• Structural Engineering and Mechanics
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• 제54권5호
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• pp.909-922
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• 2015

The dynamic response and the mooring line tension of a 1/75 scale model of spar-type platform for 2.5 MW floating offshore wind turbine subject to one-dimensional regular harmonic wave are investigated numerically and verified by experiment. The upper part of wind turbine which is composed of three rotor blades, hub and nacelle is modeled as a lumped mass the scale model and three mooring lines are pre-tensioned by means of linear springs. The coupled fluid-rigid body interaction is numerically simulated by a coupled FEM-cable dynamics code, while the experiment is performed in a wave tank with the specially-designed vision and data acquisition system. The time responses of surge, heave and pitch motions of the scale platform and the mooring line tensions are obtained numerically and the frequency domain-converted RAOs are compared with the experiment.

• Structural Engineering and Mechanics
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• 제28권3호
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• pp.281-294
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• 2008

In this paper, linear elastic isotropic structures under the effects of both stochastic operators and stochastic excitations are studied. The analysis utilizes the spectral stochastic finite elements (SSFEM) with its two main expansions namely; Neumann and Homogeneous Chaos expansions. The random excitation and the random operator fields are assumed to be second order stochastic processes. The formulations are obtained for the system solution of the two dimensional problems of plane strain and plate bending structures under stochastic loading and relevant rigidity using the previously mentioned expansions. Two finite element programs were developed to incorporate such formulations. Two illustrative examples are introduced: the first is a reinforced concrete culvert with stochastic rigidity subjected to a stochastic load where the culvert is modeled as plane strain problem. The second example is a simply supported square reinforced concrete slab subjected to out of plane loading in which the slab flexural rigidity and the applied load are considered stochastic. In each of the two examples, the first two statistical moments of displacement are evaluated using both expansions. The probability density function of the structure response of each problem is obtained using Homogeneous Chaos expansion.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1996년도 춘계학술대회 논문집
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• pp.24-29
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• 1996

The seniconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip effect on the functions of the semiconductors. The defects of the chip surface is crack or void. Because general inspection method requires many inspection processes, the inspection system which searches immediately and preciselythe defects of the semiconductor chip surface. We propose the inspection method by using the computer vision system. This study presents an image processing algorithm for inspecting the surface defects(crack, void)of the semiconductor test samples. The proposed image processing algorithm aims to reduce inspection time, and to analyze those experienced operator. This paper regards the chip surface as random texture, and deals with the image modeling of randon texture image for searching the surface defects. For texture modeling, we consider the relation of a pixel and neighborhood pixels as noncasul model and extract the statistical characteristics from the radom texture field by using the 2D AR model(Aut oregressive). This paper regards on image as the output of linear system, and considers the fidelity or intelligibility criteria for measuring the quality of an image or the performance of the processing techinque. This study utilizes the variance of prediction error which is computed by substituting the gary level of pixel of another texture field into the two dimensional AR(autoregressive model)model fitted to the texture field, estimate the parameter us-ing the PAA(parameter adaptation algorithm) and design the defect detection filter. Later, we next try to study the defect detection search algorithm.

• 전산구조공학
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• 제7권4호
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• pp.85-101
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• 1994

적층판의 동적거동에 대한 유한요소해석모델개발을 목적으로 전단변형을 적합하게 고려한 적층판이론에 대한 변분원리를 유도하였다. 유도방법은 Sandhu 등에 의해 개발된 다변수 경계치문제의 변분원리이론을 따랐으며, 지배방정식의 미분연산자 매트릭스를 self-adjoint로 만들기 위하여 convolution을 이중선형사상으로 사용하였다. 유도된 적층판의 범함수에는 경계조건, 초기조건뿐만 아니라 유한요소해석모델에서 생길 수 있는 요소간 불연속조건도 포함시킬 수 있다. 상태변수의 적합함수공간을 확장하거나 특정조건을 적용하므로서 다양한 형태의 범함수를 유도할 수 있으며, 이를 통해 다양한 유한요소해석모델의 개발이 가능함을 논하였다.

• Journal of Communications and Networks
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• 제6권1호
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• pp.68-77
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• 2004

In the near future packet networks should support applications which can not predict their traffic requirements in advance, but still have tight quality of service requirements, e.g., guaranteed bandwidth, jitter, and packet loss. These dynamic characteristics mean that the sources can be made to modify their data transfer rates according to network conditions. Depending on the customer&; needs, network operator can differentiate incoming connections and handle those in the buffers and the interfaces in different ways. In this paper, dynamic QoS-aware scheduling algorithm is presented and investigated in the single node case. The purpose of the algorithm is in addition to fair resource sharing to different types of traffic classes with different priorities ?to maximize revenue of the service provider. It is derived from the linear type of revenue target function, and closed form globally optimal formula is presented. The method is computationally inexpensive, while still producing maximal revenue. Due to the simplicity of the algorithm, it can operate in the highly nonstationary environments. In addition, it is nonparametric and deterministic in the sense that it uses only the information about the number of users and their traffic classes, not about call density functions or duration distributions. Also, Call Admission Control (CAC) mechanism is used by hypothesis testing.

• Structural Engineering and Mechanics
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• 제71권1호
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• pp.45-56
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• 2019

A modified mechanical model of pre-pressed spring self-centering energy dissipation (PS-SCED) brace is proposed, and the hysteresis band is distinguished by the indication of relevant state variables. The MDOF frame system equipped with the braces is formulated in an incremental form of linear acceleration method. A multi-objective genetic algorithm (GA) based brace parameter optimization method is developed to obtain an optimal solution from the primary design scheme. Parameter sensitivities derived by the direct differentiation method are used to modify the change rate of parameters in the GA operator. A case study is conducted on a steel braced frame to illustrate the effect of brace parameters on node displacements, and validate the feasibility of the modified mechanical model. The optimization results and computational process information are compared among three cases of different strategies of parameter change as well. The accuracy is also verified by the calculation results of finite element model. This work can help the applications of PS-SCED brace optimization related to parameter sensitivity, and fulfill the systematic design procedure of PS-SCED brace-structure system with completed and prospective consequences.

• Structural Monitoring and Maintenance
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• 제6권3호
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• pp.219-235
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• 2019

Scheduled inspections of common crossings are one of the main cost drivers of railway maintenance. Prognostics and health management (PHM) approach and modern monitoring means offer many possibilities in the optimization of inspections and maintenance. The present paper deals with data driven prognosis of the common crossing remaining useful life (RUL) that is based on an inertial monitoring system. The problem of scheduled inspections system for common crossings is outlined and analysed. The proposed analysis of inertial signals with the maximal overlap discrete wavelet packet transform (MODWPT) and Shannon entropy (SE) estimates enable to extract the spectral features. The relevant features for the acceleration components are selected with application of Lasso (Least absolute shrinkage and selection operator) regularization. The features are fused with time domain information about the longitudinal position of wheels impact and train velocities by multivariate regression. The fused structural health (SH) indicator has a significant correlation to the lifetime of crossing. The RUL prognosis is performed on the linear degradation stochastic model with recursive Bayesian update. Prognosis testing metrics show the promising results for common crossing inspection scheduling improvement.

• 한국산업융합학회 논문집
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• 제23권6_1호
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• pp.907-915
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• 2020

Specification selection, Layout, specifications and combinations of Power Drives, and Ship motions were studied for FGPP(Floating Gas-fired Power Plants), which are still needed in areas such as the Caribbean, Latin America, and Southeast Asia where electricity is not sufficiently supplied. From this study, the optimal equipment layout in ships was derived. In addition, the difference between engine and turbine was verified through LCOE(Levelized Cost of Energy) comparison according to the type and combination of Power Drives. Analysis of Hs(Significant Height of wave) and Tp(spectrum Peak Period of wave) for places where this FGPP will be tested or applied enables design according to wave characteristics in Brazil and Indonesia. Normalized Sloshing Pressures of FGPP and LNG Carrier are verified using a sloshing analysis program, which is CFD(Computational Fluid Dynamics) software developed by ABS(American Bureau of Shipping). Power Transmission System is studied with Double bus with one Circuit Breaker Topology. A nd the CFD analysis allowed us to calculate linear roll damping coefficients for more accurate full load conditions and ballast conditions. Through RAO(Response Amplitude Operator) analysis, we secured data that could minimize the movement of ships according to the direction of waves and ship placement by identifying the characteristics of large movements in the beam sea conditions. The FGPP has been granted an AIP(Approval in Principle) from a classification society, the ABS.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.47-47
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• 2023

Drought occurs due to lack of water resources over an extended period and its intensity has been magnified globally by climate change. In recent years, drought over South Korea has also been intensed, and the prediction was inevitable for the water resource management and water industry. Therefore, drought forecasting over South Korea was performed in the current study with the following procedure. First, accumulated spring precipitation(ASP) driven by the 93 weather stations in South Korea was taken with their median. Then, correlation analysis was followed between ASP and Df4m, the differences of two pair of the global winter MSLP. The 37 Df4m variables with high correlations over 0.55 was chosen and sorted into three regions. The selected Df4m variables in the same region showed high similarity, leading the multicollinearity problem. To avoid this problem, a model that performs variable selection and model fitting at once, least absolute shrinkage and selection operator(LASSO) was applied. The LASSO model selected 5 variables which showed a good agreement of the predicted with the observed value, R²=0.72. Other models such as multiple linear regression model and ElasticNet were also performed, but did not present a performance as good as LASSO. Therefore, LASSO model can be an appropriate model to forecast spring drought over South Korea and can be used to mange water resources efficiently.

• Geomechanics and Engineering
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• 제29권5호
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• pp.523-533
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• 2022

Several prediction model of penetration rate (PR) of tunnel boring machines (TBMs) have been focused on applying to design stage. In construction stage, however, the expected PR and its trends are changed during tunneling owing to TBM excavation skills and the gap between the investigated and actual geological conditions. Monitoring the PR during tunneling is crucial to rescheduling the excavation plan in real-time. This study proposes a sequential prediction method applicable in the construction stage. Geological and TBM operating data are collected from Gunpo cable tunnel in Korea, and preprocessed through normalization and augmentation. The results show that the sequential prediction for 1 ring unit prediction distance (UPD) is R²≥0.79; whereas, a one-step prediction is R²≤0.30. In modeling algorithm, a gradient boosted regression tree (GBRT) outperformed a least square-based linear regression in sequential prediction method. For practical use, a simple equation between the R² and UPD is proposed. When UPD increases R² decreases exponentially; In particular, UPD at R²=0.60 is calculated as 28 rings using the equation. Such a time interval will provide enough time for decision-making. Evidently, the UPD can be adjusted depending on other project and the R² value targeted by an operator. Therefore, a calculation process for the equation between the R² and UPD is addressed.