PURPOSES : This study aimed to develop a quantitative structure property relationships (QSPR) model to predict the density from the molecular structure information of the asphalt binder AAA1, a non-full connected structure mixed with a total of 12 molecules. METHODS : The partial least squares regression (PLSR) model, which models the relationship between predictions and responses and the structure of these variables, was applied to predict the density of a binder with molecule descriptors. The PLSR model could also analyze data with collinear, noisy, and multiple dimensional independent variables. The density and additive-free AAA1 binder’s molecule systems generated by an asphalt binder’s molecules-related study were used to fit the PLSR model with the molecular descriptors produced using alvaDesc software. In addition to developing the relationship, a systematic feature selection framework (i.e., the V-WSP- and PLSR-modelbased genetic algorithm (GA)) was applied to explore sets of predictors which contributed to predicting the physical property. RESULTS : The PLSR model accurately predicted the density for the AAA1 binder’s molecules using the condition of the temperature and aging level (R2 was 0.9537, RMSE was 0.00424, and MAP was 0.00323 for the test data) and provided a set of features which correlated well to the property. CONCLUSIONS : Through the establishment of the physical property prediction model, it was possible to evaluate the physical properties of construction materials without limited experiments or simulations, and it could be used to comprehensively design the modified material composition.

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.

해외 위험지역에서 다양한 위난상황으로부터 재외국민을 보호하고 본 국으로 안전한 귀환을 위해 외교·국방·정보 역량을 동원하여 수행되는 활 동이 비전투원후송작전(NEO)이다. 미국과 한국이 수행했던 NEO 사례분 석을 바탕으로 도출된 NEO의 성공적인 수행을 위한 요인과 시사점은 다 음과 같다. 첫째, NEO 계획의 핵심요소는 변화하는 작전환경에 대한 상 황인식과 대비태세이다. 둘째, 후송작전의 기본원칙인 정확성, 보안, 속 도를 기반으로 하여 적대세력의 접근경로와 공격유형을 파악하고, 급변 하는 위협환경에 대응할 수 있는 신속대응군과 후송부대를 투입해야한 다. 셋째, NEO 계획, 경보발령, 집결·재배치, 후송·귀환 과정에서 국무부 /외교부, 국방부, 재외공관, NEO 수행부대 간의 효과적인 협력과 조정 업무가 이루어져야한다. 넷째, 국방부와 정보기관은 현지 임무수행단에 게 작전지역 평가, 위협평가, 적대세력의 위협방책 식별, 대응책 등의 정보를 제공해야한다. 다섯째, 내란과 분쟁지역에서 NEO는 시·공간 제 한사항이 많은 원거리 해외지역에서 작전이기 때문에 동맹국·우방국과의 긴밀한 군사협력 및 연합작전도 필수적이다.

PURPOSES : In this study, the resources and energy consumed to produce hot mix asphalt mixtures and hot mix reclaimed asphalt mixtures in asphalt concrete plants were estimated and the emissions from the detailed processes of the production process were evaluated based on TRACI(the tool for the reduction and assessment of chemical and other environmental impacts). METHODS : To estimate the energy consumption of the aggregate drying process, which consumes a significant amount of energy in the production process, an energy consumption calculation model based on the thermal equilibrium equation was used, and the energy consumed for material transportation, storage, and operation of other facilities was cited from the literature. RESULTS : For the system boundary conditions established and the inventory considered, the emissions to produce one ton of hot mix reclaimed asphalt mix are greater than the emissions to produce one ton of hot mix asphalt mix for a number of key impact categories. The process of producing hot mix reclaimed asphalt mixtures was evaluated to consume more resources and energy in the production of recycled aggregates and heating for drying than in the production of hot mix asphalt mixtures, but less resources and energy in the production of binders and natural virgin aggregates and the heating to heat these materials. CONCLUSIONS : The results of the emissions assessment using the life cycle inventory for the production of hot mix asphalt mixtures were generally similar to the results understood in the field and in much of the literatures, confirming the reliability of the methodology. However, in order to evaluate the dominance of specific processes or mixtures, it is believed that the construction of a wide range of inventory databases after inventory redesign is necessary for a specific and rigorous assessment.

PURPOSES : In this study, energy-consuming processes in asphalt plants were evaluated, and the drying and mixing processes were characterized using a thermal equilibrium equation-based model to quantitatively estimate the amount of energy consumed during the production of mixtures in asphalt concrete plants. METHODS : An energy consumption model based on the thermal equilibrium equation was used to estimate the energy consumption of the aggregate drying process that consumes the maximum energy; the energy consumed for material transportation, storage, and operation of other facilities was cited from the literature. The results were compared with the actual results obtained for recycled hot asphalt mixtures and recycled warm mix asphalt mixtures, and a sensitivity analysis was performed by varying the conditions. RESULTS : An analysis of the main processes required to produce asphalt mixtures showed that the water content had the largest impact on energy consumption (approximately 80%). This quantitatively supports the opinion of field practitioners that maximum energy is consumed during aggregate drying. Although some discrepancies were observed, the results were found to be reasonable and within the range of typical measurements. CONCLUSIONS : The thermal energy consumption estimation model provides consistent results that reflect the characteristics of the mixture and can be used to derive the thermal energy consumption rates for individual materials, such as aggregates and binders. This can be used to identify the priorities for process optimization within a plant.

PURPOSES : This study aims to determine whether machine learning techniques based on the results of chemical analysis experiments can be rationally applied to evaluate the aging of various asphalt binders used throughout the country. METHODS : We conducted chemical experiments such as FT-IR, H-NMR, C- NMR, and GPC for the three-stage aging levels of eight types of asphalt binders used in the country and utilized two artificial neural network models to determine valid chemical experimentation and conditions for the use of neural modeling through predictions. RESULTS : The M-prop model, which combined the findings from each neural network model into a single artificial neural network model, demonstrated superior predictive performance compared with the M-base model, which assessed aging using two cluster layers. In addition, the minimum amount of data required to achieve 100% predictive accuracy for the target asphalt binders, regardless of the artificial neural network model, was 18, and the amount of training data decreased to less than 50%. CONCLUSIONS : The predictive accuracy of the aging of asphalt binders was significantly enhanced when GPC data was used, indicating that GPC should be prioritized in evaluating the aging of asphalt binders.

PURPOSES : In this study, we aimed to evaluate the transition temperature (Tt) of asphalt binders using molecular dynamics simulations, which can provide a more accurate assessment of the mechanical properties of a material at the molecular level and can be applied to material development and design. METHODS : Unlike conventional macro- or meso-level simulations, we utilized MD simulations to evaluate the Tg of asphalt binders based on material composition and aging degree as input variables. In this analysis, 11 temperatures ranging from 434 K to 233 K at 20 K intervals were utilized, and the bulk volume and density were calculated through MD simulations. RESULTS : The MD simulation successfully predicted the Tg of the asphalt binder, and the molecular-level properties and interactions determined in this study can be applied not only to material development but also to the determination of constitutive equations or contact models used in continuum mechanics or discrete element methods. The calculated Tg was slightly different depending on the aging of the asphalt binder; however, it was found to accurately reflect the transitional characteristics. CONCLUSIONS : This study demonstrated the potential of MD simulations as valuable tools for material development and design in the construction industry. The results indicate that the use of MD simulations can lead to more accurate and efficient material development and design by providing a more detailed understanding of material properties and interactions at the molecular level.

PURPOSES : In this study, emissions from asphalt mixture production and construction processes are calculated and used to estimate the emission from each asphalt pavement layer. The calculated emissions for the processes are used as fundamental data to estimate the total emission from the entire life cycle of pavement engineering in South Korea. METHODS : A design proposal and the Korean standard, which provide quantitative information for activities, were used to estimate the amount of construction materials and energy consumption. Subsequently, the LCI DB from NAPA and the LCIA DB from EPA were utilized in conjunction with the estimated quantity to assess the effect of the emissions to determine their environmental impact categories. RESULTS : Calculation results show that 5.84 million ton of CO2eq is discharged from production and construction processes, whereas 3.24 million ton of CO2eq is discharged from operation processes in the pavement engineering sector. The total GHG emission, i.e., 9.08 million ton of CO2eq, is approximately 1.25% of the national GHG emission in 2018. The asphalt mixture production process results in the highest GHG emission in the life cycle of asphalt pavements. CONCLUSIONS : An LCI DB that accounts for the industrial characteristics of South Korea must be established to provide more reliable emission data to be used for national GHG reduction plans, including those for the pavement engineering sector.

PURPOSES : The cooling characteristics of the asphalt mixture in a moving dump truck were analyzed using a numerical simulation method. The cooling characteristic can be used to determine the optimum transport path for minimizing the temperature drop of the asphalt mixture. METHODS : In this research, a coupled analysis of the discrete element method (DEM) with computational fluid dynamics (CFD) was applied for cooling characteristic analysis of asphalt mixtures in transit. Two different transit speeds, 30 km/h and 60 km/h, were considered to evaluate the effect of speed on the temperature drop of the asphalt mixture. Velocity, pressure, and temperature contours were plotted and temperature variations were compared. RESULTS : Most of the temperature drops in the asphalt mixture were observed in the middle of the dump box in the longitudinal direction. It was confirmed that a faster speed causes a greater temperature drop for the same travel time and a slower speed causes the more temperature to reach the same travel distance as expected. CONCLUSIONS : It is concluded that the coupled analysis method can be used to quantitatively evaluate the effect of vehicle speed on temperature drop in asphalt mixtures. In addition, the method can be used to determine the optimum travel path considering environmental conditions and traffic congestion.

PURPOSES: In this study, a numerical parametric study was performed to evaluate the effect of angular velocity and weight of wheel, and density of road-bed particles on corrugation development. METHODS : Discrete element method coupled with rigid body dynamics was applied to simulate a wheel-running circular table with variations in independent parameters, such as wheel angular velocity, wheel weight, and particle density. The position profiles for travel distance from origin were compared and analyzed to confirm if the trend from numerical analysis agrees with the analytical solution. RESULTS: The angular velocity of the wheel exhibits a clear inverse relationship with the development of corrugation even though the weight of wheel does not demonstrate clear trends for both long-wave and short-wave corrugation. The density of road-bed particles is observed to have clear proportional effect on corrugation development. The movement of corrugation to the running direction, which was observed in previous research, is also observed for various conditions. CONCLUSIONS : The parametric study using discrete element method with rigid body dynamics clearly exhibits good agreement with analytical solution for initiation of corrugation. The coupled method is confirmed to supply additional information that cannot be delivered by analytical solution only.

PURPOSES : The feasibilities of cohesive elastoplastic contact model and discrete element method (DEM) for asphalt concrete mixture compaction process were evaluated. METHODS : The contact models that were used to simulate the dynamic behavior of construction materials were reviewed. The characteristics of cohesive elastoplastic models were discussed from the perspective of integration with existing contact models. Two asphalt mixtures that were fabricated with specific aggregate gradations and binder contents were compacted according to the Superpave gyratory compaction specification. The parameters for the model were determined via trial-and-error method. The heights of the specimens were plotted with respect to number of gyrations. The results of the laboratory tests were compared to those of numerical simulations. The displacement of particles in asphalt mixture specimen was also visualized to understand the effect of gyratory compaction on asphalt mixture specimen. RESULTS : The DEM model exhibited a significant friction coefficient dependency on compaction degree and slop. The DEM model with parameters determined through trial and error demonstrated reasonable simulation results in terms of specimen height at a gyration number. CONCLUSIONS: Even though a little discrepancy was observed between the results of the experimental test and numerical simulation, a combination of DEM with cohesive elastoplastic contact model seems to be applicable for the simulation of asphalt mixture compaction in laboratory. However, the model needs to be enhanced to be used for more realistic compaction processes, including heat transfer, phase change, and vibratory loading.

PURPOSES: This study proposes a cohesive shrinkage particle model that can be used to simulate a variety of dynamic behaviors and phase changes of construction materials, including road subsidence and debris flow, and phase change curing, via discrete element method (DEM). METHODS : From the perspective of DEM modeling, the water-content-dependent characteristics of soil particles and related modeling techniques are reviewed from literature. The static friction, cohesion, and particle size change are considered as the major parameters that should be reflected in DEM modeling for a more realistic simulation. The relationships of water content with cohesive force and particle radius, as determined from experimental test results in the relevant study, are utilized to develop the cohesive shrinkage model. For each water content value, the snapshot in simulation is compared to that in the experimental study. RESULTS: The numerical simulation shows very good agreement with the experimental test in terms of overall sample radius and thickness change due to drying. However, the local curling of soil sample in the DEM simulation does not perfectly match that in the experimental test. CONCLUSIONS : The cohesive shrinking particle model seems to be good enough for simulating the volumetric and phase changes of soil samples due to drying. However, it seems necessary to consider both bonding and cohesive contact models in DEM modeling because the only cohesive contact model exhibited limitations in the simulation of curling and crack development.