• Journal of Korean Society of Steel Construction
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• v.19 no.3
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• pp.259-270
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• 2007

This paper presents an analytical method of evaluating the flexural behavior of RC (reinforced concrete) beams strengthened with high-strengh bars. The former experimental results were used to compare with the analytical results. The experimental results also outline the advantages of externally strengtheng method with high-strenght bars. To evaluate the flexural behavior of RC beams strenghtend with unbonded high-strength bars, this paper proposes a method involving a simple strength-summation method. This method basically assumes that the total strength of RC beams strengthened with high-strength bars is equal to the sum of the strengths of the RC beams and the high-strength bars. This analytical method also includes the effects of compressive force due to the tension from high-strength bars. A comparison of the analytical and experimental results leads to the conclusion that the simple strength-summation mothod can simulate the flexural behavior of RC beams strengthened with high-strength bars with a good level of accuracy.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2001.04a
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• pp.168-168
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• 2001

제지공정의 지절 현상은 많은 공정 변수들이 복합적으로 작용하여 발생하는 가장 큰 공정 트러블 중의 하나이다. 지절은 생산량 감소 뿐만 아니라 발생 후 공정의 복구 와 정리, 생산재가동 및 공정의 재안정화를 위해 많은 시간과 비용, 그리고 노력이 투 입되어야 하므로 공정의 효율과 생산성을 크게 저하시키는 요인이다. 그러나 지절 현상 의 복잡성 때문에 이에 대해 쉽게 접근하거나 해결하지 못하고 있는 것이 현실이지만 그 필요성은 더욱 더 증대되고 있다. 본 연구에서는 최근 들어 각종 산업분야에서 복잡 한 공정상의 결점 발견 및 진단에 효과적이라고 인정받고 있는 예측 분석기법인 인공 신경망(artificial neural network) 시율레이션과 일반적인 통계기법 중의 하나인 주성분 분석을 이용하여 제지 공정의 지절 현상의 검토 가능성을 타진하였다. 인공신경망이란 인간두뇌에서 일어나는 자극-반응-학습과정을 모사하여 현실세계에 존재하는 다양한 현상들의 업력벡터와 출력상태 간의 비선형 mapping올 컴퓨터 시율 레이션을 통하여 분석하고자 하는 기법으로, 여러 가지 현상들을 학습을 통해서 인식하 는 신경망 내의 신경단위들이 병렬처리에 의해 많은 양의 자료에 대한 추론이나 판단 을 신속하고 정확하게 해주는 특징이 있으며 실시간 패턴인식이나 분류 응용분야에도 매우 매력적으로 이용되고 있는 방법이다. 이러한 인공 신경망 기법 중에서도 본 연구 에서는 퍼셉트론의 한계점을 극복하기 위하여 입력총과 출력층에 한 개 이상의 은닉층 ( (hidden layer)을 사용하여 다층 네트워으로 구성하고, 모든 입력패턴에 대하여 발생하 는 오차함수를 최소화하는 방향으로 연결강도를 조정하는 back propagation 학습 알고 리즘을 사용하였다. 지절의 원인으로 추정 가능한 공정인자들을 변수로 하여 최적의 인 공신경망을 구축하기 위해 학습률과 모멘트 상수의 변화 및 은닉층의 수와 출력층의 뉴런 수를 조절하는 동의 작업을 거쳐 네트워크의 정확도가 높은 인공신경망을 설계하 였다. 또한 이러한 인공신경망과의 비교분석을 위해 동일한 공정 데이터들올 이용하여 보편적으로 사용하는 통계기법 중의 하나인 주성분회귀분석을 실시하였다. 주성분 분석은 여러 개의 반응변수에 대하여 얻어진 다변량 자료의 다차원적인 변 수들을 축소, 요약하는 차원의 단순화와 더불어 서로 상관되어있는 반응변수들 상호간 의 복잡한 구조를 분석하는 기법이다. 본 발표에서는 공정 자료를 활용하여 인공신경망 과 주성분분석을 통해 공정 트러블의 발생에 영향 하는 인자들을 보다 현실적으로 추 정하고, 그 대책을 모색함으로써 이를 최소화할 수 있는 방안을 소개하고자 한다.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.18 no.2
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• pp.154-165
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• 2006

In the present study, a numerical model using Boussinesq equation is set up to predict the interacted equilibrium between waves and their induced currents in the occurrence of breaking waves over an underwater shoal, and the numerical results are compared with results of existing hydraulic experiments. A sensitivity analysis has been done to find out appropriate values of breaking wave parameters with the result (regular wave case) of Vincent and Briggs (1989)’ experiment. Then the numerical model is applied to the irregular wave cases of the experiment and the hydraulic model test of Ieodo which is a natural undersea shoal. The results show that a strong current forms in the wave direction at the downstream side of the shoals, causing the attenuation of wave heights there. The calculated wave heights generally show a similar pattern with the measured data.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.3
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• pp.196-203
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• 2007

The postbuckling behavior and failure of composite cylinders subjected to external hydrostatic pressure are investigated by a finite element method and test. A nonlinear finite element program, ACOS, is used for the postbuckling progressive failure analysis of composite cylinders. A total of 5 carbon/epoxy composite cylinders were fabricated and tested to verify the finite element results. For comparison, analyses by MSC/NASTRAN and MSC/MARC are additionally conducted. Among the softwares, the finite element program, ACOS, predicts the buckling loads the best with about 11 to 26% deviation from experimental results except for one specimen. While the finite element analysis shows global buckling modes with 4 waves in hoop direction, in the experiments the local buckling appears first and results in the final failure without global buckling.

• Korean Journal of Ecology and Environment
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• v.43 no.1
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• pp.161-167
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• 2010

In this study, we implemented an experimental approach of ecological model development in order to emphasize the importance of input variable selection with respect to time-delayed arrangement between input and output variables. Time-series modeling requires relevant input variable selection for the prediction of a specific output variable (e.g. density of a species). Inadequate variable utility for input often causes increase of model construction time and low efficiency of developed model when applied to real world representation. Therefore, for future prediction, researchers have to decide number of time-delay (e.g. months, weeks or days; t-n) to predict a certain phenomenon at current time t. We prepared a total of 3,900 equation models produced by Time-Series Optimized Genetic Programming (TSOGP) algorithm, for the prediction of monthly averaged density of a potamic phytoplankton species Stephanodiscus hantzschii, considering future prediction from 0- (no future prediction) to 12-months ahead (interval by 1 month; 300 equations per each month-delay). From the investigation of model structure, input variable selectivity was obviously affected by the time-delay arrangement, and the model predictability was related with the type of input variables. From the results, we can conclude that, although Machine Learning (ML) algorithms which have popularly been used in Ecological Informatics (EI) provide high performance in future prediction of ecological entities, the efficiency of models would be lowered unless relevant input variables are selectively used.

• Journal of the Korea institute for structural maintenance and inspection
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• v.9 no.3
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• pp.213-220
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• 2005

Recently, a concern to verify the displacement capacity of shear wall has been arised to produce suitable data for the performance based design. In this paper, a process is presented to evaluate the displacement capacity of shear wall. The displacement of shear wall is expressed as the superposition of shear and flexural deformation. Variable crack angle truss model with a modification and sectional analysis method are used in calculating shear and flexural displacement, respectively. In addition, the effect of axial force and the contribution of vertical and horizontal reinforcements in wall are considered in the analysis. The accuracy of proposed method is evaluated by the comparison calculation results with previous test results. From the comparison, it was shown that the hysteretic behavior of shear wall could be well predicted by using the process. In the case with flange wall, however, the method overestimates the contribution of flange wall for strength and stiffness and underestimates for displacement capacity.

• Journal of the Korean Society of Propulsion Engineers
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• v.15 no.4
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• pp.73-78
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• 2011

When a liquid rocket engine - specifically for the gas-generator cycle engine has throttle valves to control the thrust level and mixture ratio of the engine, it is possible to adjust the inherent flow characteristics of the control valves in order to secure a linearized correlation between the control-process-parameters like the thrust or mixture ratio of an engine and the throttle angle of valve. These linearities can reduce the complexity of the control process and make the process more explicit by ensuring the intuitive control. In this point, we proposed an algorithm within the frame of the in-house-developed program to obtain the control valves' inherent flow characteristics which satisfy the linearity, and calculated the sensitivities of control valves with respect to the throttle angle. Also, we compared the obtained inherent flow characteristics with the existed data and concluded the results are satisfactory.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.129-138
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• 2003

A new methodology for selecting spatially variable model control parameter values through consideration of inference models within a Hydroinformatic system has been developed to overcome problems associated with determination of spatially variable control parameter values for both ungauged and gauged catchment. The adopted Hydroinformatic tools for determination of control parameter values were a GIS(Arc/Info) to handle spatial and non-spatial attribute information, the SWMM(stormwater management model) to simulate catchment response to hydrologic events, and lastly, L_BFGS_B(a limited memory quasi-Newton algorithm) to assist in the calibration process. As a result, high accuracy of control parameter estimation was obtained by considering the spatial variations of the control parameters based on landuse characteristics. Also, considerable time and effort necessary for estimating a large number of control parameters were reduced from the new calibration approach.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.73-76
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• 2008

The damage of earthquakes have to achieve by probabilistic evaluation because of uncertainty of earthquake. Fragility analysis is a useful tool for predicting the probability of damage induced by the probable earthquake. This paper presents the probability of damage as a function of peak ground acceleration and estimates the probability of five damage levels for the pier of prestressed concrete (PSC) bridge subjected to given ground acceleration. At each 100 artificial earthquake motions were generated in terms of soil conditions, and nonlinear time domain analyses were performed for the damage states of the pier of PSC bridge structures. These damage states are described by displacement ductility result from seismic performance based on existing research results. Using the damage states and ground motion parameters, five fragility curves for the pier of PSC bridges with five types of dominant frequencies were constructed assuming a log-nomal distribution. It was found that there was a significant effect on the fragility curves due to the dominant frequencies.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.371-381
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• 2017

There has never been research on Chaos analysis using real estate auction sale price rate in Korea. In this study, three Chaos analysis methodologies - Hurst exponent, correlation dimension, and maximum Lyapunov exponent - in order to capture the nonlinear deterministic dynamic system characteristics. High level of Hurst exponent and the extremely low maximum Lyapunov exponent provide the tendency and the persistence of the data. The empirical results give two meaningful facts. First, monthly time lags of the correlation dimension are coincident with the time period from the approval auction start day to the sale price fixing day. Second, its weekly time lags correspond to the time period from the last day of request for sale price allocation to the sale price fixing day. Then, this study potentially examines the predictability of the real estate auction price rate time series.