• Geomechanics and Engineering
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• v.28 no.1
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• pp.89-105
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• 2022

The behavior of the soil subgrade is complex and irregular against loads. When modeling, the soil is often replaced by a more straightforward system called a subgrade model. The Winkler method of linear elastic springs is a popular method of soil modeling in which the spring constant shows the modulus of subgrade reaction. In this research, the factors affecting the distribution of the modulus of subgrade reaction of elastoplastic subgrades are examined. For this purpose, critical theories about the modulus of subgrade reaction were examined. A square raft foundation on a sandy soil subgrade with was analyzed at different internal friction angles and Young's modulus values using ABAQUS software. To accurately model the actual soil behavior, the elastic, perfectly plastic constitutive model was applied to investigate a foundation on discrete springs. In order to increase the accuracy of soil modeling, equations have been proposed for the distribution of the subgrade reaction modulus. The constitutive model of the springs is elastic, perfectly plastic. It was observed that the modulus of subgrade reaction under an elastic load decreased when moving from the corner to the center of the foundation. For the ultimate load, the modulus of subgrade reaction increased as it moved from the corner to the center of the foundation.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.549-554
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• 2012

In this paper, we consider the optimal fuzzy filter of nonlinear discrete-time with estimation error variance constraint. First, the Takagi and Sugeno(T-S) fuzzy model is employed to approximate the nonlinear system. Next, the error state is mean square bounded, and the steady state variance of the estimation error of each state is not more than the individual predefined value. It is shown that, the addressed problem can be carried out by solving linear matrix inequality(LMI) and some algebraic quadratic matrix inequalities. Finally, some examples are provided to illustrate the design procedure and expected performance through simulations.

• Journal of the Korea Computer Industry Society
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• v.3 no.1
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• pp.85-94
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• 2002

EMRCA(Explicit Max_min Rate Control Algorithm) switch, which has been proposed in the ATM(Asychronous Transfer Mode) standard, controls the ABR(Available Bit Rate) service traffic in the ATM networks. The ABR service class of ATM networks uses a feedback control mechanism to adapt to varying link capacities. The VS/VD(Virtual Source/Virtual Destination) technique offers the possibility to segment the otherwise end-to-end ABR control loop into separate loops. The improved feedback delay and the control of ABR traffic inside closed segments provide a better performance and QoS(Quality of Service) for ABR connections with respect to throughput, delay, and jitter. This paper is study of an ABR VS/VD flow control method. Linear control theory offers the means to derive correct choices of parameters and to assess performance issues, like stability of the system, during the design phase. The performance goals are a high link utilization, fair bandwidth distribution and robust operation in various environments, which are verified by discrete event simulations. The major contribution of this work is the use of linear control theory to model and design an ABR flow control method tailored for the special layout of a VS/VD switch, the simulation shows that this techniques better than conventional method.

• Journal of Advanced Navigation Technology
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• v.22 no.3
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• pp.228-232
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• 2018

Dealing with quntization error in a control system properly becomes much more important as many devices are connected through network and controlled. Thus, in this paper, we study a data rate condition on quantizer to achieve practical stability in a discrete time linear time invariant system with state feedback control. First, required data rate is shown to depend on eigenvalue of the closed loop system, the size of the initial state vector, the magnitude of initial quantization error, and control gain in the absence of process noise. It additionally depends on the maximum magnitude of process noise when noise is not zero. Asymptotic analysis shows that a new design method may be needed to reduce the date rate for a networked control in the presence of quantization error and noise.. We provide a simple numerical evaluation of uniform quantizer and logarithmic qunatizer to assess their characteristics of practical stability depending on data rate in the presence of noise.

• Journal of the Korea Convergence Society
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• v.8 no.4
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• pp.9-18
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• 2017

UAVs began to be actively applied to so-called 3D jobs, including the autonomous exploration, investigation, mapping, search and rescue, etc. since the mid-2000s. With this global trend, having a precise controllability of the UAV will certainly revolutionize the life of the modern human in the aspect of tremendous applications of the UAV. In the first part, a simplified dynamic model of the UAV identified using system identification techniques is compared with the previously built time-discrete linear model. In the second part, the three parameters of the dynamic model are estimated using the batch and RLS methods. Angular acceleration data of the quadrotor UAV at the hovering maneuver are analyzed and shown to be converging at all time. Also, according to the quadrotor flight data from both experiments and MATLAB simulations, the batch estimation method turns out to be more accurate than the RLS estimation method based on the comparison of final parameter values.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.10-20
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• 2024

In recent automated manufacturing systems, compressed air-based pneumatic cylinders have been widely used for basic perpetration including picking up and moving a target object. They are relatively categorized as small machines, but many linear or rotary cylinders play an important role in discrete manufacturing systems. Therefore, sudden operation stop or interruption due to a fault occurrence in pneumatic cylinders leads to a decrease in repair costs and production and even threatens the safety of workers. In this regard, this study proposed a fault detection technique by developing a time-variant deep learning model from multivariate sensor data analysis for estimating a current health state as four levels. In addition, it aims to establish a real-time fault detection system that allows workers to immediately identify and manage the cylinder's status in either an actual shop floor or a remote management situation. To validate and verify the performance of the proposed system, we collected multivariate sensor signals from a rotary cylinder and it was successful in detecting the health state of the pneumatic cylinder with four severity levels. Furthermore, the optimal sensor location and signal type were analyzed through statistical inferences.

• Tunnel and Underground Space
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• v.33 no.1
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• pp.57-69
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• 2023

In this study, we simulated induced seismicity in the Groningen natural gas reservoir using 2D hydro-mechanical coupled discrete element modelling (DEM). The code used is PFC2D (Particle Flow Code 2D), a commercial software developed by Itasca, and in order to apply to this study we further developed 1)initialization of inhomogeneous reservoir pressure distribution, 2)a non-linear pressure-time history boundary condition, 3)local stress field monitoring logic. We generated a 2D reservoir model with a size of 40 × 50 km² and a complex fault system, and simulated years of pressure depletion with a time range between 1960 and 2020. We simulated fault system failure induced by pressure depletion and reproduced the spatiotemporal distribution of induced seismicity and assessed its failure mechanism. Also, we estimated the ground subsidence distribution and confirmed its similarity to the field measurements in the Groningen region. Through this study, we confirm the feasibility of the presented 2D hydro-mechanical coupled DEM in simulating the deformation of a complex fault system by hydro-mechanical coupled processes.

• Coupled systems mechanics
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• v.6 no.3
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• pp.287-316
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• 2017

This paper studies the particularities of the forced vibration of the hydro-elastic system consisting of a moving elastic plate, compressible viscous fluid and rigid wall. This study is made by employing the discrete-analytical solution method proposed in the paper by the authors (Akbarov and Panakhli (2015)). It is assumed that in the initial state the fluid flow is caused by the axial movement of the plate and the additional lineally-located time-harmonic forces act on the plate and these forces cause additional flow field in the fluid and a stress-strain state in the plate. The stress-strain state in the plate is described by utilizing the exact equations and relations of the linear elastodynamics. However, the additional fluid flow field is described with linearized Navier-Stokes equations for a compressible viscous fluid. Numerical results related to the influence of the problem parameters on the frequency response of the normal stress acting on the plate fluid interface plane and fluid flow velocity on this plane are presented and discussed. In this discussion, attention is focused on the influence of the initial plate axial moving velocity on these responses. At the same, it is established that as a result of the plate moving a resonance type of phenomenon can take place under forced vibration of the system. Moreover, numerical results regarding the influence of the fluid compressibility on these responses are also presented and discussed.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.4
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• pp.189-197
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• 2017

The development and application of accurate numerical models is essential to promptly respond to early stage of oil spill incidents occurring in nearshore area. In this study, the coupled modelling system was developed by integrating the advection-diffusion-transformation model for oil slick with the Boussinesq model, which incorporates non-linear, discrete, turbulent and rotational effects of wavy flows for accurate representation of nearshore hydrodynamics. The developed model examined its applicability through the application into real coastal region with topographical complexity and characteristics of the resulting flow originated from it. The highly-resolved, coupled model developed in this study is believed to assist in establishing the disaster prevention system that can prepare effectively for oil disasters under extreme ocean climate conditions and thus minimize industrial, economical, and environmental damages.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.29-39
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• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.