• 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.

• 한국도로학회:학술대회논문집
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• 2009.11a
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• pp.613-616
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• 2009

• International Journal of Highway Engineering
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• v.5 no.1 s.15
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• pp.11-18
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• 2003

Road roughness, as the key factor influencing not only drivers' ride quality and safety but also pavement deterioration, is one of the most important pavement performance indicator to be evaluated by users' subjective assessment. For this reason, a specific number of the pavement roughness has been adopted to monitor the condition of a road for pavement management systems and to evaluate the quality of newly constructed sections, however, none of the unified methodology was internationally accepted. In Korea highway network, road roughness has been used mainly to evaluate newly placed pavement by using 7.6m CP (California Profile meter) to calculate PrI (Profile Index). But this instrument is manually operated to measure road profiles by traffic closure and their interpretation depends on personal bias. Therefore, problems arisen from the manually operated instrument will be overcome by using the APL (Longitudinal Profile Analyzer) which can be operated in the speed of 80km per hour. A study was conducted to correlate the relation from both concrete and asphalt pavement between IRI (measured by APL) and PrI (measured by 7.6m CP). Test results showed that there was a good correlation between IRI and PrI.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.10
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• pp.2273-2280
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• 2013

This article introduces the next-generation air surveillance system and investigates how to design of front-end low noise amplifier of the ground station receiver. In consideration of the international standard documentation and the performance of existing products, the study conducts the link budget on the entire system so that it can be competitive in terms of receive sensitivity or reliability. To obtain a proper low noise amplifier, standards of design are decided so that such factors as gain, gain flatness, and reflective loss can be optimal. In its design, the bias circuit appropriate for the characteristics of low power, low noise, or high gain was built, and according to the results of the simulation conducted after the optimal design, its gain was 16.24dB, noise factor was 0.36dB, input-output reflective loss was -18dB and -28dB each, and frequency stability was 1.11. According to the results measured after the design, its gain was 17dB, noise factor was 0.51dB, gain flatness was 0.23dB, and input-output reflective loss was -18.28dB and -24.50dB each, so the results gained were suitable for building the overall system.

• Journal of IKEEE
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• v.5 no.1 s.8
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• pp.75-84
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• 2001

The reliable data relating to the condition of road surface is of increasing importance to deliver the road condition to driver and road management authority. This paper describes the development of a new high-speed. automatic, road data collection system, which collects the longitudinal road data with ${\sim}30cm$ interval covering full width of the road at 100km/h speed. The system calculates the international roughness index (IRI) from the collected data and displays the IRI and road profile data on the screen. To develope the system, we implement an optical range finder, advanced distance and motion detectors, and signal processing and display modules. The measurement accuracy of the system at 70km/h operation speed shows ${\pm}0.1m/km$ in the IRI for the standard road. To confirm the performance of the developed system, we also measure the IRI of a deployed highway road and compare the results with a conventional system and human eye measurement results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.5
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• pp.757-767
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• 2016

The power spectral density (PSD) for the road surface roughness on the bridges of minor roads in Wonju city and Hoengseong-gun, Gangwon-do is presented. To obtain the PSD, the road surface roughness on 18 different bridges with various superstructure type and span is measured by GPS at every 10 to 30cm interval. Assuming the PSD as the stationary normal probability process with zero mean value, the PSD of measured road surface roughness is obtained by applying the Maximum Entropy Method (MEM). A simple formula in evaluating the PSD of RC slab bridge, Rahmen bridge and PSC I-girder bridge which is applicable to the dynamic response analysis of bridges considering the road surface roughness is proposed. Using the calculated PSD curves, the road surface conditions on the 18 bridges are evaluated. The statistical relationship between the PSD and the IRI is presented by applying linear regression and correlation analysis.