• Journal of the Korea Institute of Building Construction
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• v.10 no.4
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• pp.75-82
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• 2010

As structures become larger, taller, and more diverse, a high degree of technology and expertise are required in the construction industry. However, it has been becoming difficult to construct under severe conditions and to fulfill the high performance needs of structures due to a lack of skilled construction engineers. To compensate for these weak points, high-performance concrete and performance specifications have been developed. The application of reliable high-fluidity concrete, which is one of these efforts, is expected to be effective in terms of overcoming severe conditions, reducing the number of workers required, and shortening the construction period. In order to apply high fluidity concrete in the field, practical mock-up tests were carried out to estimate whether self-compaction concrete could satisfy constructability needs. From the results, it was verified that the multi-component high fluidity concrete has excellent flowability in practical structures. In addition, it was shown that the temperature distribution in the concrete due to hydration heat is satisfactory. As a result, it is judged that multi-component high fluidity concrete can be utilized as an effective building material for various structures, including structures related to the electric power industry.

• Journal of the Korean Geosynthetics Society
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• v.14 no.3
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• pp.13-20
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• 2015

Inappropriate backfill material and poor compaction cause the damage to sewer and ground settlement. To deal with such problem, flowable backfill material has attracted attention recently. A basic study was conducted in a bid to obtain optimum mixing ratio of backfill material with the characteristics of rapid hardening, pseudo-plasticity, flowability and anti washout ability and enhance the cost efficiency of backfill material. Through the test of optimal mixing ratio of rapid hardening, evaluation of optimal mixing ratio of backfill material was conducted. As a result, required performance as well as cost efficiency could be achieved by adjusting plasticizer even in case of increasing W/M of the paste of rapid hardening to 100%.

• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.4
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• pp.89-98
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• 2010

Recently, many researches on bottom ash which is produced in the burning process of power plant are actively performed for its utilization for soil-subbase materials. In this paper, bottom ashes from 5 different power plants are prepared and several tests including compaction, CBR, and tri-axial compression are carried out for mixed bottom ash and weathered soil considering 3 replacement ratio of 30%, 50%, and 70%. Through the tests, CBR result over 20 are evaluated without plastic property, which shows availability of subbase material. With higher increase in replacement ratio of bottom ash, CBR of mixed soil increases due to the higher mechanical performance of bottom ash. However, replacement effects of bottom ash on friction angle and cohesion are evaluated to be little since bottom ash plays a little role in rearrangement of mixed soil. Bottom ash with a good mechanical property is evaluated to have reasonable bearing capacity which shows a good property for subbase materials.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.111-119
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• 2018

The air-void is known to be one of the influencing factors for estimating long-term performance of asphalt concrete. Most of all, confirming air void or density of pavement layer is important for quality control of field compaction level of asphalt concrete pavement. In this study, a non-nuclear type non-destructive density gage (NDDG) was used to estimate compacted air-voids of asphalt pavement as a non-destructive test method. Asphalt concrete slab specimens were prepared using 6 types of asphalt mixes in laboratory (lab) for lab NDDG test. Four different base structure materials were used to find out if there were any differences due to the type of base structure materials. The actual air-voids and NDDG air-voids were measured from 6 asphalt concrete slabs. Four sections of field asphalt pavements were tested using the NDDG, and actual air voids were also measured from field cores taken from the site where the NDDG air-void was measured. From lab and field experimental tests, it was found that the air-voids obtained by NDDG were not the same as the actual air-voids measured from the asphalt concrete specimen. However, it was possible to estimate air voids based on the relationship obtained from regression analysis between actual and NDDG air voids. The predicted air-voids based on the NDDG air-voids obtained from 50mm depth were found to be reliable levels with $R^2{\fallingdotseq}0.9$. Therefore, it was concluded that the air-voids obtained from NDDG could be used to estimate actual air-voids in the field asphalt pavement with a relatively high coefficient of determination.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2229-2233
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• 2015

The permeability of HMA(hot mixed asphalt) is a major influencing factor for long-term performance of the pavement. Especially, the lift thickness of the pavement during construction causes a wide range of physical properties of HMA. This study investigates the correlationship between the lift thickness and the physical properties of HMA through a series of laboratory experiments. The specimens were cored from a construction site of the dense graded asphalt pavement. The cored samples have various lift thickness and the number of compaction for the study. The results of the study show that the permeability of the sample decreases with the apperant density and t/NMAS, and the air void ratio. Therefore, the commonly used construction method as a constant lift thickness regardless of conditions needs to be reconsidered.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.6
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• pp.655-661
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• 2016

Relationships between saturated conductivity (Ks) and separate contents were evaluated from 44 soil series of arable lands: 18 for paddy fields and 26 for upland crop fields. Saturated hydraulic conductivities of A, B, and C horizons were determined with tension infiltrometer and Guelph permeameter in situ. Sand, silt, clay, and organic matter content of each horizon were analyzed. Based on correlation analysis, sand separate had a positive relationship with Ks for both paddy (r=0.27, p=0.017) and upland fields (r=0.24. p=0.030). Clay content had a negative relationship with Ks for paddy soils (r=-0.32, p=0.005) while significant correlation between them was not found for upland crop fields (r=-0.20, p=0.07). Organic matter content showed a positive relationship with Ks only for upland crop fields (r=0.33, p=0.002). Due to low correlation coefficients between separate contents and Ks, performance of pedotransfer functions was not enough to estimate Ks. It implies that hydraulic properties of arable lands were affected by other factors rather than particle characteristics. Platy structure and plow pan were suggested to limit Ks of paddy fields. Soil compaction and diversity of parent materials were proposed to influence Ks of upland crop fields. It suggests that genetic processes and artificial managements should be included in pedotransfer functions to estimate hydraulic properties appropriately.

• Journal of the Korean Geotechnical Society
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• v.32 no.2
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• pp.31-41
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• 2016

For sand and zeolite filter media in stormwater BMPs, media breakage effects on infiltration were investigated. Compaction effort and infiltration force were mainly examined for breakage sources. The 1-D column infiltration tests for un-compacted and compacted media filters were conducted to investigate the breakage effect on infiltration. As a result, the following findings were deduced: 1) particle breakage due to filtration forces was found to be relatively minimal; 2) un-compacted media had lesser amount of crushed particles and permeability fluctuations compared to compacted media; 3) even without the presence of suspended solids in the influent, reduction in permeability was found, which resulted from rearrangement and re-entrainment of media particle itself; 4) only media particle breakage resistance is considered, sand was revealed to have better performance compared to zeolite media.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.67-75
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• 1999

In this paper, we present an ASIC(Application Specific Integrated Circuit) design of wavelet transform filter Wavelet transform is used in lots of application fields which include image compression, because it has an excellent energy compaction. The operation characteristic and performance of wavelet transform filter are analyzed by using verilog-HDL(Hardware Description Language). In this paper, the designed wavelet transform filter uses line memory to improve data processing rate. Generally, when it reads and writes data of DRAM by using Fast Page Mode, input and output processing is very fast in horizontal direction but substantially slow in vertical direction. The use of line memory solves this low speed processing problem. As a result, though the size of the chip is getting larger, processing time for an image frame becomes 4.66ms. Generally, since the limit of 1 frame processing time on the data of TV video is 33ms, so it is appropriate for TV video.

• Advances in Computational Design
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• v.5 no.2
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• pp.195-207
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• 2020

The present study focuses on the application of artificial neural network (ANN) and Multiple linear Regression (MLR) analysis for developing a model to predict the unconfined compressive strength (UCS) and split tensile strength (STS) of the fiber reinforced clay stabilized with grass ash, fly ash and lime. Unconfined compressive strength and Split tensile strength are the nonlinear functions and becomes difficult for developing a predicting model. Artificial neural networks are the efficient tools for predicting models possessing non linearity and are used in the present study along with regression analysis for predicting both UCS and STS. The data required for the model was obtained by systematic experiments performed on only Kaolin clay, clay mixed with varying percentages of fly ash, grass ash, polypropylene fibers and lime as between 10-20%, 1-4%, 0-1.5% and 0-8% respectively. Further, the optimum values of the various stabilizing materials were determined from the experiments. The effect of stabilization is observed by performing compaction tests, split tensile tests and unconfined compression tests. ANN models are trained using the inputs and targets obtained from the experiments. Performance of ANN and Regression analysis is checked with statistical error of correlation coefficient (R) and both the methods predict the UCS and STS values quite well; but it is observed that ANN can predict both the values of UCS as well as STS simultaneously whereas MLR predicts the values separately. It is also observed that only STS values can be predicted efficiently by MLR.

• Computers and Concrete
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• v.21 no.4
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• pp.407-417
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• 2018

Concrete which is a composite material is one of the most important construction materials. Compressive strength is a commonly used parameter for the assessment of concrete quality. Accurate prediction of concrete compressive strength is an important issue. In this study, we utilized an experimental procedure for the assessment of concrete quality. Firstly, the concrete mix was prepared according to C 20 type concrete, and slump of fresh concrete was about 20 cm. After the placement of fresh concrete to formworks, compaction was achieved using a vibrating screed. After 28 day period, a total of 100 core samples having 75 mm diameter were extracted. On the core samples pulse velocity determination tests and compressive strength tests were performed. Besides, Windsor probe penetration tests and Schmidt hammer tests were also performed. After setting up the data set, twelve artificial intelligence (AI) models compared for predicting the concrete compressive strength. These models can be divided into three categories (i) Functions (i.e., Linear Regression, Simple Linear Regression, Multilayer Perceptron, Support Vector Regression), (ii) Lazy-Learning Algorithms (i.e., IBk Linear NN Search, KStar, Locally Weighted Learning) (iii) Tree-Based Learning Algorithms (i.e., Decision Stump, Model Trees Regression, Random Forest, Random Tree, Reduced Error Pruning Tree). Four evaluation processes, four validation implements (i.e., 10-fold cross validation, 5-fold cross validation, 10% split sample validation & 20% split sample validation) are used to examine the performance of predictive models. This study shows that machine learning regression techniques are promising tools for predicting compressive strength of concrete.