Structural characteristics influence assessment of fatigue cracking behavior. In the assessment of asphalt pavements, the asphalt structure and practical conditions must be considered. This study analyzes changes in the elastic modulus of the pavement of different asphalt mixtures amid aging and moisture damage through fatigue cracking tests. A model to predict the tensile strain at the bottom of the pavement layer is developed through a structural analysis based on the material properties. The results are comparatively analyzed using the Mechanistic-Empirical Pavement Design Guide to predict the fatigue crack life. The test results indicate that moisture damage significantly influences the material properties of asphalt pavement and can accelerate pavement damage as the asphalt ages. The coefficient values of the proposed fatigue-life prediction model can be used to predict the fatigue life depending on the age of the asphalt and its moisture damage after aging. The degree of fatigue damage can be predicted by calculating the tensile strain using the regression equation and elastic modulus according to the aging and moisture damage.

This study presents a machine learning model for predicting representative surface distresses (crack, durability, patching, joint spall) in concrete pavements, focusing on South Korean examples. It thoroughly analyzes specific distress types using time series data to understand their development over time, aiming to surpass traditional regression methods in forecasting pavement conditions. The research fills a gap by applying machine learning algorithms to detailed long-term data, enhancing the accuracy of distress progression predictions, which is crucial for efficient pavement management. A notable aspect of this study is the use of particle filtering, recognized for its effective resampling in analyzing time series data. To validate predictions, we compared the results from particle filtering with those from traditional regression models, long short-term memory (LSTM) networks, and Deep Neural Networks (DNNs). The accuracy varied significantly, with differences ranging from 3.32% to 23.64%, indicating particle filtering’s suitability for time-series-based pavement condition predictions. These findings are especially relevant in the context of current image-based machine learning and AI research in pavement distress detection and prediction. This research offers a comprehensive reference that is especially valuable due to the lack of studies using long-term usage data, thereby making a significant contribution to pavement management research and practice.

A number of warm mix asphalt (WMA) technology has been developed to allow asphalt mixtures to be produced and compacted at a significantly lower temperature. This eco-friendly technology has been spread so quickly in the world. Recently, an innovative WMA additive has been developed to reduce mixing and paving temperatures applied in asphalt paving process by Korea Institute of Construction Technology (KICT) and Kumho Petrochemical in Korea. It is named low energy and low carbon-dioxide asphalt pavement (LEADCAP), which is an organic additive of a wax-based composition including crystal controller and artificial materials. In this study, WMA mixtures using LEADCAP additive along with the control hot mix asphalt (HMA) mixtures were evaluated with respect to their moisture susceptibility and rutting resistance in the laboratory. The WMA pavement using LEADCAP additive along with a conventional HMA pavement were evaluated with respect to their density and air void in the field trials. Based on the limited laboratory and field test results, WMA mixtures using LEADCAP additive is superior to HMA mixtures in the moisture susceptibility and rutting resistance. The LEADCAP additive is found effective in producing and compacting WMA mixtures that are comparable to HMA mixtures.

As part of the research to evaluate the Warm-Mix Asphalt (WMA) performance for use in Korea, an extensive testing program has been conducted on the warm-mix asphalt technology that is newly developed in Korea, along with Hot Mix Asphalt (HMA). This research program consists of Accelerated Pavement Test (APT) and laboratory test. This paper presents the rutting and fatigue performance test results of both WMA and HMA. The rut development due to trafficking loading was evaluated using APT with 8.2 ton loading at 40°C temperature. The transverse profile was measured periodically at each point per test section as a function of mixture types. In order to investigate the fatigue performance, APT applied trafficking loading under wet and dry condition. The very stiff base is likely to complicate the planned fatigue cracking test, in that a huge number of APT repetitions will be generally required before any distress occurs. In this study, therefore, the fatigue test was conducted at 20°C with adding water into the aggregate base layer to accelerate the distress after the given trafficking loading. Cores were taken to be tested in the laboratory after construction of the test track as well as after completion of APT testing on and off the wheel path. The air voids were measured for all cores and dynamic modulus test and fatigue test in indirect testing mode were conducted. Based on the limited data obtained from this study, it is concluded that WMA mixture performs comparable to HMA mixture in terms of rutting and fatigue resistance.

As a result of the 1997 Kyoto treaty on climate changes, many countries n the world were faced with greenhouse gas reduction targets. Warm-mix asphalt (WMA) technologies are currently of interest to road construction industry around the world. WMA technology was developed in Europe and introduced into the United States in 2002. WMA technologies can decrease the energy consumption and emissions associated with conventional hot-mix asphalt (HMA) production. Based on those benefits and increasing awareness of WMA, the Korea Institute of Construction and Technology (KICT) developed WMA technology in Korea. WMA developed by KICT used a WMA additive that was developed by Korea Kumho Petrochemical Co. LTD. To evaluate the performance of WMA developed in Korea, an experimental test program was designed to evaluate rutting and crack resistance by using thewheel track test and indirect tensile strength test as a function of mixture types. In the case of rutting resistance, WMA shows better performance than HMA at high temperature. The Indirect Tensile Strength (IDT) test results of both WMA and HMA were same.