• 한국수소및신에너지학회논문집
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• 제34권5호
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• pp.465-477
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• 2023

In proton exchange membrane fuel cell (PEMFC), proper thermal management of the stack and moisture generation by electrochemical reactions significantly affect fuel cell performance. In this study, the PEMFC dynamic characteristic model was developed through Simcenter AMESim, a development program. In addition, the developed model aims to understand the thermal resin balance of the stack and performance characteristics for input loads. The developed model applies the thermal management model of the stack and the moisture content and permeability model to simulate voltage loss and stack thermal behavior precisely. This study extended the C based AMESet (adaptive modeling environment submodeling tool) to simulate electrochemical reactions inside the stack. Fuel cell model of AMESet was liberalized with AMESim and then integrated with the balance of plant (BOP) model and analyzed. And It is intended to be used in component design through BOP analysis. The resistance loss of the stack and thermal behavior characteristics were predicted, and the impact of stack performance and efficiency was evaluated.

• Geomechanics and Engineering
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• 제38권5호
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• pp.507-515
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• 2024

An accurate estimation of the geotechnical parameters in front of tunnel faces is crucial for the safe construction of underground infrastructure using tunnel boring machines (TBMs). This study was aimed at developing a data-driven model for predicting the rock quality designation (RQD) of the ground formation ahead of tunnel faces. The dataset used for the machine learning (ML) model comprises seven geological and mechanical features and 564 RQD values, obtained from an earth pressure balance (EPB) shield TBM tunneling project beneath the Han River in the Republic of Korea. Four ML algorithms were employed in developing the RQD prediction model: k-nearest neighbor (KNN), support vector regression (SVR), random forest (RF), and extreme gradient boosting (XGB). The grid search and five-fold cross-validation techniques were applied to optimize the prediction performance of the developed model by identifying the optimal hyperparameter combinations. The prediction results revealed that the RF algorithm-based model exhibited superior performance, achieving a root mean square error of 7.38% and coefficient of determination of 0.81. In addition, the Shapley additive explanations (SHAP) approach was adopted to determine the most relevant features, thereby enhancing the interpretability and reliability of the developed model with the RF algorithm. It was concluded that the developed model can successfully predict the RQD of the ground formation ahead of tunnel faces, contributing to safe and efficient tunnel excavation.

• 한국공작기계학회논문집
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• 제13권3호
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• pp.30-36
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• 2004

The exchange of model design data among heterogeneous CAD systems is very difficult because each CAD system has different data structures suitable for its own functions. STEP represents product information in a common computer-interpretable form that is required to remain complete and consistent when the product information is needed to be exchanged among different computer systems. However, STEP has complex architecture to represent point, line, curve and vectors of element. Moreover it can't represent geometry data of feature based models. In this study, a structure of XML document that represents geometry data of feature based models as neutral format has been developed. To use the developed XML document, a converter also has been developed to exchange modules so that it can exchange feature based data models among heterogeneous CAD systems. Developed XML document and Converter have been applied to commercial CAD systems.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 춘계학술대회 논문집
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• pp.434-440
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• 2003

The exchange of model design date among heterogeneous CAD systems is a difficult task because each system has different data structures suitable for its own functions. STEP has been able to represent product information as a common computer-interpretable form that is required to remain complete and consistent when the product informant is needed to be exchanged among different computer system. However, STEP has difficult architecture in is representing point, line, curve and vectors of element, more over it can't represent geometry data of feature based models. In this study, a structure of XML document that represents geometry data of feature based models as neutral format has been developed. To use the developed XML document, a Converter has also been developed to exchange modules so that it can exchange feature based data models among heterogeneous CAD systems. Aa for evaluation of the developed XML document and Converter, Solidworks and SolidEdge are selected.

• 상하수도학회지
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• 제21권1호
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• pp.3-11
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• 2007

THM models have been developed in several researchers in order to better understand and manage the presence of THM in water distribution system. Several developed models were demonstrated in this study for estimating THM concentrations in target water distribution system. In order to investigate the performance of developed THM models, lab and field test were investigated. Predicted THM concentrations by all kind of models were showed good correlation with observed values. When the developed models were compared with lab and field test, the Rodriguez model during tested models was most predictive than the other models.

• 한국시뮬레이션학회논문지
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• 제8권3호
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• pp.29-37
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• 1999

When an escalator is developed or modified to improve its performance, estimation of dynamic characteristics of the escalator is required. But modeling of the escalator for a design purpose is very difficult and time consuming. Especially, it is very difficult for a designer to use the simulation model during design process because preparing a proper model takes time and also the designer needs to know how to use the simulation program. In order to solver these problems, a graphic user interface program that can predict dynamic characteristics of an escalator is developed for the designer. Since this program makes the necessary escalator model for simulation for itself, the designer does not need to know how to use the simulation program while design is in progress. In this paper, a designer oriented interface program is developed and an example is presented to show the effectiveness of the developed program.

• 자원환경지질
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• 제29권3호
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• pp.325-333
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• 1996

폐기물 매립지 내에셔 가스 흐름을 추정하기 위하여 수치 모델을 개발하였다. 가스 흐름은 밀도에 영향 받는 밀도류이고 매립지 내의 매체는 매우 불균질하므로 단순한 수학적 해법으로 가스 흐름을 추정하기 어렵다. Darcy 방정식과 절량 보존의 법칙을 결합하고 이상 기체 방정식을 도입하여 지배방정식을 만들어지고, 이 지배방정식을 유한요소법으로 풀이하였다. 정류상태 모의의 결과는 AIRFLOW 모델에 의한 모의 결과와 일치한다. 부정류 상태 모의 결과는 질량 보존 평가와 일정 시간 후의 결과를 정류상태의 결과와 비교하여 간접적으로 결과의 신뢰성을 평가하였다. 대우건설에서 1993년에 실시한 난지도 매립지 가스 추출 시험 결과를 모델을 사용하여 분석하였다. 개발된 모델은 1994년 재단법인 한국컴퓨터 프로그램 보호회에 등록되었다.

• 대한조선학회논문집
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• 제45권5호
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• pp.538-546
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• 2008

In this paper, the constitutive equation is developed to analyze the characteristics of strain-induced plasticity in the range of low temperature of 316 stainless steel. The practical usefulness of the developed equations is evaluated by the comparison between experimental and numerical results. For 316 stainless steel, constitutive equations, which represent the characteristics of nonlinear material behavior under the cryogenic temperature environment, are developed using the Bodner's plasticity model. In order to predict the material behaviour such as damage accumulation, Bodner-Chan's damage model is implemented to the developed constitutive equations. Based on the developed constitutive equations, 3-D finite element analysis program is developed, and verified using experimental results.

• 한국환경교육학회지:환경교육
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• 제19권3호
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• pp.138-149
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• 2006

The purpose of this study was to develop the environmental sensitivity(ES) measurement instrument and to apply for middle school students. The questionnaire was developed to evaluate ES. The developed questionnaire consists of 15 items in 5 categories. Each item of the instrument was developed through the conceptional analysis of the definition of ES. The 5 categories included natural environment, activity at natural environment, artificial environment, environmental pollution, environmental destruction. Data for this study were collected from 397 middle school students including 46 environmental class and 351 non-environmental class students. It was found that the developed instrument to measure ES was valid and reliable. Reliability coefficient, Cronbach $\alpha$ was 0.75. Using the developed instrument of ES, the ES was measured for the students of experimental group to which a inqury-based EE model was applied. The result was that the effect of ES of the students of the experimental group was not statistically significant. Futher research is needed related to the EE model based on the inquiry learning model and measurement of environmental sensitivity.

• 상하수도학회지
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• 제36권4호
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• pp.239-248
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• 2022

The prediction of algal bloom is an important field of study in algal bloom management, and chlorophyll-a concentration(Chl-a) is commonly used to represent the status of algal bloom. In, recent years advanced machine learning algorithms are increasingly used for the prediction of algal bloom. In this study, XGBoost(XGB), an ensemble machine learning algorithm, was used to develop a model to predict Chl-a in a reservoir. The daily observation of water quality data and climate data was used for the training and testing of the model. In the first step of the study, the input variables were clustered into two groups(low and high value groups) based on the observed value of water temperature(TEMP), total organic carbon concentration(TOC), total nitrogen concentration(TN) and total phosphorus concentration(TP). For each of the four water quality items, two XGB models were developed using only the data in each clustered group(Model 1). The results were compared to the prediction of an XGB model developed by using the entire data before clustering(Model 2). The model performance was evaluated using three indices including root mean squared error-observation standard deviation ratio(RSR). The model performance was improved using Model 1 for TEMP, TN, TP as the RSR of each model was 0.503, 0.477 and 0.493, respectively, while the RSR of Model 2 was 0.521. On the other hand, Model 2 shows better performance than Model 1 for TOC, where the RSR was 0.532. Explainable artificial intelligence(XAI) is an ongoing field of research in machine learning study. Shapley value analysis, a novel XAI algorithm, was also used for the quantitative interpretation of the XGB model performance developed in this study.