from numerical simulations. In this paper, we focus on the mathematical representation of volumetric data sets and the method of extracting meaningful information from the derived volume model. For this purpose, a B-spline volume is extended to a high dimensional trivariate model which is called as a flow visualization model in this paper. Two three-dimensional examples are presented to demonstrate the capabilities of this model.

• The KIPS Transactions:PartA
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• v.10A no.2
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• pp.157-164
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• 2003

Volume graphics have received a lot of attention as a medical image analysis tool nowadays. In the visualization based on volume graphics, there is a process called voxelization which transforms the geometrically defined objects into the volumetric objects. It enables us to volume render the geometrically defined data with sampling data. This paper suggests a voxeliration method using the cutting surfaces of cubes, implements the method on a PC, and evaluates it with simple geometric modeling data to explore propriety of the method. This method features the ability of calculating the exact normal vector from a voxel, having no hole among voxels, having multi-resolution representation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.9
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• pp.1-8
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• 2017

The purpose of this study is to propose a cache structure for processing large-volume building information modeling (BIM) geometry data,whereit is difficult to allocate physical memory. As the number of BIM orders has increased in the public sector, it is becoming more common to visualize and calculate large-volume BIM geometry data. Design and review collaboration can require a lot of time to download large-volume BIM data through the network. If the BIM data exceeds the physical free-memory limit, visualization and geometry computation cannot be possible. In order to utilize large amounts of BIM data on insufficient physical memory or a low-bandwidth network, it is advantageous to cache only the data necessary for BIM geometry rendering and calculation time. Thisstudy proposes acache structure for efficiently rendering and calculating large-volume BIM geometry data where it is difficult to allocate enough physical memory.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.05a
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• pp.159-162
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• 2005

To overcome the drawbacks of conventional load-control method and displacement-control method, the so-called volume-control method was developed by utilizing a pressure node added into a layered shell element. The pressure node has an increment of pressure as an additional degree of freedom of the shell element. In this study, the hollow RC columns are discretized with multi-layered shell elements and a modeling technique utilizing the volume-control analysis for various hollow RC column structures is introduced. The results of the nonlinear analysis using the modeling for hollow RC columns subjected to lateral reversed cyclic loading as well as lateral loading under compression are shown. Validity of the modeling technique is also verified by comparing the analysis results with experimental results and other analysis data.

• Bulletin of the Korean Chemical Society
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• v.15 no.2
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• pp.106-112
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• 1994

Six physical properties (molecular weight, heat capacity, side chain weight, side chain volume, standard entropy and partial molar volume) of amino acids, peptides and their derivatives were examined by molecular modeling techniques. The molecular connectivity index, Wiener distance index and ad hoc descriptor are employed as structural parameters to encode information about branching, size, cyclization, unsaturation, heteroatom content and polarizability. This paper examines the correlation of the molecular modeling techique's parameters and the physicochemical properties of amino acids and their derivatives. As a result, calculated values were in agreement with experimental data in the above six physical properties of amino acids, peptides and their derivatives and the molecular connectivity index was superior to the other indices in fitting the calculated data.

• Journal of Biomedical Engineering Research
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• v.21 no.4
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• pp.433-439
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• 2000

Volume rendering is a powerful tool for visualizing sampled scalar values from 3D data without modeling geometric primitives to the data. The volume rendering can describe the surface-detail of a complex object. Owing to this characteristic. volume rendering has been used to visualize medical data. The size of volume data is usually too big to handle in real time. Recently, various volume rendering algorithms have been proposed in order to reduce the rendering time. However, most of the proposed algorithms are not proper for fast rendering of large non-coded volume data. In this paper, we propose a block-based fast volume rendering algorithm using a shear-warp factorization for non-coded volume data. The algorithm performs volume rendering by using the organ segmentation data as well as block-based 3D volume data, and increases the rendering speed for large non-coded volume data. The proposed algorithm is evaluated by rendering 3D X-ray CT body images and MR head images.