PURPOSES : The actual service life of repair methods applied to cement concrete pavement is analyzed based on de-icing agent usage. METHODS : Highway PMS data pertaining to de-icing agent usage are classified into three grades: low (1~5 ton/lane/year), medium (5~8 ton/lane/year), and high (greater than 8 ton/lane/year). The repair methods considered include diamond grinding, patching, joint repair, partial depth repair, and asphalt overlay on five major highways. The service life of each repair method is analyzed based on the usage level of the de-icing agent. RESULTS : The service lives of the applied repair methods are much shorter than expected. It is confirmed that the service life afforded by diamond grinding, patching, and joint repair methods are not significantly affected by the use of de-icing agents, whereas that afforded by asphalt overlay and partial depth repair methods is affected significantly. The service life afforded by the asphalt overlay and partial depth repair methods decreases at high usage levels of the de-icing agent (greater than 8 ton/lane/year). CONCLUSIONS : Among the repair methods considered, the service life afforded by partial depth repair and asphalt overlay is affected significantly by the amount of de-icing agent used. Additionally, the differences between the expected and actual analyzed service lives should be considered in the next-generation maintenance strategy for cement concrete pavements.

PURPOSES : The study aims to predict the service life of national highway asphalt pavements through deep learning methods by using maintenance history data of the National Highway Pavement Management System. METHODS: For the configuration of a deep learning network, this study used Tensorflow 1.5, an open source program which has excellent usability among deep learning frameworks. For the analysis, nine variables of cumulative annual average daily traffic, cumulative equivalent single axle loads, maintenance layer, surface, base, subbase, anti-frost layer, structural number of pavement, and region were selected as input data, while service life was chosen to construct the input layer and output layers as output data. Additionally, for scenario analysis, in this study, a model was formed with four different numbers of 1, 2, 4, and 8 hidden layers and a simulation analysis was performed according to the applicability of the over fitting resolution algorithm. RESULTS: The results of the analysis have shown that regardless of the number of hidden layers, when an over fitting resolution algorithm, such as dropout, is applied, the prediction capability is improved as the coefficient of determination (R2) of the test data increases. Furthermore, the result of the sensitivity analysis of the applicability of region variables demonstrates that estimating service life requires sufficient consideration of regional characteristics as R2 had a maximum of between 0.73 and 0.84, when regional variables where taken into consideration. CONCLUSIONS : As a result, this study proposes that it is possible to precisely predict the service life of national highway pavement sections with the consideration of traffic, pavement thickness, and regional factors and concludes that the use of the prediction of service life is fundamental data in decision making within pavement management systems.

PURPOSES: The purpose of this study is to analyze the service life of expressway pavement based on both traffic volumes and use of deicing chemicals. METHODS: A database was built using expressway rehabilitation history information from over the last decade. In order to estimate the service life of expressway pavement, various analysis methods were considered, and a decision was made to perform analysis using a method based on an accumulated rehabilitation ratio. The service life of expressway pavement was then analyzed by classifying the scale of traffic volume and extent of de-icing chemicals used. RESULTS: The service life of PMA and SMA ranged from 7.8 to 10.6 years and from 9.9 to 12.0 years, respectively. The service life of JCP ranged from 16.0 to 22.2 years, and the service life of CRCP was 33.5 years on average. Results of assessing service life according to traffic volumes and de-icing chemicals showed that the lower the traffic volumes were, the greater the service life of PMA and JCP, and the less that de-icing chemicals were applied, the greater the service life of JCP. CONCLUSIONS : The dependence of expressway pavement service life on traffic volumes and de-icing chemicals makes it possible to apply LCCA for regional maintenance plans and cost-effective selection of expressway pavement type.

현재 공용되고 있는 국내공항은 인천국제공항공사에서 관리하고 있는 인천국제공항과 한국공항공사에서 관리하고 있는 김포국제공항 외 13개 공항이 운영되고 있다. 두 공항공사 모두 효율적인 포장관리를 위해 포장관리시스템(PMS: Pavement Management System)을 구축하여 공항포장상태를 평가하고, 보수의 우선순위를 선정하여 보수방안을 결정한다. 포장상태평가는 보통 5년을 주기로 시행되고 있으며, 포장표면결함의 자료를 통해 포장상태지수(PCI: Pavement Condition Index)가 산출된다. 이러한 지수를 통해 공용중인 공항포장의 상태와 보수를 필요로 하는 시점을 판단 할 수 있다. 기존에 개발된 공항포장 공용성 예측모형은 크게 아스팔트포장과 콘크리트포장으로 나뉘어, 재령과 교통량에 따른 통합된 PCI 예측모형을 개발하였다. 하지만 공항별로 준공시기와 환경인자들이 다르게 때문에 상당한 오차가 발생하여, 모든 공항에 적용하기에는 한계가 있다. 또한 주로 활주로를 대상으로 연구가 진행되었으며, 유도로 및 계류장에 관한 선행연구는 아직까지는 미흡한 상태이다. 따라서 본 논문에서는 국내 콘크리트공항포장의 각각의 동질성구간에 대한 공용성 예측모형을 위한 연구를 진행하였다. 모든 단면이 아스팔트 포장인 울산공항과 군산공항을 제외한 13개 공항의 콘크리트 포장 부분의 PCI 자료를 수집하였고 활주로, 유도로, 계류장에 따라 크게 분류하였다. 분류된 각 구간은 동질성 구간별로 세분화하여 재령에 따른 PCI변화 추이를 살펴보았다. 본 논문에서는 인천국제공항공사, 한국공항공사, 한양대학교 및 (주)로드텍의 협조를 얻어 각 공항의 포장평가 조사보고서를 수집하였다. 각 공항별 동질성 구간의 준공년도와 재포장 시점을 분석하였으며, 이 시점을 기준으로 재령에 따른 PCI 변화 추이를 살펴보았다. 또한 보수를 시행한 구간에 대하여 조사하였으며, 이 구간에 대해서는 보수시점의 PCI값을 100으로 가정하고, 이 후 재령에 따른 PCI 변화를 살펴보았다. 이러한 PCI의 변화추이를 회귀분석하여 각각 선형과 지수형태로 나타냄으로써 각 공항별 동질성 구간에 따른 콘크리트 공항포장 예측모형을 개발하였다. 이렇게 개발된 모형을 통하여 공항포장설계수명인 재령 20년일 때의 PCI값을 예측하였고, 재포장이 요구되는 ‘Critical PCI`값인 70으로 저감되기까지의 공용연수를 나타내었다. 각 공항의 동질성 구간에 따른 예측모형들을 비교 검토해 봄으로써, 각 공항의 특성과 공용수명을 예측할 수 있었다.