• 한국도로학회:학술대회논문집
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• 2001.10a
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• pp.37-40
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• 2001

• 한국도로학회:학술대회논문집
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• 1999.11a
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• pp.35-40
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• 1999

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.6
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• pp.38-44
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• 2019

A Convolution Neural Network(CNN) model was utilized to detect surface cracks in asphalt concrete pavements. The CNN used for this study consists of five layers with 3×3 convolution filter and 2×2 pooling kernel. Pavement surface crack images collected by automated road surveying equipment was used for the training and testing of the CNN. The performance of the CNN was evaluated using the accuracy, precision, recall, missing rate, and over rate of the surface crack detection. The CNN trained with the largest amount of data shows more than 96.6% of the accuracy, precision, and recall as well as less than 3.4% of the missing rate and the over rate.

• Journal of the Korean Society for Railway
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• v.19 no.1
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• pp.54-66
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• 2016

In this study, the absorbing boundary condition was adopted to prevent elastic wave propagation due to abrupt load condition changes in moving force analysis. It was proven to be effective in reducing inappropriate noise components. Furthermore, to verify whether fixed point excitation in a laboratory test can simulate train movement effectively, the results of dynamic analysis for fixed point excitation and moving force conditions were analyzed. The dynamic stability of an asphalt track structure under a KTX train condition was also studied. Additionally, the dynamic safety of asphalt tracks was verified by comparing the results of a moving force analysis under a KTX train load and a quasi-static analysis under the design standard Korean train load.

• International Journal of Highway Engineering
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• v.7 no.3 s.25
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• pp.11-21
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• 2005

To examine adequacy of existing multi-layer elastic analysis of layer interface conditions, this study compared outputs of finite element analysis and multi-layer elastic analysis as vertical load was applied to the surface of asphalt pavements. Structural pavement analysis considering influence of a horizontal load was also carried out in order to simulate passing vehicle loads under various interface conditions using ABAQUS, a three dimensional finite element program. Pavement performance depending on interface conditions was quantitatively evaluated and fundamental study of layer interface effect was performed in this study. As results of the study, if only vertical load is applied, subdivision of either fully bonded or fully unbonded is enough to indicate interface condition. On the other hand, when horizontal load is applied with vertical load, pavement behavior and performance are greatly changed with respect to layer interface condition.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.719-726
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• 2009

In this study, a series of push-off tests for lean concrete, aggregate, asphalt subbases mainly used in Korea were performed to investigate the friction characteristics between the slab and subbase layers. Use of separation membrane and wet condition of subbase were other parameters in the tests. Horizontal displacements of the slabs and friction coefficients were measured at 1st loading, stable condition (2nd and 3rd loadings), and wet condition (4th loading) by applying 40mm/hour horizontal loadings. Larger maximum friction coefficients were measured in order of the lean concrete, asphalt, aggregate, and subbases using the separation membrane at 1st loading, and in order of the asphalt, aggregate, lean concrete, and subbases using the separation membrane at stable and wet conditions. The friction coefficients of the aggregate and asphalt subbases which did not used the separation membrane decreased by the wet condition while the subbases using the separation membrane were not affected. Additional push-off tests for effects of slab thickness and temperature sensitivity of asphalt will be performed. And, effects of the friction characteristics between the slab and subbase layers on behavior and performance of concrete pavements will be investigated by structural analyses using the test results.

• Computational Structural Engineering
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• v.3 no.2
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• pp.89-95
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• 1990

As modern industry go further, a rigid concrete pavement has been widely constructed. The load carrying capacity of the flexible asphalt pavements is brought about by a layered system, distributing the load over the subgrade, rather than by the bending action of the slab. On the other hand, the rigid pavement, because of its rigidity and high modulus of elasticity, tends to distribute the traffic load over wide subbases, and its capacity of the strength is supplied by the slab itself. Thus, it is necessary to study the structural behavior of concrete slab under the variations of temperature changes and applied traffic loads. It reguires the development of finite element analysis program for the concrete highway pavement, which provides better understanding of concrete pavement behavior and effective design data to highway engineers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.171-182
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• 2022

The safe use of a structure requires it to be maintained in an undamaged state. Thus, a typical factor that determines the safety of a structure is a crack in it. In addition, cracks are caused by various reasons, damage the structure in various ways, and exist in different shapes. Making matters worse, if these cracks are unattended, the risk of structural failure increases and proceeds to a catastrophe. Hence, recently, methods of checking structural damage using deep learning and computer vision technology have been introduced. These methods usually have the premise that there should be a large amount of training image data. However, the amount of training image data is always insufficient. Particularly, this insufficiency negatively affects the performance of deep learning crack detection algorithms. Hence, in this study, a method of augmenting crack image data based on the image translation technique was developed. In particular, this method obtained the crack image data for training a deep learning neural network model by transforming a specific case of a asphalt crack image into a concrete crack image or vice versa . Eventually, this method expected that a robust crack detection algorithm could be developed by increasing the diversity of its training data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.951-960
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• 2006

Structural pavement analysis considering lateral loads of moving vehicle was carried out in order to simulate passing vehicle loads under various interface conditions. To verify of existing multi-layer elastic analysis of layer interface effect parameters, this study compared outputs by using ABAQUS, a three dimensional finite element program and KENLAYER, multi-layer elastic analysis as vertical load was applied to the surface of asphalt pavements. Pavement performance depending on interface conditions was quantitatively evaluated and fundamental study of layer interface effect parameters was performed in this study. As results of the study, if only vertical loads of moving vehicle is applied, subdivision of either fully bonded or fully unbonded is enough to indicate interface effect parameters. On the other hand, when lateral loads are applied with vertical loads, pavement behavior and performance are greatly changed with respect to layer interface conditions. The thinner thickness of the asphalt layer is and the smaller elastic moduli of the asphalt layer is, the more pavement behavior is influenced by interface conditions. In addition, regression analysis equation analytically computing tensile strain which was considered thicknesses and elastic moduli of the asphalt layer and layer interface effect parameters at the bottom of the asphalt layer was presented using database from numerical analyses on national pavement model sections.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.873-876
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• 2008

Although Permeable concrete is resently used as a pavement at a parking lot, a public squre and a bicycle road, we use without enough examining. most the maintenance of quality for Permeable concrete is only dealt with strength and color tone. also, there is not yet enough fundamental data about dynamical properties for strength, rate of void and water permeability. even when it is applied to at the scene, it is been a matter.