• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.395-402
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• 2006

In analyzing the nano-scale phenomena or behaviors of nano devices or materials, it is often desirable to deal with more atoms than can be treated only with a full atomistic simulation. However, even now, it is advisable to apply the atomistic simulation to the narrow region where the deformation field changes rapidly but to apply the conventional continuum model to the region far from that region. This equivalent continuum model can be formulated by applying the Cauchy-Born rule to the exact atomistic potential as in the quasicontinuum method. To couple the atomistic model with the equivalent continuum model, continuum displacements are conformed to the molecular displacements at the discrete positions of the atoms within the bridging domain. To satisfy the coupling constraints, we apply the Lagrange multiplier method. The continuum model in the bridging model should be applied on the region where the deformation field changes gradually. Then we can make the nodal spacing in the continuum model be much larger than the atomic spacing. In the first step, we generate the atomic-resolution mesh with the nodal spacing equal to the atomic spacing, and then we eliminate the nodal degrees of freedom adaptively using the node deactivation techniques. We eliminate more DOFs as the regions are more far from the atomistic region. Computing time and computational resources can be greatly reduced by the present node deactivation technique in multi scale analysis.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.2
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• pp.77-105
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• 2014

Medical imaging techniques have evolved to expand our ability to visualize new contrast information of electrical, optical, and mechanical properties of tissues in the human body using noninvasive measurement methods. In particular, electrical tissue property imaging techniques have received considerable attention for the last few decades since electrical properties of biological tissues and organs change with their physiological functions and pathological states. We can express the electrical tissue properties as the frequency-dependent admittivity, which can be measured in a macroscopic scale by assessing the relation between the time-harmonic electric field and current density. The main issue is to reconstruct spectroscopic admittivity images from 10 Hz to 1 MHz, for example, with reasonably high spatial and temporal resolutions. It requires a solution of a nonlinear inverse problem involving Maxwell's equations. To solve the inverse problem with practical significance, we need deep knowledge on its mathematical formulation of underlying physical phenomena, implementation of image reconstruction algorithms, and practical limitations associated with the measurement sensitivity, specificity, noise, and data acquisition time. This paper discusses a number of issues in electrical tissue property imaging modalities and their future directions.

• Journal of Mechanical Science and Technology
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• v.19 no.8
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• pp.1582-1596
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• 2005

Groundwater flow and behavior have to be investigated based on heterogeneous subsurface formation since the homogeneity assumption of this formation is not valid. Over the past twenty years, stochastic approach and Monte Carlo technique have been utilized very efficiently to understand the groundwater flow behavior. However, these techniques require lots of computational and numerical efforts according to the various researchers' comments. Therefore, utilizing new techniques with much less computational efforts such as Artificial Neural Network (ANN) in the prediction of the stochastic behavior for the groundwater based on heterogeneous subsurface formation is highly appreciated. The current paper introduces the ANN technique to investigate and predict the stochastic behavior of a well draw down in a confined aquifer based on subsurface heterogeneous hydraulic conductivity. Several ANN models are developed in this research to predict the unsteady two dimensional well draw down and its stochastic characteristics in a confined aquifer. The results of this study showed that ANN method with less computational efforts was very efficiently capable of simulating and predicting the stochastic behavior of the well draw down resulted from the continuous constant pumping in the middle of a confined aquifer with subsurface heterogeneous hydraulic conductivity.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.487-494
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• 2004

Resizing techniques have been recognized as practical methods for drift design of high-rise building since sensitivity analysis and iterative structural analysis are not required in implementation. In the techniques, the amount of material of a memberin a building for resizing is determined in terms of cross-sectional areas and sectional inertia moments as design variables. In this study, five drift design methods are developed by considering design variable linking strategy and fomulating resizing algorithm in terms of material properties of shear walls as a design variable. The developed methods are applied to the drift design of 20-story frame-RC shear wall structure, and then evaluated in the view points of practicality and efficiency.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.3-11
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• 2005

The structural analysis considering the soil-structure interaction is very important in the design process of underground structures located on the site with various soil conditions. In practice, simplified modelling techniques to obtain the approximate solution are used in accordance with the specifications. However, their details are insufficient for practical engineers to obtain the stable solutions and the analysis results of each engineer occasionally my be different in spite of the same problem. In this study, the sensitivity of structural behaviour on the underground structures is analyzed according to the structural modelling techniques of existing specifications. It is performed to obtain the fundamental informations to establish the guide to obtain the stable solutions in practical analysis of the underground structures such as subway structures.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.04a
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• pp.71-76
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• 1989

Structural design, generally engineering design, is a complex process combinding design knowledges and analysis techniques. While analysis techniques can be automated in an algorithmic fashion, relatively little work has been done in the area of the design automation. An effect approach method for the automation of the engineering design may be a hybrid system, in which design knowledges, specification requirements and interpretations are represented using an expert system methodology and numerically intensive operations of the design process are implemented using an algorithmic language such as FORTRAN. The purpose of this paper is concentrated on the knowledge of K-CLIPS(KAIST-C Language Integrated Production System) used to design and implement this hybrid system. In K-CLIPS, some representation methods : frame, production rule, fact and user defined function are used to construct the knowledge base. The hierarchical knowledges could be expressed more naturally with a little number of rules than other plain production systems.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.39-44
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• 2008

Stress wave propagation plays an important role in many engineering problems for reducing industrial noise and vibrations. In this paper, the dispersion-corrected finite element model is proposed for reducing the dispersion error in simulation of stress wave propagation. At eliminating the numerical dispersion error arising from the numerical simulation of stress wave propagation, numerical dispersion characteristics of the wave equation based finite element model are analyzed and some dispersion control scheme are proposed. The validity of the dispersion correction techniques is demonstrated by comparing the numerical solutions obtained using the present techniques.

• Korean Journal of Computational Design and Engineering
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• v.1 no.3
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• pp.234-241
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• 1996

Recently, Genetic Algorithms(GAs), which consist of genetic operators named selection crossover and mutation, are widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GAs are very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GAs. So, they can be easily applicable to wide territory of design optimization problems. Also, virtue to multi-point search procedure, they have higher probability of convergence to global optimum compared with traditional techniques which take one-point search method. The introduction of basic theory on GAs, and the application examples in combination optimization of ten-member truss structure are presented in this paper.

• Korean Journal of Computational Design and Engineering
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• v.18 no.2
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• pp.104-112
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• 2013

Computer-based modeling and simulation (M&S) techniques have become an essential component in the development of new weapons systems. M&S techniques provide a means to simulate military training, strategies, military doctrines, and weapons acquisition processes. This paper proposes a small scale engagement scenario generation method. This work also includes a process for scenario generation and visualization. The proposed scenario generation methodology employs the Timed-FSA (finite state automata) and DFS (depth first search) algorithms. The proposed scenario generation method is verified using a one-on-one combat engagement scenario between two submarines. In addition, we suggest a scenario generation process including whole scenario generation and scenario visualization.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.21-31
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• 1998

Ordering is used to reduce the amount of fill-ins in the Cholesky factor of an symmetric definite matrix. One of most efficient ordering methods is the minimum degree ordering method. In this paper. we propose the two techniques to improve the performance of the minimum degree ordering which are implemented using clique storage structure. One is node absorption which is a generalized version of clique absorption. The other technique is using the lower bounds of degree to suspend the degree updates of nodes. finally, we provide computational results on the problems on NETLIB. These results show that the proposed techniques reduce the number of degree updates and the computational time considerably.