• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1277-1285
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• 2015

It has been known that the conventional retaining wall system with timber lagging and H pile has several problems such as the irregular gap between H-piles, cutting or adding to standard timber, back fill over first step excavation, and especially break-down accident at the disjoint of wall system. In the practical excavation, these problems may lead to worker's accident and the inefficiency of construction economy. To solve the above problems, a new method using prefabricated retaining wall was proposed and verified. The characteristics of the new method is to replace timber wall as free-sliding steel-lagging and connector. To check its verification and application, laboratory tests such as bending strength, tensile strength, and fatigue strength were carried out. Also, a pilot test in the field and numerical simulations under various ground conditions were performed. From the researches, it is found that the prefabricated retaining wall plate can be superior to the conventional timber lagging plate in the strength. It is also found that the proposed methods can be effective in the reuse of retaining wall plate and safe in the disjoint of wall system. Finally, it is desired that the proposed method will be effective in the reduction of the imported timbers and helpful in the safety of retaining wall construction.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.585-588
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• 2019

Predictions of Energy Consumption for Industries gain an important place in energy management and control system, as there are dynamic and seasonal changes in the demand and supply of energy. This paper presents and discusses the predictive models for energy consumption of the steel industry. Data used includes lagging and leading current reactive power, lagging and leading current power factor, carbon dioxide (tCO2) emission and load type. In the test set, four statistical models are trained and evaluated: (a) Linear regression (LR), (b) Support Vector Machine with radial kernel (SVM RBF), (c) Gradient Boosting Machine (GBM), (d) random forest (RF). Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used to measure the prediction efficiency of regression designs. When using all the predictors, the best model RF can provide RMSE value 7.33 in the test set.

• Advances in concrete construction
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• v.1 no.2
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• pp.163-185
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• 2013

The use of post-compressed plates (PCP) to strengthen preloaded reinforced concrete (RC) columns is an innovative approach for alleviating the effects of stress-lagging between the original column and the additional steel plates. Experimental and theoretical studies on PCP-strengthened RC columns have been presented in our companion papers. The results have demonstrated the effectiveness of this technique for improving the strength, deformability and ductility of preloaded RC columns when subjected to axial or eccentric compression loading. An original and comprehensive design procedure is presented in this paper to aid engineers in designing this new type of PCP-strengthened RC column and to ensure proper strengthening details for desirable performance. The proposed design procedure consists of five parts: (1) the estimation of the ultimate load capacity of the strengthened column, (2) the design of the initial pre-camber displacement of the steel plate, (3) the design of the vertical spacing of the bolts, (4) the design of the bearing ends of the steel plates, and (5) the calculation of the tightening force of the bolts. A worked example of the design of a PCP-strengthened RC column is shown to demonstrate the application of the proposed design procedure.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.5
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• pp.153-160
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• 2020

Energy Consumption Predictions for Industries has a prominent role to play in the energy management and control system as dynamic and seasonal changes are occurring in energy demand and supply. This paper introduces and explores the steel industry's predictive models of energy consumption. The data used includes lagging and leading reactive power lagging and leading current variable, emission of carbon dioxide (tCO2) and load type. Four statistical models are trained and tested in the test set: (a) Linear Regression (LR), (b) Radial Kernel Support Vector Machine (SVM RBF), (c) Gradient Boosting Machine (GBM), and (d) Random Forest (RF). Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used for calculating regression model predictive performance. When using all the predictors, the best model RF can provide RMSE value 7.33 in the test set.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.11a
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• pp.244-247
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• 2003

Recently, construction materials have been quickly advancing. Especially, the rate of development of cement based construction materials is much quicker than steel or composite materials. In order to optimize the ductility and strength of cement based materials, Micro-Mechanics based fiber concrete called Engineered Cement Composite (ECC) has been developed and studied extensively by many researchers in the field due to ECC's remarkable flexural strain and strength capacities, many leading nation (i.e., US, Japan and European countries have reached the point of being able to use ECC in actual constructions. But, due to the belated interest in the field, Korea is lagging behind the leading countries. ECC's ability to use its short fibers to bridge micro-cracks (50-80㎛ in width) allows great ductility and strength. In this study, it is confirmed excellency of ECC through the test of tensile strength.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.361-366
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• 2003

Recently, construction materials have been guickly advancing. Especially, the rate of development of cement based construction materials is much quicker than steel or composite materials. In order to optimize the ductility and strength of cement based materials, Micro-Mechanics based fiber concrete called Engineered Cement Composite (ECC) has been developed and studied extensively by many researchers in the field due to ECC's remarkable flexural strain and strength capacities, many leading nation (i.e., US, Japan and European countries have reached the point of being able to use ECC in actual constructions. But, due to the belated interest in the field, Korea is lagging behind the leading countries. ECC's ability to use its short fibers to bridge micro-cracks (50-80㎛ in width) allows great ductility and strength. ,In this study, ECC with superior material capacities are manufactured using domestic materials such as cement, silica sand, metal cellulose, etc. Using only domestic products, the optimal W/C ratio and mixing procedures are determined.