The purpose of this study was to enhance the correlation between the dependent and independent variables in a prediction model of pavement performance for local roads on Jeju Island by applying K-means clustering for data preprocessing, thereby improving the accuracy of the prediction model. Pavement management system (PMS) data from Jeju Island were utilized. K-means clustering was applied, with the optimal K value determined using the elbow method and silhouette score. The Haversine formula was used to calculate the distances between the analysis sections and weather stations, and Delaunay triangulation and inverse distance weighting (IDW) were employed to interpolate the magnitude of the influencing factors. The preprocessed data were then analyzed for correlations between the rutting depth (RD) and influencing factors, and a prediction model was developed through multiple linear regression analysis. The RD prediction model demonstrated the highest performance with an R² of 0.32 and root-mean-square error (RMSE) of 1.48. This indicates that preprocessing based on the RD is more effective for developing an RD prediction model. The study also observed that the lack of pavement-age data in the analysis was a limiting factor for the prediction accuracy. The application of K-means clustering for data preprocessing effectively improved the correlation between the dependent and independent variables, particularly in the RD prediction model. Future research is expected to further enhance the prediction accuracy by including pavement-age data.

This paper explores a convergent approach that combines advanced informatics and computational science to develop road-paving materials. It also analyzes research trends that apply artificial-intelligence technologies to propose research directions for developing new materials and optimizing them for road pavements. This paper reviews various research trends in material design and development, including studies on materials and substances, quantitative structure–activity/property relationship (QSAR/QSPR) research, molecular data, and descriptors, and their applications in the fields of biomedicine, composite materials, and road-construction materials. Data representation is crucial for applying deep learning to construction-material data. Moreover, selecting significant variables for training is important, and the importance of these variables can be evaluated using Pearson’s correlation coefficients or ensemble techniques. In selecting training data and applying appropriate prediction models, the author intends to conduct future research on property prediction and apply string-based representations and generative adversarial networks (GANs). The convergence of artificial intelligence and computational science has enabled transformative changes in the field of material development, contributing significantly to enhancing the performance of road-paving materials. The future impacts of discovering new materials and optimizing research outcomes are highly anticipated.

PURPOSES : This study evaluates the noise reduction effects of various road paving methods and focuses on low-noise pavements as a cost-effective alternative to sound barriers and tunnels. In addition, this study assesses how noise levels vary with vehicle speed across different paving methods. METHODS : An analysis of variance (ANOVA) was conducted to evaluate the noise performance of different paving methods, and this followed by a post-hoc analysis to examine the differences among the paving methods. Another ANOVA was conducted to evaluate the impact of speed on noise performance. This ANOVA was followed by a post hoc analysis to assess differences by speed. Finally, a covariance analysis was conducted, using speed as a covariate, to evaluate the noise reduction effects of the various paving methods. RESULTS : The results of the analyses showed that noise levels follow the order of General ≈ Non-draining > Single-layer ≈ Doublelayer, thus grouping the paving methods into two categories with significant differences in noise performance. In addition, the noise levels increased with speed, except at 70 and 80 km/h. The covariance analysis resulted in a regression coefficient of 0.267 for speed across all paving methods. A post-hoc analysis grouped the paving methods into three distinct categories: General, Non-draining ≈ Single-layer ≈ Double-layer, with notable noise differences between them. CONCLUSIONS : The analysis of noise performance showed that both the paving method and speed significantly affected the noise levels. The covariance analysis, using speed as a covariate, revealed a consistent regression coefficient of 0.267 across all the paving methods. After controlling for speed, noise differences were observed. The General method showed higher noise levels than did the Non-draining, Doublelayer, and Single-layer methods.

콘크리트 도로포장의 손상은 차량의 이동에 의한 진동, 겨울철 제설제 사용, 동결융해 작용 등이 주요 손상원인으로 나타나고 있다. 이러한 손상을 해결하기 위하여 열화 원인에 능동적으로 대응하는 보수재료 및 방법이 적용되어야 하나, 일반적으로 단면복구, 부분보 수를 반복적으로 사용함으로써, 지속적인 열화 현상의 발생으로 도로포장의 기능을 상실하게 된다. 또한, 기존에 사용되고 있는 보수 재료 중 무기계 보수재료는 폴리머 모르타르, 에폭시수지 모르타르 등이 있다. 이러한 재료는 높은 압축강도를 가지고 있으나, 취성 및 부착력이 약한 단점을 나타내고 있다. 따라서 본 연구에서는 보통포틀랜드시멘트(Ordinary Portland Cement), 칼슘알루미네이트계 재 료인 칼슘설포알루미네이트(Calcium Sulfo Aluminate) 및 비정질 알루미네이트(Amorphous Calcium Aluminate)를 사용한 보수 모르타르의 압축강도 및 내동해성을 평가하였다. 보수 모르타르의 압축강도를 분석한 결과, 비정질 알루미네이트를 사용한 보수모르타르의 압축강 도가 보통포틀랜드시멘트 및 칼슘설포알루미네이트를 사용한 보수 모르타르보다 우수하게 나타나는 것을 확인하였다. 한편, 보수 모르 타르의 내동해성 평가는 ASTM C 666 A법에 준하여 실험을 진행하였다. 그 결과, 칼슘설포알루미네이트 및 비정질 알루미네이트를 적용한 보수 모르타르의 상대동탄성계수가 300사이클에서 약 90%이상으로 나타나 보통포틀랜드시멘트를 사용한 보수 모르타르보다 우수한 내동해성을 나타내었다. 따라서, 칼슘설포알루미네이트 및 비정질 알루미네이트를 적용한 보수 모르타르는 우수한 압축강도 및 내동해성을 나타냄으로써 도로포장의 보수재료로 사용이 가능할 것으로 판단된다.

단지 내 도로는 별도의 설계법 없이 AASHTO 및 TA 설계법, 한국형 도로포장 설계법을 적용하여 일률적인 포장 두께를 적용하고 있으나 비산먼지 방지 목적으로 중간층 또는 기층 포설 후, 공사차량을 사전개방하고 사업 준공 단계에서 표층을 시공하는 단계시공 을 실시하고 있다. 이에 의해 포장단면 두께는 공사차량의 영향으로 공용수명을 만족하지 못하게 되므로 포장 파손이 빈번하게 발생 하므로 이를 고려한 포장 설계법 정립이 필요하다. 따라서 공사차량 통행을 고려한 단지 내 도로포장 설계기준을 적용한 시험시공 구 간을 대상으로 현장 모니터링 조사를 수행하였으며, 구조해석 프로그램을 활용하여 단면두께에 대한 포장 공용수명을 산출함으로써 적정성을 검토하였다. 현장조사 결과, 표층 시공 후, 공사차량 교통량을 개방한 구간에서는 공용기간 48개월일 때 표면 균열율이 1% 미만으로 조사되었으며, 중간층만 포설된 단면에서 공사차량 하중이 재하되고, 표층을 포설한 구간의 균열율은 약 8%로 상대적으로 높게 나타났다. 일반적으로 균열율이 8% 초과할 경우, 노후화된 포장층으로 판단하여 유지보수를 실시(서울시, 2018)하므로 조기파손 이 발생한 것으로 제시할 수 있다. 또한, 기존 설계기준을 적용한 구간의 표면상태 조사결과와 KENPAVE를 활용한 Damage 산출 결과 가 유사한 추세로 나타났으며, 6,170 세대 이상의 공사차량이 통행할 경우 공용년수를 만족하지 못하였으므로 해당 세대수에 대해서는 상향 설계를 실시해야 한다. 유지보수 기준에 따라 5∼7년 동안 공용된 포장에서 나타나는 균열율을 기준으로 KENPAVE Damage 10%, KPRP 피로균열 6% 이하이면 10년 이상의 공용이 가능한 것으로 도출되었다. 그러나 절삭 후 덧씌우기를 진행하지 않은 포장 단면에서는 상대적으로 높은 표면 균열율이 발생하므로, 잔존수명 예측을 통해 적절한 절삭 깊이를 산출하여 목표 설계수명을 만족할 수 있는 단지 내 도로포장 설계단면의 적정 기준을 제시함으로써 공용수명을 향상시킬 수 있을 것으로 기대한다.

PURPOSES : As evaluation methods for road paving materials become increasingly complex, there is a need for a method that combines computational science and informatics for new material development. This study aimed to develop a rational methodology for applying molecular dynamics and AI-based material development techniques to the development of additives for asphalt mixtures. METHODS : This study reviewed relevant literature to analyze various molecular models, evaluation methods, and metrics for asphalt binders. It examined the molecular structures and conditions required for calculations using molecular dynamics and evaluated methods for assessing the interactions between additives and asphalt binders, as well as properties such as the density, viscosity, and glass transition temperature. Key evaluation indicators included the concept and application of interaction energy, work of adhesion, cohesive energy density, solubility parameters, radial distribution function, energy barriers, elastic modulus, viscosity, and stress-strain curves. RESULTS : The study identified key factors and conditions for effectively evaluating the physical properties of asphalt binders and additives. It proposed selective application methods and ranges for the layer structure, temperature conditions, and evaluation metrics, considering the actual conditions in which asphalt binders were used. Additional elements and conditions considered in the literature may be further explored, considering the computational demands. CONCLUSIONS : This study devised a methodology for evaluating the physical properties of asphalt binders considering temperature and aging. It reviewed and selected useful indicators for assessing the interaction between asphalt binders, additives, and modified asphalt binders and aggregates under various environmental conditions. By applying the proposed methods and linking the results with informatics, the interaction between asphalt binders and additives could be efficiently evaluated, serving as a reliable method for new material development.

최근 국내 겨울철 블랙아이스(Black Ice)로 인해 발생하는 교통사고가 증가하는 추세이며, 한국 도로교통공단 조사 결 과 2016～2020년 겨울철까지 블랙아이스로 인한 사고는 총 4,868건이며, 사상자는 8,938명인 것으로 조사 되었다. 도로상 태에 따라 건조대비 동결상태에서 교통사고 발생시 치사율이 43%로 높게 나타났다. 이러한 사고는 기온이 떨어지는 12 월부터 급증하여, 최저기온이 가장낮은 1월까지 증가한다. 블랙아이스는 도로에 쌓인 눈이 융해(해설)과 동시에 도로 위 각종 이물질과 결합 후 재동결하여 흑색 동결막을 형성하는 것을 말한다. 그 특성상 운전자가 차량내부에서 도로의 상태 를 쉽게 파악할 수 없으며 대부분의 운전자가 차량이 미끄러지기 시작함과 동시에 인지하여 사고가 발생하게 된다. 이에 본 연구에서는 기존 포장체의 미끄럼 저항도를 상태별로 비교 분석하였다. 포장체의 미끄럼 저항성 정도를 파악하기 위 해 영국식 미끄럼저항 시험기 (British Pendulum Tester ; BPT)를 사용하였으며, 포장체의 종류로는 일반적인 밀입도 아스팔트 포장, 배수성 아스팔트 포장, 그루빙(포장 표면에 일정한 규격의 홈을 형성)을 적용한 콘크리트 포장, 그루빙이 없는 콘크리트 포장을 적용하였다. 미끄럼저항 실험은 관련 KS규격 및 ASTM규격에 준하여 실시하되 블랙아이스를 모 사하기위하여 표면온도 영하 2～3℃ 샘플에 강우를 모사한 물을 분사하며 영하 9℃로 10분 동결 후 2mm강수량을 모사 한 수분을 재 분사한 후 시험을 실시하였다.

PURPOSES : Derive a road pavement design method using Geocells, aim to derive a road pavement design and construction method suitable for the characteristics of the Bangladesh region METHODS : To assess long-term performance during road construction in Southeast Asia using Geocells, field tests and numerical analysis are conducted to verify stability. RESULTS : A total of 12 displacement measurements were conducted during the field tests, confirming an average load of 15.75 kN and an average displacement of 0.542mm. Inverse analysis was performed to obtain the properties of Geocell combined with compacted soil. The numerical analysis results confirmed that the insertion of Geocell provides better stability compared to the case with only compacted soil. CONCLUSIONS : Based on field tests and numerical analysis, a road design plan suitable for the Southeast Asian environment was proposed. A preliminary test section was selected in the Comilla region of Bangladesh, and test construction has been completed. Subsequent evaluations of the structural performance by soil layer in the test construction area will be conducted to develop a Geocell road pavement method, taking into consideration the characteristics of the Bangladesh region.

PURPOSES : This study intended to derive a methodology that can evaluate water splash caused by distress on the road surface based on experimental methods and to present quantitatively by analyzing the impact on road users. METHODS : Through literature review, the current problems of road pavement and drainage facility standards, the factors of road splash caused by puddle was selected to measure damage. Field measurements were conducted by setting different conditions for each factors and setting different conditions based on the hypothesis. In addition, water splash by surface distress type and puddle was measured to analyze using statistical techniques from correlation to multi-regression. RESULTS : The maximum and effective distance due to road splash increases as the driving speed, regardless of vehicle load and tyre type. Splash was measured according to the type of road distress to analyze the correlation between the influencing factors, and there was a weak correlation between the width and length of the puddle, depth and the effective distance. In addition, the interaction analysis showed that there was an interaction between the width of the water hole and the depth of puddle. Moreover, based on the multi-regression analysis, it was not statistical significant. This is judged to that the number of data samples used for this analysis is limited because the diversity of puddle conditions cannot be set differently for each type of distress. CONCLUSIONS : Since the distress of depending on the size, depth and shape of the road surface, it is necessary to calculate it and present maintenance standards, so this results present an experimental methodology that can intuitively evaluate damage cased by unestablished puddle. From this results, this is expected to be used as a quantitative indicator to evaluate the satisfaction of road users as a functional performance according to road surface condition.

PURPOSES : Fine dust significantly affects the atmospheric environment, and various measures have been implement to reduce it. The aim of this study is to reduce fine dust on roads by implementing porous pavements and a clean road system using the low-impact development technique. METHODS : We conducted quality tests (draindown, cantabro loss rate, tensile strength ratio, dynamic stability, and indoor permeability coefficient tests) and performance evaluation (dynamic modulus and Hamburg wheel-tracking tests) on the porous asphalt mixture. Subsequently, we constructed a porous pavement road in a test bed and conducted a permeability test. In the test bed, we installed a nozzle, a water tank, and a fluid pump to water the roadside. After the clean road system was completely installed, we measured the concentration of fine dust before and after water was sprayed. Additionally, we conducted a total suspended solids (TSS) test to confirm the reduction in re-suspended dust. RESULTS : All results from the quality test of the porous asphalt mixture satisfy the standards stipulated by the Ministry of Land, Infrastructure and Transport. Results from the dynamic modulus test show a low plastic deformation resistance but a high fatigue crack resistance. The results from the Hamburg wheel-tracking test satisfy the U.S. Department of Transportation standards. After the porous pavement was constructed, a permeability test was conducted, and the result satisfies the standard value. Using a particle counter, we measured the concentration of fine dust before and after water spraying, and results show 12.08% and 10.23% for PM10 and PM2.5 particles, respectively. The results from the TSS test show that after the initial water spray, almost all re-suspended dust are removed from a road. In unfavorable road conditions, almost all re-suspended dust are removed after a second water spray. CONCLUSIONS : The results of all of quality tests performed on a porous asphalt mixture satisfy the standards. By applying the results to a test bed, the problem of securing water is solved. Using the clean road system, 12.08% and 10.23% of PM10 and PM2.5 particles are removed, respectively. The system removes PM10 particles (larger particles) more effectively compared with PM2.5 particles. IN the future, we plan to revise the maintenance plan such that the porous pavement can exhibit long-term performance. Because pipe freezing may occur in the winter, we plan to analyze the periodic maintenance plan of the porous pavement and develop a solution to mitigate the issue of freezing pipes in the winter.

PURPOSES : In this study, surface distress (SD), rutting depth (RD), and international roughness index (IRI) prediction models are developed based on the zones of Incheon and road classes using regression analysis. Regression analysis is conducted based on a correlation analysis between the pavement performance and influencing factors. METHODS : First, Incheon was categorized by zone such as industrial, port, and residential areas, and the roads were categorized into major and sub-major roads. A weather station triangle network for Incheon was developed using the Delaunay triangulation based on the position of the weather station to match the road sections in Incheon and environmental factors. The influencing factors of the road sections were matched Based on the developed triangular network. Meanwhile, based on the matched influencing factors, a model of the current performance of the road pavement in Incheon was developed by performing multiple regression analysis. Sensitivity analysis was conducted using the developed model to determine the influencing factor that affected each performance factor the most significantly. RESULTS : For the SD model, frost days, daily temperature range, rainy days, tropical nights, and minimum temperatures are used as independent variables. Meanwhile, the truck ratio, freeze–thaw days, precipitation days, annual temperature range, and average temperatures are used for the RD model. For the IRI model, the maximum temperature, freeze–thaw days, average temperature, annual precipitation, and wet days are used. Results from the sensitivity analysis show that frost days for the SD model, precipitation days and freeze–thaw days for the RD model, and wet days for the IRI model impose the most significant effects. CONCLUSIONS : We developed a road pavement performance prediction model using multiple regression analysis based on zones in Incheon and road classes. The developed model allows the influencing factors and circumstances to be predicted, thus facilitating road management.