• Title/Summary/Keyword: 아스팔트포장

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Performance Evaluation of Asphalt Pavement Reinforced with Glass Fiber Sheet Type of Geosynthetics (유리섬유시트 형태의 토목섬유로 보강된 아스팔트 포장의 공용성 평가)

  • Cho, Sam-Deok;Lee, Dae-Young
    • Journal of the Korean Geosynthetics Society
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    • v.10 no.3
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    • pp.1-8
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    • 2011
  • This paper presents the performance evaluation of asphalt pavement reinforced with fiber sheet type of geosynthetics and observations conducted to evaluate the practical efficiencies and performance of overlay asphalt pavement reinforced with geosynthetics. In this study, performance evaluation were performed for the six section of construction site. The performance indcators of asphalt pavement reinforced with geosynthetics has been collected Automatic Road Analyzer (ARAN), Falling Weight Deflectometer (FWD) and have been analyzed for rutting, cracking ratio, falling weight and international roughness index. As a result of performance evaluations, geosynthetics reinforced asphalt pavement is sigficant effect on increasing a cracking resistance than the non-reinfroced asphalt pavement, also rutting and crak is slowly increase as incerasingly performance period.

A Study on the Characteristics of Fatigue Failure for Asphalt Pavement (아스팔트포장(鋪裝)의 피로파괴특성(疲勞破壞特性)에 관한 연구(硏究))

  • Seo, Chae Yeon;Lee, Kye Hak
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.7 no.2
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    • pp.9-20
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    • 1987
  • The main object of this study are to investigate an effect of the characteristics of materials and to seize the behavior of fatigue failure of asphalt pavement with the results of laboratory tests for asphalt mixtures. In order to prove the practical application of applied methods, the relationships between temperature, depth of asphalt layer, elastic modulus and the number of fatigue failure by the results of elastic theory and fatigue failure envelope are also considered.

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Evaluation of the Performance and Moisture Retaining Ability in Semi-Rigid Pavement (반강성포장의 성능 및 보수성 평가)

  • Park, Tae-Soon
    • International Journal of Highway Engineering
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    • v.10 no.2
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    • pp.69-79
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    • 2008
  • This study presents the test results on the performance and the moisture retaining ability of semi rigid pavement using the moisture retaining grouting. The two kinds of the grouting materials were used for the Laboratory tests. The method of the tests includes the compression(3 hours and 7 days) and flexural strength(7 days) varying the P lot flow values. The test results show that the variation of the P lot value has no great effects on the strength, however, the different strength was found as the different grouting materials were used. The performance of the semi rigid pavement was evaluated varying the air void ration of the base asphalt pavement. The test results show that the flexural strength of the semi rigid pavement increases with increasing the air void of the base asphalt pavement so that the flexural strength of the semi rigid asphalt pavement can be effected by the air void of the base asphalt pavement. The moisture retaining tests were conducted and compared in the field the comparisons were made with the dense grade asphalt pavement and the semi rigid asphalt pavement with and without spraying the water. The difference of the temperature of the semi rigid pavement with the spraying water has recorded $11^{\circ}C$ when it compared with the dense grade asphalt pavement and $4^{\circ}C$, when it compared with the semi rigid pavement without the spraying the water. It can be seen that decrease the temperature of the pavement by the moisture retaining ability from the semi rigid pavement.

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A Study on the Economical Analysis Model for Asphalt Pavementin Congestion Area of Metropolitan (대도시 혼잡구간의 아스팔트 포장에 대한 경제성 분석 모델 연구)

  • Jo, Byung Wan;Tae, Ghi Ho;Kim, Do Keun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.5D
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    • pp.771-781
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    • 2006
  • This Study is about the development of LCC Analysis Model and Evaluation of VE. It was carried out to help the person's intention decision about choosing the pavement construction method that can deal with 'Pavement Life Factor' like Area Character and Traffic Volume efficiently, by considering the total life cycle cost of pavement life cycle happens according to the numbers of public use year. For this, we developed the new LCC Analysis Model by using the Data of Seoul city the representative city in Korea, and carried out VE Evaluation that reflects the opinions of specialists. This Analysis Model consists of cost items that affects directly the choice of pavement construction, except for the common cost items of the various pavement construction. And we investigated the propriety by applying our model to the example line that are used for the public at present. About the base data of cost items that are used for our analysis, we enhanced our model's confidence by using the statistics data of Seoul and the standard data of unit cost calculation.

A Study on Crack Detection in Asphalt Road Pavement Using Small Deep Learning (스몰 딥러닝을 이용한 아스팔트 도로 포장의 균열 탐지에 관한 연구)

  • Ji, Bongjun
    • Journal of the Korean GEO-environmental Society
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    • v.22 no.10
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    • pp.13-19
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    • 2021
  • Cracks in asphalt pavement occur due to changes in weather or impact from vehicles, and if cracks are left unattended, the life of the pavement may be shortened, and various accidents may occur. Therefore, studies have been conducted to detect cracks through images in order to quickly detect cracks in the asphalt pavement automatically and perform maintenance activity. Recent studies adopt machine-learning models for detecting cracks in asphalt road pavement using a Convolutional Neural Network. However, their practical use is limited because they require high-performance computing power. Therefore, this paper proposes a framework for detecting cracks in asphalt road pavement by applying a small deep learning model applicable to mobile devices. The small deep learning model proposed through the case study was compared with general deep learning models, and although it was a model with relatively few parameters, it showed similar performance to general deep learning models. The developed model is expected to be embedded and used in mobile devices or IoT for crack detection in asphalt pavement.