• Computers and Concrete
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• v.15 no.4
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• pp.547-562
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• 2015

A two-dimensional multi-layered finite elements modeling of reinforced concrete structures at non-linear behaviour under monotonic and cyclical loading is presented. The non-linearity material is characterized by several phenomena such as: the physical non-linearity of the concrete and steels materials, the behaviour of cracked concrete and the interaction effect between materials represented by the post-cracking filled. These parameters are taken into consideration in this paper to examine the response of the reinforced concrete structures at the non-linear behaviour. Four examples of application are presented. The numerical results obtained, are in a very good agreement with available experimental data and other numerical models of the literature.

• Tunnel and Underground Space
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• v.12 no.3
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• pp.171-178
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• 2002

A dynamic analysis of a horseshoe_shaped tunnel near to cavity was performed to study the effect of the cavity on the dynamic behavior of the tunnel. In order to obtain the dynamic response of the tunnel embedded in a semi-infinite domain, a hybrid numerical technique was primarily developed. A dynamic fundamental solution in frequency domain for multi-layered half planes was derived and subsequently incorporated in the boundary element method. Coupling of the boundary element method for the far field with the finite element method for the near field is made by imposing compatibility condition of a displacement at the interface. The boundary element method is then coupled with the finite element method, which is utilized to model the near field including the tunnel and the cavity. In order to demonstrate the validity of the proposed technique, dynamic responses of single and multiply-layered semi-infinite structural systems are obtained by using the Kicker waveform and investigated in the limestone layer to find how the being and the location of the cavity affect the dynamic characteristics of the system.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.261-269
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• 2024

In this paper, the acoustic performance of an absorptive silencer was enhanced by optimizing an arrangement of multi-layered absorbing materials. The acoustic performance of the silencer was evaluated through transmission loss, and finite element method-based numerical analysis program was employed to calculate the transmission loss. Polyurethane, a porous elastic material frequently used in absorptive silencers, was employed as the absorbing material. The Biot-Allard model was applied, assuming that air is filled inside the polyurethane. By setting the frequency range of interest up to the 2 kHz and the acoustic performance affecting properties of the absorbing materials were investigated when it was composed as a single layer. And the acoustic performance of the silencers with the single and multi-layered absorbing materials was compared with each other based on polyurethane material properties. Subsequently, the arrangement of the absorbing materials was optimized by applying the Nelder-Mead method. The results demonstrated that the average transmission loss improved compared to the single-layered absorptive silencer.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.03b
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• pp.58-76
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• 2000

An analytical solution method capable of determining the geometric configuration and developed tensile forces of mooring lines associated with fixed plate/pile or drag anchors is presented. The solution method, satisfying complete equilibrium conditions, is capable of analyzing multi-segmented mooring lines that can consist of either chains, cables, or wires embedded in layered seafloor soils. Centrifuge model tests and full -scale field tests were used to calibrate and validate the analytical solution.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.187-190
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• 2003

In order to apply a cyclic elasto-plastic and a viscoelastic-viscoplastic constitutive model to actual multi-layered ground conditions during large earthquake, numerica simulations were performed by a liquefaction analysis in the present study. From the liquefaction analysis, it was verified that the models can give a good description of the damping characteristics and liquefaction phenomena of ground accurately during large event which induces plastic deformation in large strain range.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.850-855
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• 1991

In this paper, neural network-based compliance control of telerobot is presented, This is a method to learn the compliance of human behavior and control telerobot using learned compliance. The consistency of human behavior is checked using Lipschitz's condition. The neural compliance model is composed of a multi-layered neural network which mimics the compliant notion of the human operator. The effectiveness of proposed scheme ie verified by a simulation study.

• Geophysics and Geophysical Exploration
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• v.16 no.1
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• pp.6-17
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• 2013

Multicomponent seismic data including both P- and PS-waves have advantages in discriminating the type of pore fluid, characterizing the lithologic attributes and producing the high resolution image. However, multicomponent seismic data recorded at the vertical and horizontal component receivers contain both P- and PS-waves which have different features, simultaneously. Therefore, the wavefield separation of P- and PS-waves as a preprocessing is inevitable in order to use the multicomponent seismic data successfully. In this study, we analyzed the previous study of the wavefield separation method suggested by Jeong and Byun in 2011, where the approximated reflection angle calculated only from one refernce depth is used in rotation transform, and showed its limitation for seismic data containing various reflected events from the multi-layered structure. In order to overcome its limitation, we suggested a new effective wavefield separation method of P- and PS-waves. In new method, we calculate the reflection angles with various reference depths and apply rotation transforms to the data with those reflection angles. Then we stack all results to obtain the final separated data. To verify our new method, we applied it to the synthetic data sets from a multi-layered model, a fault model, and the Marmousi-2 model. The results showed that the proposed method separated successfully P- and PS-reflection events from the multicomponent data from mild dipping layered model as long as the dip is not too steep.

• Journal of the military operations research society of Korea
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• v.11 no.2
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• pp.6-14
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• 1985

The layered multi-barrier defense situation against penetrating enemy threat is analytically modeled towards minimizing the penetration probability. Each layer is characterized by probability of detection and probability of kill given detection. The two capabilities are assumed independent. Detection in a layer, however, affects detection performance in subsequent layers. The following three models were formulated and investigated: (1) 'Model A' permits increase of detection performance in only the next barrier, (2) 'Model B' permits the increase in all subsequent barriers linearly, and (3) 'Model C' expresses the increase in an asymptotic exponential way. The best and the worst barrier combinations are determined through model exercise and model performances are compared through sensitivity analysis for the 'intensification factor.'

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.719-722
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• 2003

This paper presents the development of reservoir characterization model equipped with parallelized genetic algorithm, and its application for a heterogeneous reservoir system with integration of the well data and multi-phase production data. A parallel processing method performed by PC-cluster was applied to the developed model in order to reduce time for an inverse calculation. By utilizing the developed model, we performed the inverse calculation with the production data obtained from three layered reservoir system to estimate porosity and permeability distribution. As a result, the pressures observed at well almost identical to those calculated by the developed model. Also, it was confirmed that parallel processing could be applied for reservoir characterization study efficiently.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.31-37
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• 2017

There are lots of combined battlefield elements which complete the war. It looks problematic when collecting and analyzing these elements and then predicting the situation of war. Commander's experience and military power assessment have widely been used to come up with these problems, then simulated combat training program recently supplements the war-game models through recording real-time simulated combat data. Nevertheless, there are challenges to assess winning factors of combat. In this paper, we characterize the combat element (ce) by clustering simulated combat data, and then suggest multi-layered artificial neural network (ANN) model, which can comprehend non-linear, cross-connected effects among ces to assess mission completion degree (MCD). Through our ANN model, we have the chance of analyzing and predicting winning factors. Experimental results show that our ANN model can explain MCDs through networking ces which overperform multiple linear regression model. Moreover, sensitivity analysis of ces will be the basis of predicting combat situation.