This paper presents a finite-difference method (FDM)-based heat-transfer model for predicting black-ice formation on asphalt pavements and establishes decision criteria using only meteorological data. Black ice is a major cause of winter road accidents and forms under specific surface temperature and moisture conditions; however, its accurate prediction remains challenging owing to dynamic environmental interactions. The FDM incorporates thermodynamic properties, initial pavement-temperature profiles, and surface heat-transfer mechanisms, i.e., radiation, convection, and conduction. Sensitivity analysis shows the necessity of a 28-d stabilization period for reliable winter predictions. Black-ice prediction logic evaluates the surface conditions, relative humidity, wind speed, and latent-heat accumulation to assess phase changes. Field data from Nonsancheon Bridge were used for validation, where a maximum prediction accuracy of 64% is indicated in specific cases despite the overestimation of surface temperatures compared with sensor measurements. These findings highlight the challenges posed by wet surface conditions and prolonged latent-heat retention, which extend the predicted freezing duration. This study provides a theoretically grounded methodology for predicting black ice on various road structures without necessitating additional measurements. Future studies shall focus on enhancing the model by integrating vehicle-induced heat effects, solar radiation, and improved weather-prediction data while comparing the FDM with machine-learning approaches for performance optimization. The results of this study offer a foundation for developing efficient road-safety measures during winter.

This study aimed to develop a pavement management system suitable for the climate and traffic characteristics of Gangwon Province. This research focused on analyzing the asphalt pavement performance characteristics of national highways in Gangwon Province by region and developing prediction models for the current pavement performance and annual changes in performance. Quantitative indicators were collected to evaluate the condition of national highway pavements in Gangwon Province, including factors affecting road performance, such as weather data and traffic volume. The Gangwon region was then classified according to its topography, climate, weather, traffic volume, and pavement performance. Prediction models for the current pavement performance and annual changes in performance were developed for national highways. This study also compared the predicted values for the Gangwon region using a nationwide pavement performance-prediction model from other studies with the predicted values from the developed annual changes in the performance prediction model. This study established a foundation for implementing a pavement management system tailored to the unique climate and traffic characteristics of Gangwon Province. By developing region-specific performance prediction models, this study provided valuable insights into more effective and efficient pavement maintenance strategies in Gangwon Province.

The purpose of this study was to optimize the design of asphalt concrete pavements for Jeju Island by considering the regional characteristics of the island. This study employed an MEPDG program to determine the allowable traffic loads for class 4 vehicles by considering the axle loads, climate, and material properties. Samples of basalt asphalt concrete from Jeju were used to measure the dynamic modulus for material property estimation. The climate input was based on 30-year climate data from Jeju. The thicknesses and moduli of the subgrade, subbase, and asphalt layers were incorporated into the design. The regression-analysis program SPSS was used to develop a regression equation for the overlay design, factoring in the modulus and thickness ratios between the existing and overlay asphalt layers. A pavement-thickness design formula tailored to Jeju's characteristics was derived. An equivalent single-axle load factor (ESALF) formula was developed to facilitate traffic-load estimation for different roads, enabling the easy incorporation of varying traffic volumes into the design. The ESALF formula demonstrated a high correlation with the pavement thickness, subgrade conditions, and axle loads, whereas the pavementthickness design formula exhibited strong correlations with the pavement thickness, subgrade state, thickness ratios, and modulus ratios. The use of basalt aggregates in asphalt concrete pavements provides an economically viable and technically sound solution for Jeju. The proposed design methodology not only reduces costs but also enhances pavement performance and road safety. The developed formulas offer flexibility in adjusting designs based on specific traffic conditions, providing optimal pavement solutions for different road categories.

This study aimed to evaluate the performance criteria of low-noise asphalt pavements under laboratory conditions. Laboratory tests were performed on eight porous and three non-porous asphalt mixtures. Draindown, Cantabro, tensile strength ratio (TSR), and dynamic stability tests were conducted to evaluate durability. The functionality was assessed using sound-absorption and indoorpermeability- coefficient tests. The laboratory results showed that all mixtures satisfied the quality standards for the draindown and TSR tests. In the dynamic stability test, all the mixtures demonstrated adequate rutting resistance. For porous mixtures, the Cantabro test results indicated sufficient shatter resistance and the indoor-permeability-coefficient test confirmed proper drainage performance. All mixtures exhibited satisfactory sound absorption, with the porous mixtures exhibiting slightly better sound absorption than the non-porous mixtures. Both porous and non-porous mixtures are durable and functional and are used in Korea. Future field tests are required to evaluate the noise reduction performance under different conditions and to compare the in-situ performance results with those from laboratory tests.

PURPOSES : For most local governments, including that of Gangwon-do, the establishment of an organized pavement management system is insufficient, resulting in problems such as inefficient distribution and use of maintenance budgets for deteriorated road pavements. In this study, we aimed to contribute to the establishment of a more reasonable road maintenance strategy by developing a model for predicting the annual international roughness index (IRI) change for national highway asphalt pavements in Gangwon-do based on big data analysis. METHODS : Data on independent and dependent variables used for model development were collected. The collected data were subjected to exploratory data analysis (EDA) and data preprocessing. Independent variable candidates were selected to reduce multicollinearity through correlation analysis and specific conditions. A final model was selected, and sensitivity analysis was performed. RESULTS : The final model that predicts annual IRI change uses independent variables such as annual temperature range, minimum temperature, freeze-thaw days, IRI, surface distress (SD), and freezing days. The sensitivity analysis confirmed that the annual IRI change was affected in the order of annual temperature range, minimum temperature, freeze-thaw days, IRI, SD, and freezing days. CONCLUSIONS : Road maintenance can be performed rationally by predicting future pavement conditions using the model developed in this study. The accuracy of the prediction model can be improved if additional data, such as material properties and pavement thickness, are obtained in future studies.

PURPOSES : To efficiently manage pavements, a systematic pavement management system must be established based on regional characteristics. Suppose that the future conditions of a pavement section can be predicted based on data obtained at present. In this case, a more reasonable road maintenance strategy should be established. Hence, a prediction model of the annual surface distress (SD) change for national highway pavements in Gangwon-do, Korea is developed based on influencing factors. METHODS : To develop the model, pavement performance data and influencing factors were obtained. Exploratory data analysis was performed to analyze the data acquired, and the results show that the data were preprocessed. The variables used for model development were selected via correlation analysis, where variables such as surface distress, international roughness index, daily temperature range, and heat wave days were used. Best subset regression was performed, where the candidate model was selected from all possible subsets based on certain criteria. The final model was selected based on an algorithm developed for rational model selection. The sensitivity of the annual SD change was analyzed based on the variables of the final model. RESULTS : The result of the sensitivity analysis shows that the annual SD change is affected by the variables in the following order: surface distress ˃ heat wave days ˃ daily temperature range ˃ international roughness index. CONCLUSIONS : An annual SD change prediction model is developed by considering the present performance, traffic volume, and climatic conditions. The model can facilitate the establishment of a reasonable road maintenance strategy. The prediction accuracy can be improved by obtaining additional data, such as the construction quality, material properties, and pavement thickness.

PURPOSES : The surface distress of asphalt pavements is one of the major factors affecting the safety of road users. The aim of this study was to analyze the factors influencing the occurrence of surface distress and statistically predict its annual change to contribute to more reasonable asphalt pavement management using the data periodically collected by the national highway pavement data management system. METHODS : In this study, the factors that were expected to influence the surface distress were determined by reviewing the literature. The normality was secured by changing the forms of the variables to make the distribution of the variables got closer to normal distribution. In addition, min-max normalization was performed to minimize the effect of the unit and magnitude of the candidate independent variables on the dependent variable. The final candidate independent variables were determined by analyzing the correlation between the annual surface distress change and each candidate independent variable. In addition, a prediction model was developed by performing data grouping and multi-regression analysis. RESULTS : An annual surface distress change prediction model was developed using present surface distress, age, and below 0 ℃ days as the independent variables. As a result of sensitivity analysis, the surface distress affected the annual surface distress change the most. The positive correlation between the dependent variable and each independent variable demonstrated engineering and statistical meaningfulness of the prediction model. CONCLUSIONS : The surface distress in the future can be predicted by applying the annual surface distress prediction model to the national highway asphalt pavement sections with survey data. In addition, the prediction model can be applied to the national highway pavement condition index (NHPCI) evaluating the national highway asphalt pavement conditions to be used in the prediction of future NHPCI.

PURPOSES : The purpose of this study is to identify a gradation control method that minimizes the volatility of recycled aggregates to maintain the quality of reclaimed asphalt mixtures. METHODS : In this study, two types (0~13 and 0~10 mm) of recycled aggregate stockpiles with an extraction viscosity of 40,000 poise and a 19 mm hot asphalt mixture with virgin aggregates are used. The test methods are evaluated for plastic deformation resistance using the Hamburg wheel-tracking test and for low-temperature crack resistance using the dynamic modulus test. In the field, the performance is evaluated via an accelerated pavement test. RESULTS : The Hamburg wheel-tracking test shows good water resistance as well as less than 5 mm of deformation. The result of a dynamic modulus test at -5 °C shows a 92.9% low-temperature crack resistance as compared with that of the 19 mm dense grade hot-mix asphalt mixture. The result of the accelerated pavement test confirms that the performances of the 19 mm dense grade hot-mix asphalt mixture and reclaimed asphalt mixture are equal owing a 1.2 cm plastic deformation. CONCLUSIONS : By evaluating the plastic deformation resistance and crack resistance of the reclaimed asphalt mixture based on a stockpile gradation controlled at 0~10 mm via an indoor test, it is discovered that the plastic deformation resistance increases partially, whereas the crack resistance remains almost unchanged. The accelerated pavement test confirms that a performance equivalent to that of a 19 mm dense grade hot-mix asphalt mixture is achieved.

PURPOSES : Rut depth of asphalt pavements is a major factor that affects the maintenance of pavements as well as the safety of drivers. The purpose of this study was to analyze the factors influencing rut depth, using data collected periodically on national highways by the pavement management system and, consequently, predict annual rut depth change, to contribute to improved asphalt pavement management. METHODS : The factors expected to influence rut depth were determined by reviewing relevant literature, and collecting the related data. Further, the correlations between the annual rut depth change and the influencing factors were analyzed. Subsequently, the annual rut depth change model was developed by performing regression analysis using age, present rut depth, and annual average maximum temperature as independent variables. RESULTS : From the sensitivity analysis of the developed model, it was found that age affected the annual rut depth change the most. Additionally, the relationship between the dependent and independent variables was statistically significant. The model developed in this study could reasonably predict the change in the rut depth of the national highway asphalt pavements. CONCLUSIONS : In summary, it was verified that the model developed in this study could be used to predict the change in the National Highway Pavement Condition Index (NHPCI), which represents comprehensive conditions of national highway pavements. Development of other models that predict changes in surface distress as well as international roughness index is required to predict the change in NHPCI, as they are the independent variables of the NHPCI prediction model.

PURPOSES : The type and degree of structural conditions and influencing factors distributed across representative sections should be similar to those distributed across entire sections as the representative sections have been predominantly used for developing performance prediction models, which substitute entire sections of road pavement. Therefore, a logic that selects the representative sections with similar distributions of structural conditions and the influencing factors with those of entire expressway asphalt pavement sections requires development. METHODS : The logic developed in this study to select the representative sections of asphalt pavements comprised three steps. First, the data on the structural conditions of the pavement and the influencing climate conditions and pavement materials were collected and organized. Consequently, in the second step, the candidate sections were selected, with the severity of the structural conditions of the pavement distributed widely and evenly. Finally, in addition to the widely and evenly distributed pavement conditions, the representative sections with climatic conditions and pavement materials were selected. RESULTS : A total of 6,352 ordinary asphalt pavement sections and 596 composite asphalt pavement sections were selected as entire expressway asphalt pavement sections and the data were collected and organized according to the logic developed in this study. Three times the representation sections were selected as candidate sections and, finally, 85 sections were selected as representative sections. The distribution of structural conditions and influencing climate conditions and pavement materials in the representative sections were similar to those in the entire sections. In addition, the representative sections were spread evenly across the country. CONCLUSIONS : The sections presenting similar distributions of structural conditions and the influencing factors of entire expressway asphalt pavement sections could be selected in this study. Using the representative sections selected in this study, a remodeling index model will be developed for predicting the asphalt pavement sections that require large-scale repair.

PURPOSES : The adhesive bonding strength of the grid between asphalt pavements is critical in pavement performance. The study is to compare and evaluate the interlayered bonding strength of asphalt mixture specimens with fiber-glass grid (FG) reinforcement and different tack coating materials based on the test results of the shear bonding test. METHODS : Asphalt mixtures were molded with FG reinforcement using various tack coating materials namely RSC4 and D/B coat. The adhesive shear-bond strength was measured by inducing a monotonic shear loadnig rate of 5 mm/min at 20℃. RESULTS : As expected, the asphalt mixture with non-reinforced FG exhibited the highest adhesive shear-bond strength, followed by that of the FG with D/B coating. The ranking order of superiority is as follows: Control (RSC4) > D/B+FG > RSC4+FG. CONCLUSIONS : The results of this experimental study indicate that FG with RSC4 and D/B tack coats can be successfully used in asphalt concrete overlay construction with superior field performance. Based on the test results and literature review, the field bonding strength should exceed 300kPa in grid reinforced asphalt pavement.

PURPOSES: This study determines the life of asphalt overlay over old concrete pavements for various times of overlay, using the actual 30- year performance history of the Jungbu Expressway. The results from this study can be used as the basis for decisions on the proper time for overlay, and can also provide information for life cycle cost analysis. METHODS : The maintenance history of the Jungbu Expressway and traffic database 30 years after construction were analyzed. The durations between the first overlay and subsequent overlay for each section of the pavement were analyzed for the entire Jungbu Expressway. The durations were analyzed in terms of both years and the ESAL traffic volumes. RESULTS : 1. The life of the asphalt overlay over the old concrete pavements depended on the time of overlay in terms of both age and cumulative ESALs. A strong correlation was observed between the overlay life and the cumulative ESALs at the time of overlay. 2. The life of the second overlay at the same section was significantly shorter than the first overlay. For JCP, the average lives of the first and second overlays were 6.1 and 2.4 years, respectively. For CRCP, they were 4.8 and 2.7 years, respectively. The main reason for the shorter life of the overlay for CRCP may be that the overlay time was generally later than that for the JCP. 3. The life of the overlay was analyzed according to its materials. SMA exhibited the best performance, followed by CRM. CONCLUSIONS: Life of the overlay reduced with the time of overlay especially in terms of cumulative ESALs, and the life of the second overlay at the same section was significantly shorter than the first overlay. The results can be used in the decision making of the time of overlay and in the life cycle cost analysis.

PURPOSES : This study establishes a pay adjustment factor scheme that will penalize or provide incentives to contractors after pavement construction in Seoul City. METHODS: Random sampling was conducted, wherein acceptable quality characteristics (AQCs) of the field mixture such as the aggregate gradation, asphalt binder content, pavement thickness, field air void, and IRI (International Roughness Index) were determined. Using the acquired field data, the percent within limit (PWL) values of each AQC were determined. RESULTS : Weight factors were used to consider the effect of each AQC, since field data varies depending on the field condition. The total pay factor (PF) was determined by combining the PF material and PF construction. PF material considers the asphalt binder content and the aggregate gradation, while PF construction considers the field air void, pavement thickness, and field IRI. CONCLUSIONS: A pay adjustment factor was established by determining the PWL of each AQC and calculating the corresponding pay factor. Based on the results, it is found that PWL is a reasonable and acceptable method for evaluating the pavement quality and determining the pay factor.

PURPOSES : The purpose of this study is to analyze the magnitude of shoving of asphalt pavement by junction type between airport concrete and asphalt pavements, and to suggest a junction type to reduce shoving. METHODS : The actual pavement junction of a domestic airport, which is called airport “A”was modified by placing the bottom of the buried slab on the top surface of the subbase. A finite element model was developed that simulated three junction types: a standard section of junction proposed by the FAA (Federal Aviation Administration), an actual section of junction from airport “A”and a modified section of junction from airport“ A”. The vertical displacement of the asphalt surface caused by the horizontal displacement of the concrete pavement was investigated in the three types of junction. RESULTS: A vertical displacement of approximately 13 mm occurred for the FAA standard section under horizontal pushing of 100 mm, and a vertical displacement of approximately 55 mm occurred for the actual section of airport “A”under the same level of pushing. On the other hand, for the modified section from airport“ A”a vertical displacement of approximately 17 mm occurred under the same level of pushing, which is slightly larger than the vertical displacement of the FAA standard section. CONCLUSIONS: It was confirmed that shoving of the asphalt pavement at the junction could be reduced by placing the bottom of the buried slab on the top surface of the subbase. It was also determined that the junction type suggested in this study was more advantageous than the FAA standard section because it resists faulting by the buried slab that is connected to the concrete pavement. Faulting of the junctions caused by aircraft loading will be compared by performing finite element analysis in the following study.

PURPOSES : The purpose of this study is to analyze the performance life of hot central plant recycling (HCPR) and hot in-place recycling (HIR) pavements applied to the National Highway for the past 20 years and compare it with conventional hot-mix asphalt (HMA) pavement. METHODS: In order to analyze the performance life of recycling asphalt pavements, a comprehensive literature review was conducted to investigate the government law and official system for the use of recycling asphalt pavement in Korea and foreign countries. Next, the application information of using a hot central plant recycling and hot in-place recycling pavements in the national highway is collected from the database of pavement management system (PMS) and then their field condition is visually surveyed. Finally, the performance life of recycling asphalt pavements in the national highway is analyzed and compared with conventional hot-mix asphalt pavement. RESULTS: Institutions are encouraging the promotion of using recycled asphalt pavement through various legal systems in Korea as well as abroad. Based on analysis results for the average performance life of hot central plant recycling pavement applied to the national highway, the average performance life is estimated to be 10.2 years. However, the average performance life of in-place recycling pavement is estimated to be 6.5 years. However, it is expected to increase performance life after the HIR construction system is modified. CONCLUSIONS : Based on the limited data analysis of the performance life of recycled asphalt pavements, HCPR shows similar performance life to conventional asphalt pavement but HIR shows shorter performance life than conventional asphalt pavement. However, it is noted that all performance life data is very limited and it should be monitored and analyzed further.

PURPOSES:Pavement textures can be categorized into four according to wavelength: microtexture, macrotexture, megatexture (roads), and roughness. Pavement surface texture influences a number of aspects of tire-pavement interaction such as wet-weather friction, tire-pavement noise, splash, spray, tire-wear, and rolling resistance. In particular, macrotexture is the pavement surface characteristic that considerably impacts tire-pavement noise. In general, it can be demonstrated that tire-pavement noise increases with the increase of texture depth and wavelength. Recently, mean profile depth (MPD) and wavelength have been used to evaluate tire-pavement noise. This study aimed to identify the relationship between mean profile depth and average wavelength for asphalt pavement based on the information obtained on a number of asphalt pavement sections.METHODS :Profile data were collected from a number of expressway sections in Korea. In addition, mean profile depth and average wavelength were calculated by using this profile data. Statistical analysis was performed to determine the correlationship between mean profile depth and average wavelength.RESULTS:This study demonstrates a linear relationship between mean profile depth and average wavelength for asphalt concrete pavement.CONCLUSIONS:The strong relationship between mean profile depth and average wavelength of asphalt pavement was determined in this study.