포트홀은 아스팔트 도로 위에서 반복적인 하중으로 인해 일부가 떨어져 나가며 발생하는 패임을 의미한다. 포트홀은 습기에 취약해 특히 장마철에 큰 영향을 받으며, 이로 인해 대형교통사고와 높은 개보수 비용이 발생한다. 매년 포트홀 로 인한 피해와 사고는 언론을 통해 지속적으로 보도 되고 있다. 이러한 피해를 최소화하기 위해서는 사고가 발생하기 전 적절한 시기에 포트홀이 보수되어야 한다. 이를 위해서는 정확한 포트홀 면적 탐지가 선행되어야 한다. 포트홀 면적 의 정확한 탐지는 도로포장의 유지관리 및 보수 전략 수립에 매우 중요한 과정이다. 이에 따라 본 연구에서는 2,086의 포트홀 이미지를 기반으로 학습하고 탐지하였다. 비정형 탐지에 최적화된 Mask R-CNN을 활용하여 포트홀의 전체적인 면적을 탐지하였으며, 탐지 정확도를 높이기 위해 SwinT 백본 네트워크를 사용하였다. 그 결과, 90% 이상의 높은 정확 도로 포트홀의 면적을 탐지하였다. 추후 이 연구를 바탕으로 적절한 시기에 개보수 시기를 예측하여 포트홀로 인한 피해 와 사고를 줄이는 데 기여할 것이다.

In the contemporary era, 3D printing technology has become widely utilized across diverse fields, including biomedicine, industrial design, manufacturing, food processing, aerospace, and construction engineering. The inherent advantages of automation, precision, and speed associated with 3D printing have progressively led to its incorporation into road engineering. Asphalt, a temperature-responsive material that softens at high temperatures and solidifies as it cools, presents distinctive challenges and opportunities in this context. For the effective implementation of 3D printing technology in road engineering, 3D printed asphalt (3DPA) must exhibit favorable performance and printability. This requires attributes such as good fluidity, extrudability, and buildability. Furthermore, materials utilizing 3DPA for crack repair should possess high viscosity, elasticity, toughness, superior high-temperature stability, and resistance to low-temperature cracking. These characteristics ultimately contribute to enhancing pavement longevity and ensuring worker safety.

PURPOSES : This study uses deep learning image classification models and vehicle-mounted cameras to detect types of pavement distress — such as potholes, spalling, punch-outs, and patching damage — which require urgent maintenance. METHODS : For the automatic detection of pavement distress, the optimal mount location on a vehicle for a regular action camera was first determined. Using the orthogonal projection of obliquely captured surface images, morphological operations, and multi-blob image processing, candidate distressed pavement images were extracted from road surface images of a 16,036 km in-lane distance. Next, the distressed pavement images classified by experts were trained and tested for evaluation by three deep learning convolutional neural network (CNN) models: GoogLeNet, AlexNet, and VGGNet. The CNN models were image classification tools used to identify and extract the combined features of the target images via deep layers. Here, a data augmentation technique was applied to produce big distress data for training. Third, the dimensions of the detected distressed pavement patches were computed to estimate the quantity of repair materials needed. RESULTS : It was found that installing cameras 1.8 m above the ground on the exterior rear of the vehicle could provide clear pavement surface images with a resolution of 1 cm per pixel. The sensitivity analysis results of the trained GoogLeNet, AlexNet, and VGGNet models were 93 %, 86 %, and 72 %, respectively, compared to 62.7 % for the dimensional computation. Following readjustment of the image categories in the GoogLeNet model, distress detection sensitivity increased to 94.6 %. CONCLUSIONS : These findings support urgent maintenance by sending the detected distressed pavement images with the dimensions of the distressed patches and GPS coordinates to local maintenance offices in real-time.

PURPOSES: The objectives of this study are to analyze the current status of pothole during a rainy season and to suggest a future pavement maintenance method via pothole analysis. METHODS: Potholes are caused by moisture submerged in pavement. The pore pressure caused by traffic and environmental loads causes failure between the aggregate and asphalt binder. Thus, heavy rain is a primary pothole creator, especially in aged pavement. To prevent accidents on roadways, Gyeonggi-do has initiated a fast pothole repair program. However, the number of potholes increase every year. In this study, the current status of potholes and maintenance methods are analyzed. Based on these results, a future pavement maintenance method is suggested. RESULTS AND CONCLUSIONS : Gyeonggi-do’s pothole situation is worse than Seoul’s. Problems were founded, as follows. The amount of potholes was large, and the number increased annually. Pothole management is done at a basic level, because there is no long-term plan. Potholes occur frequently at the same site because of the poor quality of emergency repair. Finally, there is no systematic and comprehensive pavement management. Thus, pothole prevention measures are ill-prepared. Therefore, to reduce potholes and to manage high quality pavement, it is necessary to make a long-term pavement management plan.

Three CNN (Convolutional Neural Network) models of GoogLeNet, VGGNet, and Alexnet were evaluated to select the best deep learning based image analysis mothod that can detect pavement distresses of pothole, spalling, and punchout on expressway. Education data was obtained using pavement surface images of 11,056km length taken by Gopro camera equipped with an expressway patrol car. Also, deep learning framework of Caffe developed by Berkeley Vision and Learning Center was evaluated to use the three CNN models with other frameworks of Tensorflow developed by Google, and CNTK developed by Microsoft. After determing the optimal CNN model applicable for the distress detection, the analyzed images and corresponding GPS locations, distress sizes (greater than distress length of 150mm), required repair material quantities are trasmitted to local maintenance office using LTE wireless communication system through ICT center in Korea Expressway Corporation. It was found out that the GoogLeNet, AlexNet, and VGG-16 models coupled with the Caffe framework can detect pavement distresses by accuracy of 93%, 86%, and 72%, respectively. In addition to four distress image groups of cracking, spalling, pothole, and punchout, 22 different image groups of lane marking, grooving, patching area, joint, and so on were finally classified to improve the distress detection rate.

아스팔트 포장에 수분 (moisture)이 침투하게 되면 골재의 부착력 (adhesion)을 유지하는 아스팔트 피 막 (asphalt thin film)이 약화되어 골재에서 아스팔트가 벗겨지는 박리 (striping) 현상이 발생한다. 포 장표면에 박리가 발생하고 박리로 인하여 결합력이 약화된 부분에 자동차 윤하중 (wheel load)이 지속적 으로 작용하게 되면 포장에서 골재가 떨어져 나오면서 포트홀 (pothole)이 발생하게 된다. 포트홀을 보다 쉽고 간단하게 복구하고 양호한 품질을 확보하기 위한 다양한 방법이 개발되어 적용되 고 있다. 그 중 적외선 가열장치 (infrared gas heater)를 활용하여 파손 부를 복구하는 공법이 대두되어 외국에서는 상용되고 있다. 국내에는 최근에 도입되어 일부 지역에서 포트홀 복구에 적용되고 있다. 국내 의 적외선 히터를 이용한 포트홀 복구는 포트홀 발생부분 (1*1*0.05m)을 적외선 히터로 가열하고, 신규 재료를 추가하여 혼합한 후 다짐 작업 이후에 교통 개방하는 방법으로 비교적 간단하고, 1개소를 30분 이 내에 보수할 수 있는 공법이다. 또한 포트홀 발생부분보다 넓은 부분을 가열하여 보수하므로 파손부 경계 면에서 2차 파손을 예방하는 효과도 있다. Infrared gas heater를 이용한 포트홀 보수공법을 적용함에 있어 추가되는 신규혼합물의 아스팔트 등 급, 재생첨가제 사용량, 수정입도 등을 결정하여 보수혼합물의 성능을 회생시켜야 한다. 따라서 포트홀 보수에 추가되는 신규혼합물을 제조하기 위한 전단계로서 포트홀이 발생한 파손부분 혼합물 (Pothole RAP이라 명명)의 특성을 명확히 판단할 필요가 있다. 이에 본 연구에서는 pothole RAP을 샘플링하여 특 성을 분석하여 추가될 신규혼합물 등급을 결정하는 기초자료로 활용하고자 하였다. 포트홀이 발생한 파손부 시료와 파손부를 일정시간 가열한 후 채취한 시료, 보수혼합물 시료에 대하여 아스팔트 함량, 입도, 추출 회수, 회수 바인더의 점도, 강성지수, Pass/Fail 온도 등을 측정하여 다양한 상태의 바인더와 노화 상태를 비교 평가하였다. 그 결과 포트홀이 발생한 구간의 혼합물은 일반 아스팔트 혼합물 포설 직 후에 비하여 매우 심각한 노 화 상태를 나타냈고, 특정 구간의 경우 현장에서 10년 이상 공용된 일반 혼합물에 비하여 5배 이상 노화 가 진행된 것으로 나타났다. Pothole RAP과 신규혼합물을 혼합한 보수용 혼합물은 노화상태가 현저히 개선되었으나, 일반 혼합물 수준에는 미치지 못하여 재생첨가제를 사용해야 할 것으로 판단되었다.

PURPOSES : The objective of this study is to develop new pothole repair materials using polyurethane-modified asphalt binder, and to evaluate them relative to current pothole repair materials in order to improve the performance of repaired asphalt pavement. METHODS : In the laboratory, polyurethane-modified asphalt binder is developed, and then asphalt binder is added to produce pothole repair materials. In order to evaluate the properties of this new pothole repair material, both an indirect tension strength test and a direct tension strength test are performed to measure the material strength and bond strength, respectively. Additionally, the basic material properties are evaluated using the asphalt cold mix manual. The strength characteristics based on curing times are evaluated using a total of 7 types of materials (3 types of current materials, 2 types of new materials, and 2 types of moisture conditioned new materials). The indirect tension strength tests are conducted at 1, 2, 4, 8, 16, and 32 days of curing time. The bond strength between current HMA(Hot Mix Asphalt) and the new materials is evaluated by the direct tension strength test. RESULTS AND CONCLUSIONS : Overall, the new materials show better properties than current materials. Based on the test results, the new materials demonstrate less susceptibility to moisture, faster curing times, and an improved bond strength between HMA and the new materials. Therefore, the use of the new materials reported in this study may lead to enhanced performance of repairs made to asphalt pavement potholes.

PURPOSES: The purpose of this study was to break away from the workforce method using cold-mix asphalt mixtures and has a constant quality and has develop repair materials of pre-production asphalt-precast types. METHODS: The selection of the repair material was determined as the results obtained through physical properties of materials and the field applicability. In case of repair materials, values obtained through Marshall stability test & the dynamic stability test & retained stability test as well as the site conditions was considered. In case of adhesive, test results were obtained through examination of the bond strength(tensile, shear) and the field applicability of the adhesive was examined through combined specimens to simulate field applications. RESULTS : According to the results of laboratory tests, in the case of repair materials, Marshall stability and dynamic stability, retained stability of cold-mix reaction type asphalt mixture is the highest. In the case of adhesive, two-component epoxy-urea has a very high bonding strength(tensile, shear) was most excellent. According to the results of field tests, when epoxy-urea was excellent workability. Also, the repair body through actual mock-up test did not occur large deformation and fracture after 12 months. CONCLUSIONS : A suitable repair material is cold-mix reaction type mixture of asphalt-precast, a suitable adhesive is a two-component epoxy-urea.

Purpose of this study is investigates mechanical property of Chemically Bonded Phosphate Ceramic(CBPC). For the purpose of the investigation of mechanical property, compressive stress and length change ratio were evaluated. Evaluated results of compressive stress was shown that compressive stress increased depending on aging time. On the other hand, length change ratio decrease depending on aging time.

아스팔트 콘크리트 포장 파손 중 40cm-50cm 지름과 5cm-10cm 깊이를 갖는 움푹 파이는 형태의 포장 파손을 포트홀(pothole)이라고 한다. 포트홀 파손 발생 메커니즘은 아스팔트 혼합물에 수분이 침투하고, 아스팔트 바인더와 골재의 점착력이 침투한 수분에 의하여 약화되어 발생한다. 따라서 아스팔트 콘크리트 포장의 포트홀은 주로 장마 기간에 많이 발생하지만 최근 들어 지구 온난화의 영향으로 겨울철 강우 또는 강설의 증가와 제설제의 영향으로 겨울과 봄에도 많이 발생하고 있다. 본 연구에서는 아스팔트 콘크리트 포장에 발생한 포트홀 파손을 효율적으로 상온에서 보수할 수 있는 보수 재료에 대하여 25℃에서 간접인장강도시험을 수행하고, 5회 동결융해 반복 후 간접인장강도시험을 수행하여 인장강도비(TSR, Tensile Strength Ratio)를 산정하였다. 이때 사용된 우레탄 개질 아스팔트 포트홀 보수재는 목표 공극률 4%대의 혼합물을 사용하였으며, 비교대상 상온 보수재는 사전 혼합된 형태로 사용되고 있는 기성 제품 2종류를 선정하였다. 각각의 포트홀 보수재는 양면 50회 다짐을 수행하여 공시체를 제작하였다. 동결융해 조건은 KS F 2398에 따라서 영하 18℃에서 16시간 방치한 후 60℃ 항온수조에서 24시간 담그는 것을 동결융해 1회로 보고 5회 반복한 후 간접인장강도시험을 수행하였다. 5회 동결융해 반복시험 후 인장강도비가 우레탄 개질 아스팔트 포트홀 보수재의 경우 35%이며, 비교 대상 상온 포트홀 보수재는 각각 67%와 66%로 나타났다. 우레탄 개질 아스팔트 보수재의 인장강도비가 다른 두 혼합물보다 50%정도 인장강도비가 작은 것으로 나타났지만 5회 동결융해 반복 시험 후 25℃의 인장강도값의 경우 비교 대상인 상온포트홀 보수재가 개발중인 상온 포트홀 보수재보다 각각 36%와 12%로 매우 작은 것으로 나타났다.

In recent years, many potholes in asphalt pavement occurred. In order to facilitate the repair, in this study, repair materials with high durability and excellent productivity appropriate for asphalt pre-cast materials was developed. Physical properties test and durability test of various repair materials(SMA, PMA, guss mixtures, water-reactive mixtures) were performed. In order to evaluate the workability at pre-production time of samples using repair materials were made in different shapes and sizes. Finally, after comparing mixtures, water-reactive mixture was selected as repair material. This was verified through several testing.

Asphalt overlay on top of concrete pavement is commonly used in Korea. But water and deicing chemical can penetrate asphalt layer and stay at the boundary of asphalt and concrete layer, which cause accelerated degradation of concrete. Theoretically asphalt mixture is impermeable, but water can penetrate where improper compaction applied area or boundary area. Accordingly, optimum asphalt contents in existing mix design were modified in order to increase impermeability and test road was constructed with the modified method. The testing field site was monitored for 17 months and the performance of the test road was similar to the road used conventional mix design, although modified mix design used for the test road has 30% less air void. Thus, reduced pavement deterioration is expected on the concrete pavement rehabilitation with asphalt overlay