• Korean Journal of Construction Engineering and Management
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• v.7 no.6
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• pp.151-164
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• 2006

Numerous efforts are currently underway to automate pavementcrack and joint sealing activities. Productivity improvements, improved safety and quality, and reduced road user costs motivate these developments. Recently, an automated pavement crack sealing machine has been developed to automate the process of sealing pavement cracks and joints in Korea. This paper mainly describes the results of the economic feasibility analysis revealed through its overall performance evaluation and field tests. Finally, it is concluded that the automated machine exceeds the performance in terms of productivity, safety, and quality required in conventional method, thus making the machine economically feasible.

• Smart Structures and Systems
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• v.18 no.3
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• pp.405-423
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• 2016

In this study, the feasibility of using telecommunication single-mode optical fiber (SMF) as a distributed fiber optic strain and crack sensor was evaluated in concrete pavement monitoring. Tensile tests on various sensors indicated that the $SMF-28e^+$ fiber revealed linear elastic behavior to rupture at approximately 26 N load and 2.6% strain. Six full-scale concrete panels were prepared and tested under truck and three-point loads to quantify the performance of sensors with pulse pre-pump Brillouin optical time domain analysis (PPP-BOTDA). The sensors were protected by precast mortar from brutal action during concrete casting. Once air-cured for 2 hours after initial setting, half a mortar cylinder of 12 mm in diameter ensured that the protected sensors remained functional during and after concrete casting. The strains measured from PPP-BOTDA with a sensitivity coefficient of $5.43{\times}10^{-5}GHz/{\mu}{\varepsilon}$ were validated locally by commercial fiber Bragg grating (FBG) sensors. Unlike the point FBG sensors, the distributed PPP-BOTDA sensors can be utilized to effectively locate multiple cracks. Depending on their layout, the distributed sensors can provide one- or two-dimensional strain fields in pavement panels. The width of both micro and major cracks can be linearly related to the peak strain directly measured with the distributed fiber optic sensor.

• Korean Journal of Construction Engineering and Management
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• v.5 no.2 s.18
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• pp.90-105
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• 2004

Machines for crack sealing automation have been continually developed since the early 1990's because of the effectiveness of crack sealing that would be able to improve safety, quality and productivity. It has been considered challenging problem to detect crack network in pavement which includes noise (oil marks, skid marks, previously sealed cracks and inherent noise). Moreover, it is required to develop crack network mapping and modeling algorithm in order to accurately inject sealant along to the middle of cut crack network. The primary objective of this study is to propose machine vision algorithms (digital image processing algorithm and path planning algorithm) for fully automated pavement crack sealing. It is anticipated that the effective use of the proposed machine vision algorithms would be able to reduce error rate in image processing for detecting, mapping and modeling crack network as well as improving quality and productivity compared to existing vision algorithms.

• International Journal of Highway Engineering
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• v.18 no.4
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• pp.19-28
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• 2016

PURPOSES : Long-life asphalt pavements are used widely in developed countries. In order to be able to devise an effective maintenance strategy for such pavements, in this study, we evaluated the performance of the long-life asphalt pavements constructed along the national highways in South Korea. Further, an economic evaluation of the long-life asphalt pavements was performed based on a life-cycle cost analysis. We aimed to devise a model for evaluating the performance of long-life asphalt pavements using the national highway pavement management system (PMS) database as well as for analyzing the economic feasibility of such pavements, in order to promote their use in South Korea. METHODS : The maintenance history and pavement performance data were obtained from the national highway PMS database. The pavement performances for a total of 292 sections of 10 lanes (5 northbound lanes and 5 eastbound lanes) of national highways were used in this study. Models to predict the performances of hot mix asphalt (HMA) and long-life asphalt pavements under two distinct traffic conditions were developed using a simple regression method. Further, the economic feasibility of long-life asphalt pavements was evaluated using the Korea Pavement Management System (KoPMS). RESULTS : We developed service-life prediction models based on the traffic volume and the equivalent of single-axle load and found that long-life asphalt pavements have service lives 50% longer than those of HMA pavements. Further, the results of the economic analysis showed that long-life asphalt pavements are superior in terms of various economic indexes, including user cost, delay cost, total cost, and user benefits, even though their maintenance cost is higher than that of HMA pavements. A comparison of the economic feasibilities of the various groups showed that group A is superior to HMA pavements in all aspects except in terms of the maintenance criterion (crack 20% or higher) as per the NPV index. However, the long-life asphalt pavements in group B were superior in terms of the maintenance criterion (crack 25% or higher) regardless of the economic feasibility. CONCLUSIONS : The service life of long-life asphalt pavements was found to be approximately 50% longer than that of HMA pavements, regardless of the traffic volume characteristics. The economic feasibility of long-life asphalt pavements was evaluated based on the KoPMS. The results of the economic analysis were the following: long-life asphalt pavements are exceptional in terms of almost all factors, such as user cost, delay cost, total cost, and user benefit; however, the exception is the maintenance cost. Further, the economic feasibility of the long-life asphalt pavements in group B was found to be better than that of the HMA pavements (crack 25% or higher).

• 한국지형공간정보학회:학술대회논문집
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• 2002.11a
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• pp.93-99
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• 2002

• 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 Korea institute for structural maintenance and inspection
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• v.13 no.1 s.53
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• pp.106-114
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• 2009

The steel design based on the width of transverse crack which is the major factor to affect a long-term performance of continuously reinforced concrete pavement was developed. For this study, twenty-one cities of Texas were selected and the temperature data was collected at those locations during the past ten years. From the data, zero-stress temperatures were calculated by the PavePro program and the widths of transverse crack were analyzed by the CRCP program. The variables used to this numerical analysis were slab thickness, coefficient of thermal expansion of concrete, steel ratio, and design temperature. The total of 448 factorial runs were made and the regression analysis was performed using the results. Steel ratios from the regression equations were backcalculated and a steel design table was proposed.

• International Journal of Highway Engineering
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• v.9 no.2 s.32
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• pp.39-49
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• 2007

The objective of this study was to investigate features of transverse crack occurrence and propagation in continuously reinforced concrete pavement(CRCP) when subjected to environmental loading. The finite element model of CRCP was developed and the element removal method was implemented to predict the crack propagation process. To investigate the effect of the type of environmental loading on the CRCP behavior and cracking aspects, the following three different cases were considered: (1) the temperature gradient between top and bottom of the slab does not vary and the constant temperature drop throughout the depth occurs; (2) the temperature at the slab bottom does not vary and the temperature gradient increases; and (3) the temperature between the mid-depth and the bottom of the slab is the same and does not vary and the temperature at the top decreases. The analysis results showed that the crack occurrence and propagation through the depth of the slab in CRCP were significantly affected by the type of environmental loading. The changes in stress distribution and displacements during the crack occurrence and propagation process could also be investigated.

• International Journal of Highway Engineering
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• v.2 no.3
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• pp.145-153
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• 2000

Pavement evaluation is a fundamental component for rational pavement management. Optimal rehabilitation method and the priority of rehabilitation should be based on the evaluation data. Some types of pavement condition index are needed for objective evaluation of Pavement condition and management of road network. In this study a expressway concrete pavement condition index model is developed through regression analysis that correlates panel rating with distress measurement from the test sections. The derived condition index can be used for network level PMS for the expressway concrete pavement. Correlation coefficient of the model was 0.68. The selected independent variables were International Roughness Index, crack and area of patching.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2502-2507
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• 2003

In this paper, a crack sealing robot is developed. The crack sealing robot is built to detect, track, and seal the crack on the pavement. The sealing robot is required to brush all dirt in the crack out for preparing a better sealing job. Camera calibration has been done to get accurate crack position. In order to perform a cleaning job, the explicit force control method is used to regulate a specified desired force in order to maintain constant contact with the ground. Experimental studies of force tracking control are conducted under unknown environment stiffness and location. Crack tracking control is performed. Force tracking results are excellent and the robot finds and tracks the crack very well.