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.

시멘트 콘크리트 포장의 양생 공정에서는 피막양생제를 살포하는 것이 가장 일반적이며 양생포와 같은 덮개를 콘크리트 포장 위에 덮어 온도와 습도를 유지하는 방법으로 콘크리트 포장의 강도를 발현시키기도 한다. 콘크리트 포장의 미끄럼 저항 및 배수, 주행안전 성을 향상시키기 위해서는 양생 공정 이전에 표면 타이닝 공정을 수행하는 것이 일반적이지만 양생 이후에 그루빙을 실시하기도 한다. 본 연구에서는 콘크리트 포장 품질에 지대한 영향을 주는 양생 작업과 표면 그루빙 작업의 일원화 방법 개발을 위한 기초 연구로써 3D 스케치 프로그램과 3D 프린터를 이용하여 타원형, 삼각형, 사각형 모양의 홈으로 그루빙을 형성하면서 동시에 양생포로 사용이 가 능한 그루빙 양생 플레이트를 설계하여 제작하였다. 그루빙 양생 플레이트의 적용성을 분석하기 위해 콘크리트 공시체를 제작하여 실 내 실험을 수행하였으며 양생 플레이트의 그루빙 홈 형상에 따른 콘크리트 포장 표면 그루빙 형성 상태를 분석하였다.

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.

This study was conducted to examine the microbiological quality indicators (total bacterial count and coliform count) and physicochemical quality indicators (pH, redness, volatile basic nitrogen [VBN] content) of meat according to various storage temperatures (20~15oC) and packaging methods (wrap, vacuum). Based on these results, we proposed a safe consumption period. Redness, pH, and VBN content were not considered appropriate for setting the expiration date, as the redness and pH of the meat after spoilage were better than the standard values for both vacuum and wrap packaging (p<0.05). Additionally, the VBN content at 2 and 4oC increased slightly (fresh level) until the initial time of spoilage (1.0×106 colony-forming unit [CFU]/cm2) and then increased rapidly thereafter. Therefore, the results were not consistent with microbial spoilage. When the decay point was evaluated based on the presence of microorganisms, vacuum packaging extended the storage period approximately 2.5-fold when compared with wrap packaging, and the meat could be stored at 2 or 4oC for 40 or 23 days, respectively. Therefore, to evaluate meat quality, microbial indicators should be considered first. The microbiological standards proposed in this study can be used for safety management during the distribution of meat. However, to ensure meat safety, additional investigations of appropriate indicators of freshness must be conducted.

PURPOSES : In this study, a method for evaluating concrete bridge deck deterioration using three-dimensional (3D) ground penetrating radar (GPR) survey data and its in situ application are discussed. METHODS : Field surveys are conducted on two bridges in Yongsan-gu (Bridge A) and Seodaemun-gu (Bridge B) in Seoul using 3D GPR. The obtained survey data are used to calculate the dielectric constant map of each bridge using the extended common midpoint method. In addition, random points on both bridges are selected for the chloride content test in accordance with the KS F 2713 standard. The results from the dielectric constant map and chloride content test are compared. RESULTS : For Bridge A, it is discovered that the percentage of sections with a dielectric constant of 5.0 or less is 1.57%, whereas that above 5.0 is 98.43%; this indicates that the percentage of deteriorated sections for Bridge A is low. Meanwhile, for Bridge B, the dielectric constants calculated for the entire bridge exceed 5.0, which suggests no deterioration for Bridge B. Moreover, all the points selected for the chloride content test have less than 0.15% chloride content and have dielectric constants ranging from 5.0 to 7.0, which are favorable condition for the bridge deck. CONCLUSIONS : The analysis results of the dielectric constants of the concrete bridge deck obtained from the 3D GPR system are consistent with the actual chloride content results. Furthermore, additional verification of this method through field surveys on bridge sections with severe deterioration is highly recommended for future improvements.