• International Journal of Highway Engineering
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• v.11 no.4
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• pp.95-105
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• 2009

This study was conducted to investigate the effects of concrete flexural strength and surface smoothness, which were pay factors of concrete pavements, on pavement performance, and to develop the methodologies to determine the proper allowable ranges according to the magnitudes of those pay factors. The concrete flexural strength was analyzed using the AASHTO, power, and linear fatigue failure models, and the surface smoothness was analyzed for the roughness indices of PSI, IRI, and PrI using the AASHTO model. The analysis results showed that the allowable range of the flexural strength should be determined using the rate between the deficiency and strength, and the penalty should be linearly proportional to the strength deficiency rate because the linear relationship between the strength deficiency rate and the reduction in pavement life was observed. As the initial surface smoothness became better, the smoothness deficiency rate should be larger. The penalty due to the surface smoothness deficiency should also be linearly proportional to the smoothness deficiency rate.

• International Journal of Highway Engineering
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• v.12 no.2
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• pp.123-127
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• 2010

In this study, the profiles of optimized rehabilitated section was measured by a lightweight inertial profiler, and pavement smoothness was evaluated. To analyze the repeatability of the used lightweight profiler, two repeatable measurements were conducted. The agreement between two repeatable measurements were evaluated by Cross-correlation function. Pavement smoothness of the optimized rehabilitated pavement section and existing area was compared in terms of International Roughness Index and Profilograh Index. In general, the pavement smoothness of the rehabilitated sections was not good compared to the existing pavement sections. The analysis results could be used for the evaluation of pavement smoothness of the optimized rehabilitated pavement sections.

• International Journal of Highway Engineering
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• v.10 no.3
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• pp.189-197
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• 2008

Using a 5 year(2003 to 2007) pavement condition survey data from the highway pavement management system(HPMS), the roughness of the bridge deck pavement was analyzed. Based on the result of this analysis, this study tried to identify the factors affecting the deterioration of the bridge deck pavement condition. The data from HPMS indicates that the roughness of the bridge deck pavement is worse than that of the general pavement on the roadbed. The worse roughness of the bridge deck pavement is caused by the settlement of approach slab as well as the surface distress on the bridge deck pavement. In order to improve effectively the roughness of the bridge deck pavement, a management system was established in which not only the regular automated pavement condition survey to check the distress of surface of the bridge deck pavement was adopted but an automated surface profiler to check the degree of settlement of approach slab was applied.

• International Journal of Highway Engineering
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• v.12 no.2
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• pp.9-16
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• 2010

Roughness is the most important factor to maintain the road performance, and affects greatly on the design life in Jointed Plain Concrete pavements. Also, the factors the evaluate pavement‘s commonality is the three method such as functionality, safety and structural performance. In evaluating function of road, representative factors is the roughness, which has been used to determine maintenance time as key standard. As research for roughness is absence in pavement design. Applied roughness-model had a low-reliability in Korea. Therefore, it is needed to develop reliable model in road roughness. In this research, uniform specific is applied to distribute them after selecting the concrete pavements. Concrete pavement is divided by sections of 238. Total length of this sections has 281km and account for 16% of total road length in korean concrete pavements for selected sections. Considering the korean roughness-model, the evaluation of roughness is performed for the freezing index, average annual rainfall, condition for the base, the amount of traffic as well as spalling(%), cracking(%), age(year) at the selected section at the selected section. Also, additional sections is selected to evaluate various age which affects on the roughness. As a result of the analysis, it showed that spalling(%), cracking(%), age(year), and the condition of the base affected road roughness. When the correlation with the road roughness was analyzed, the reliable model for road roughness was proposed, and the ratio that can explain road roughness was R2-68.8% and P value-0 which is statistically meaningful.

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.135-144
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• 2008

The dynamic loads imposed by moving vehicles have variations in the magnitude due to the surface roughness of the pavement systems and the larger dynamic loads than the design loads may affect the pavement performance. This paper presents variations of the moving dynamic vehicle loads due to the pavement surface roughness. This study was performed as a basic study to apply the pay factor to the surface roughness for the improvement of pavement quality and performance. The profile data was obtained from the old and new pavements and the analysis was performed to investigate the dynamic loads when vehicles move on the pavements having those profiles. The artificial profiles were also developed to find the effects of the vehicle speed, wavelength and amplitude of the surface roughness on the dynamic vehicle loads. The increase in the load magnitude due to the surface roughness affects the stresses and strains of pavements and finally reduces the pavement life. The methodology to obtain the relationship between the surface roughness and the pavement performance was proposed in this study.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.167-175
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• 2011

Evaluation of fuel consumption for the various road condition and vehicle type is necessary to perform the economic analysis of road construction which is important for the efficient design and management of road. Economic analysis of road should consider the social cost which can be divided into agency cost including initial construction expense, maintenance cost, and so on, and user cost consisting of vehicle operating cost, congestion cost, etc. Since vehicle operating cost depends on the traffic volume, fuel consumption that is a major part of vehicle operating cost will change by traffic volume as well. Fuel consumption is significantly affected by vehicle speed and road condition, especially the roughness. Thus, fuel consumption should be evaluated in terms of road condition, which is not currently considered. In this study, the estimation model of fuel consumption for the passenger cars in Korea has been developed by considering the road condition. First, the relationship between vehicle speed and fuel consumption that is used to calculate the vehicle operating cost for investment evaluation of transportation facility and the initial feasibility study of road construction was investigated. Second, with the consideration of road roughness, fuel consumption of the passenger car was measured. From the measurement, it was found that fuel consumption increased by $80m{\ell}$ per 100km driving as the roughness increased by 1m/km. Therefore, it is recommended that for the economic analysis of road design and management, the fuel consumption should be a function of road roughness.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.55-63
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• 2021

The roughness of the road is an important factor directly connected to the ride comfort, and is an evaluation item for functional evaluation and pavement quality management of the road. In this study, data on the road surface were acquired using the latest 3D geospatial information construction technology of ground LiDAR, drone photogrammetry, and drone LiDAR, and the accuracy and roughness of each method were analyzed. As a result of the accuracy evaluation, the average accuracy of terrestrial LiDAR were 0.039m, 0.042m, 0.039m RMSE in X, Y, Z direction, and drone photogrammetry and drone LiDAR represent 0.072~0.076m, 0.060~0.068m RMSE, respectively. In addition, for the roughness analysis, the longitudinal and lateral slopes of the target section were extracted from the 3D geospatial information constructed by each method, and the design values were compared. As a result of roughness analysis, the ground LiDAR showed the same slope as the design value, and the drone photogrammetry and drone LiDAR showed a slight difference from the design value. Research is needed to improve the accuracy of drone photogrammetry and drone LiDAR in measurement fields such as road roughness analysis. If the usability through improved accuracy can be presented in the future, the time required for acquisition can be greatly reduced by utilizing drone photogrammetry and drone LiDAR, so it will be possible to improve related work efficiency.

• International Journal of Highway Engineering
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• v.3 no.2 s.8
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• pp.131-140
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• 2001

Concrete pavement of Jungbu Expressway composed of CRCP(Continuously Reinforced Concrete Pavement) and JCP(Jointed Concrete Pavement). The CRCP was firstly constructed and applied to new expressway in Korea. It is a good source of the study to analyze the performance of CRCP and JCP because it experiences same amount of traffic and environmental loading. Up to the present, condition survey has conducted several times during 13 years but roughness measurement has not been carefully conducted. Through comparisons among several types of pavement(CRCP, JCP, Asphalt) by roughness, CRCP is superior to JCP. In addition, connected sections in the highway such as bridges and tunnels that have higher IRI values, about 5mm/m, than normal sections should be considered appropriated maintenance such as diamond grinding. The relationship between IRI and distresses carried out by Korea Highway Cooperation in 1999 skewed that the number of crack is related to IRI value in JCP, while other distresses of JCP and CRCP are not shown clearly. The comparison study with IRI values between Jungbu Expressway and GPS-3(JCP) and GPS-5(CRCP) of LTPP data also showed that roughness of Jungbu Expressway is not inferior to that of the state. Some of section showed larger values of IRI are linked with under-9round structures for passages and drainages. The overall performance considering only roughness, the CRCP is also superior to JCP in sections with under-ground tunnels.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2018.06a
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• pp.77-77
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• 2018

Panel level packaging (PLP) 공정은 차세대 반도체 패키징 기술로써 wafer level packaging 대비 net die 면적이 넓어 생산 단가 절감에 유리하다. PLP 공정에 적용되는 구리 재배선 층 (RDL, redistribution layer)은 두께 불균일도에 의해 전기 저항의 유동이 민감하게 변화하기 때문에 RDL의 두께를 균일하게 형성하는 것은 신뢰성 측면에서 매우 중요하다. 구리 RDL은 주로 도금 공정을 통해 형성되며, 균일한 도금막 형성을 위해 도금조에 평탄제를 첨가하여 도금 속도를 균일하게 한다. 도금막에 대한 흡착은 주로 평탄제의 imine 작용기에 포함된 질소 원자가 관여하며, imine 작용기의 4차화에 의한 평탄제의 흡착 정도를 제어하여 평탄제 성능을 개선할 수 있다. 본 연구에서는 도금 평탄제에 포함된 imine 작용기의 질소 원자를 4차화하여 구리 RDL의 도금 두께 불균일도를 제어하고자 하였다. 유기첨가제와 4차화 반응을 위해 알킬화제로써 dimethyl sulfate의 비율을 조절하여 각각 0, 50, 100 %로 4차화 반응을 진행하였다. 평탄제의 4차화 여부를 확인하기 위해 gel permeation chromatography (GPC) 분석을 실시하였다. 도금은 20 ~ 200 um의 다양한 배선 폭을 갖는 구리 RDL 미세패턴에서 진행하였으며, 4차화 평탄제를 첨가하여 광학 현미경과 공초점 레이저 현미경을 통해 도금막 표면과 두께에 대한 분석을 실시하였다. GPC 분석을 통해 4차화 반응 후 알킬화제에 의해 나타나는 GPC peak이 감소한 것을 확인하였다. 광학 현미경 및 공초점 레이저 현미경 분석 결과, 4차화된 질소 원자가 존재하지 않는 평탄제의 경우, 도금 시 도금막의 두께가 불균일하였으며 단면 분석 시 dome 형태가 관찰되었다. 또한 100 % 4차화를 실시한 평탄제를 첨가하여 도금 한 경우 마찬가지로 두께가 불균일한 dish 형태의 도금막이 형성되었다. 반면, 50 % 4차화를 적용한 평탄제를 첨가한 경우, 도금막 단면의 형태는 평평한 모습을 보였으며 매우 양호한 균일도를 가지는 것으로 확인되었다. 이로 인해 imine 작용기를 포함한 평탄제의 4차화 반응을 통해 구리 RDL의 단면 형상 및 불균일도가 제어되는 것을 확인하였으며, 4차화된 imine 작용기의 비율을 조절하여 높은 균일도를 갖는 구리 RDL 도금이 가능한 것으로 판단되었다.

• International Journal of Highway Engineering
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• v.14 no.2
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• pp.29-36
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• 2012

In this study, frequently passing vehicles with two, three, four, and five axles were chosen through traffic volume analysis in Kyung-In Expressway in order to analyze how the road roughness and vehicle speed affect on the dynamic loads for roads in various vehicle classes. Dynamic loads according to chosen vehicles are estimated by TruckSim program. Dynamic load amplification factor is ratio between dynamic and static loads, and it is also determined for each vehicle classes. From the result of dynamic loads estimated by the dynamic load amplification factor, it is shown that for three-axles vehicle, when IRI is 3.5 and vehicle speed is 100km/hr, asphalt pavements receive additional 36% of static loads in maximum. The analysis of the amplification factor according to each vehicle classes also indicates that the amplification factor increases as the distance between the axles becomes smaller and each axle receives more loads.