• Composites Research
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• v.36 no.3
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• pp.167-172
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• 2023

The manufacturing technology of composite material is applicable with filler characteristics maintaining low cost, flexibility, and easy process to develope the various functional composite materials. To realize functional composites, various researches on the high performance of composite materials using graphene as a filler is being actively conducted. In this study, physical and chemical properties were investigated using graphene to improve high functional properties. Graphene oxide (GO) was prepared using graphane nanoplatelet (GNP), and reduced graphene oxide (R-GO) was formed by reducing GO. The physical properties of GO and R-GO were analyzed, and the reliability of the manufactured method was reviewed by comparing that of GNP results. As a result of analysis by Raman spectroscopy, in the case of R-GO, it was confirmed that the intensity of D-peak and G-peak decreased compared to GO, and an increase of 0.08 was observed through the ratio of ID/IG. For the FTIR results, GO and RGO has a repeating C-C and C=C connection structure unlike GNP. GO and R-GO show clear peaks for C-O bond, C=C bond, C=O bond, and O-H bonding. As a result of X-ray diffraction analysis, GNP showed a wide diffraction peak at 25.86° of (002) plane characteristics, whereas GO and R-GO showed peaks corresponding to (001) and (100) planes. It was also found that the interlayer distance of GO increased by about 2.6 times compared to GNP.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3C
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• pp.115-125
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• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by insitu test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network (NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. It was already found that NN model can come over the site dependency and prediction accuracy is greatly improved when compared with present theoretical and empirical models. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network (CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. Prediction results of CNN model are compared with those of conventional empirical and theoretical models and multi-layered neural network model, which has the optimized structure. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5B
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• pp.429-439
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• 2009

When Catastrophic extreme flood occurs due to dam break, the response time for flood warning is much shorter than for natural floods. Numerical models can be powerful tools to predict behaviors in flood wave propagation and to provide the information about the flooded area, wave front arrival time and water depth and so on. But flood wave propagation due to dam break can be a process of difficult mathematical characterization since the flood wave includes discontinuous flow and dry bed propagation. Nevertheless, a lot of numerical models using finite volume method have been recently developed to simulate flood inundation due to dam break. As Finite volume methods are based on the integral form of the conservation equations, finite volume model can easily capture discontinuous flows and shock wave. In this study the numerical model using Riemann approximate solvers and finite volume method applied to the conservative form for two-dimensional shallow water equation was developed. The MUSCL scheme with surface gradient method for reconstruction of conservation variables in continuity and momentum equations is used in the predictor-corrector procedure and the scheme is second order accurate both in space and time. The developed finite volume model is applied to 2D partial dam break flows and dam break flows with triangular bump and validated by comparing numerical solution with laboratory measurements data and other researcher's data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3A
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• pp.211-219
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• 2010

The design concept of high speed railway bridges is applied to a method for increasing the stiffness of existing bridge structures considering the impact factor by a static load. Generally, the process of structural design would be relied upon an advanced foreign technology. However, the dynamic amplification factor (DAF) and dynamic capacity assessment of high speed railway bridges may be conducted essentially a detailed estimation because the resonance phenomenon is affected by the long length (380 m) and high speed (300 km/h) moving of a high speed railway (Korea Train eXpress: KTX). Therefore, this study will be examined the dynamic capacity of the typical PSC Box Girder high speed railway bridge efficiently, and offered the basic information for the reasonable structural design. For this, the static analysis is conducted considering the load line diagram of KTX based upon existing references. In addition, the KTX moving load is transformed into the time series load considering various analytical variables. The time history analysis is assessed reasonable using the transformed time series load. At that time, analytical variables for calculating the time series load are considered loading node distance, time increment and KTX velocity variation etc. The dynamic capacity of the PSC Box Girder high speed railway bridge is examined based upon the FE analysis result systematically. The structural safety is assessed quantitatively in accordance with the related regulation of the inside and outside of the country.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.107-120
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• 2010

The effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water was assessed using the SLURP (semi-distributed land use-based runoff process), a physically based hydrological model. The fundamental input data (elevation, meteorological data, land use, soil, vegetation) was collected to calibrate and validate of the SLURP model for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang and Gosam) located in Anseongcheon watershed. Then, the CCCma CGCM2 data by SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (intergovernmental panel on climate change) was used to assess the future potential climate change. The future weather data for the year, m ms, m5ms and 2amms was downscaled by Change Factor method through bias-correction using 3m years (1977-2006) weather data of 3 meteorological stations of the watershed. In addition, the future land uses were predicted by modified CA (cellular automata)-Markov technique using the time series land use data fromFactosat images. Also the future vegetation cover information was predicted and considered by the linear regression between monthly NDVI (normalized difference vegetation index) from NOAA AVHRR images and monthly mean temperature using eight years (1998-2006) data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.695-703
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• 2008

China water market has huge potential for increased use of BOT mode and one of the most attractive markets of doing business. However, the current China water BOT market shows that many foreign companies are retreating from the market while Chinese water companies fast growing. From the view no domestic companies have track records in China BOT water market, the research identified twenty market access barriers in terms of construction laws, regulations, BOT-related policy and the recent market situation. These are evaluated based on interview results with 10 professionals direct or indirect having a China water BOT experience. All the factors are found to be highly influential to foreign company's decision on the market participation. Among those, no fixed return policy and low water price, difficulty in water price adjustment and approval, and no government guarantees, all directly related to the project viability and under the control of government, were the most critical factors, implying government's role is the key in increasing the market competition by attracting more foreign participation on the market. In addition, new construction law regulating foreign EPC contractor's construction work, namely Decree 113, and requirement of applying competitive bidding in selecting EPC contractor in a BOT project are also considered signigicant barriers on foreign participation, which contradicts international norm and therefore necessitates an adjustment on current decision process in domestic companies.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.329-344
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• 2023

In this study, we comprehensively analyze the generalization performance of various deep learning-based active sonar target classifiers when applied to small and imbalanced active sonar datasets. To generate the active sonar datasets, we use data from two different oceanic experiments conducted at different times and ocean. Each sample in the active sonar datasets is a time-frequency domain image, which is extracted from audio signal of contact after the detection process. For the comprehensive analysis, we utilize 22 Convolutional Neural Networks (CNN) models. Two datasets are used as train/validation datasets and test datasets, alternatively. To calculate the variance in the output of the target classifiers, the train/validation/test datasets are repeated 10 times. Hyperparameters for training are optimized using Bayesian optimization. The results demonstrate that shallow CNN models show superior robustness and generalization performance compared to most of deep CNN models. The results from this paper can serve as a valuable reference for future research directions in deep learning-based active sonar target classification.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.55-62
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• 2023

Internal erosion is one of the main causes of levee damage and collapse, and representative of this is backward erosion piping. This type of internal erosion accounts for one-third of the damage to levees, meaning it is important to predict and prevent it. In this work, experiments were conducted with the aim of detecting piping in advance by using a tracer. Experiments were undertaken by changing the head difference, soil diameter, and the installation of the cutoff wall. A tracer was injected twice, once at the beginning of the experiment and once after the piping occurred. A key finding was that the piping process significantly affectedthe concentration variation of the tracer in a soil layer. Hence, a tracer concentration curve monitored at downstream could provide information about piping occurrence. It is expected that the results of this study can be used to prevent levee damage and collapse caused by piping.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.79-89
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• 2023

The inventory of many materials requires a large storage space, and the longer the storage period, the higher the potential maintenance cost. When materials are stored on a construction site, there are also concerns about safety due to the reduction of room for movement and working. On the other hand, construction sites that do not store materials have insufficient inventory, making it difficult to respond to demands such as sudden design changes. Ordering materials is then subject to delays and extra costs. Although securing an appropriate amount of inventory is important, in many cases, material management on a construction site depends on the experience of the site manager, so a reasonable material inventory management plan that reflects the construction conditions of a site is required. This study proposes an economical material management method by reflecting variables such as the status of the preceding and following activities, site size, material delivery cost, timing of an order, and quantity of orders. To this end, we set the appropriate inventory amount while adjusting related activities in the activity network, using float time for each activity, the size of the yard, and the order quantity as the main variables, and applied a genetic algorithm to this process to suggest the optimal order timing and order quantity. The material delivery cost derived from the results is set as a fitness index and the efficiency of inventory management was verified through a case application.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.587-592
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• 2023

Cobalt oxide (Co₃O₄·CoO) ultra fine particles were synthesized by liquid phase precursor method. cobalt(II) chloride hexahydrate (CoCl₂·6H₂O) was as a starting material. A plant-derived crystalline cellulose was used as impregnating materials. A impregnated precursor was calcined at a temperature of 350 to 900℃ to obtain cobalt oxide particles having a particle size of 1 to 10㎛. The crystallization process and morphology according to the calcination temperature were examined, and the properties of the synthesized powder were evaluated using SEM and XRD. It was confirmed that a crystal phase of Co₃O₄ began to form around 350℃ and crystal growth occurred up to 900℃. At a temperature above 500℃, the Co₃O₄ crystal was changed to another crystal phase CoO.