PURPOSES : The purpose of this study was to improve the performance of concrete pavements by measuring the unit-water content with an Internet-of-Things (IoT)-based unit-water content measurement device at an increased precision compared with that of existing measuring equipment. METHODS : We calculated the properties of concrete that varied according to variations in the unit-water content. To confirm the change in the performance of concrete pavements, we compared and analyzed the fatigue cracking rate and international roughness index of concrete pavements at the 20-year point of public use according to the changes in properties using the Korea Pavement Research Program(KPRP). RESULTS : We confirmed that IoT-based measurement equipment can improve the performance of pavements without changing their mixing designs or specifications. We confirmed that the performance of the concrete pavements changed significantly, even with unit-water content variations within the range of quality standards. According to IoT-based unit-water content management, we confirmed that the performance of the concrete pavement (fatigue cracking rate and international roughness index) improved without changing the mixing design. CONCLUSIONS : We confirmed that by using IoT-based unit-water content management, pavement performance can be improved. It is necessary to consider whether the application of this concept to other concrete property management items, such as the chloride content, is possible. Considering the changes in concrete properties according to the unit-water content based on laboratory tests and considerations of various load conditions will be necessary for future research.

PURPOSES : This study was conducted to compare and evaluate the compaction performance and physical properties of recycled asphalt mixtures by utilizing the characteristics of hot-mix asphalt mixtures and foamed asphalt. METHODS : A wearing-course mixture was used for performance evaluations. Subsequently, dynamic shear rheometry (DSR), compaction performance, general physical properties, tensile strength ratio, and Hamburg wheel tracking were tested. RESULTS : As a result of performance comparisons, compaction, and general physical properties satisfied the quality standards. In the Hamburg wheel tracking test, the mixture with the antistripping agent improved performance by approximately 40% compared with the general mixture. As the foamed asphalt binder was produced at a relatively low temperature compared with the general hot-mix asphalt binder, the penetration, viscosity, and DSR test results of the aged foamed asphalt binder showed that the aging of the asphalt binder was suppressed, and the flexibility increased. Therefore, the resistance to fatigue cracks is expected to be enhanced. CONCLUSIONS : Even though the foamed warm-mix recycled asphalt mixture was produced at a temperature that was 20~30°C lower than the hot-mix asphalt mixture, its physical properties were similar to those of the hot-mix asphalt mixture; its use is expected to reduce the production of fuel and air pollutants.

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.