도로포장의 노면 마찰력은 노면 조직 특성에 큰 영향을 받으며, 이를 예측하기 위한 인자로써 MTD(Mean Texture Depth, 평균 노면 조직 깊이)를 주로 사용한다. 그러나 MTD는 노면 특성 중 노면 조직의 깊이만을 나타내므로 여러 요인이 복합적으로 구성되어 있는 노면 조직 특성을 포괄적으로 설명할 수 없다. 이에 선행 연구에서는 다양한 노면조직 특성을 반영하여 보다 적합한 마찰력 예측 식 을 제안하고자 하였다. 노면 마찰력에 영향을 미치는 노면 조직 특성을 정량화하기 위하여 3D 프린팅 시편을 제작한 후 BPT(British Pendulum Tester)를 이용해 노면 마찰력(BPN; British Pendulum Number)을 측정하였다. 선행 연구를 통하여 노면 마찰력에 영향을 미치 는 노면 조직을 MTD, EAN(Exposed Aggregate Number, 골재노출도) 및 골재 형상으로 선정하였으며, 이를 포함한 노면 마찰력 예측 식 을 제안하였다. 그러나 3D 프린팅 시편을 사용하여 제안한 노면 마찰력 예측식의 경우 이상적인 노면조직 특성에 기반하여 제안된 것 으로 실제 현장에서의 노면 조직 특성과 비교 및 검증이 이루어져야 한다. 이에 3D 프린팅 시편을 기반으로 개발된 노면 마찰력 예측 식의 현장 적용성 평가를 위하여 EACP(Exposed Aggregate Concrete Pavement), 밀입도 및 개립도 아스팔트 콘크리트 포장에서 188개의 노면 조직 데이터를 측정하였다. 현장 측정 데이터와 3D 프린팅 시편을 기반으로 개발된 노면 마찰력 예측 식을 비교 검토한 결과 MTD, EAN 및 골재 형상은 노면 마찰력 예측에 있어서 유의미한 지표로 사용될 수 있는 것으로 확인하였다.

PURPOSES : Pavement surface friction depends significantly on pavement surface texture characteristics. The mean texture depth (MTD), which is an index representing pavement surface texture characteristics, is typically used to predict pavement surface friction. However, the MTD may not be sufficient to represent the texture characteristics to predict friction. To enhance the prediction of pavement surface friction, one must select additional variables that can explain complex pavement surface textures. METHODS : In this study, pavement surface texture characteristics that affect pavement surface friction were analyzed based on the friction mechanism. The wavelength, pavement surface texture shape, and pavement texture depth were hypothesized to significantly affect the surface friction of pavement. To verify this, the effects of the three abovementioned pavement surface texture characteristics on pavement surface friction must be investigated. However, because the surface texture of actual pavements is irregular, examining the individual effects of these characteristics is difficult. To achieve this goal, the selected pavement surface texture characteristics were formed quantitatively, and the irregularities of the actual pavement surface texture were improved by artificially forming the pavement surface texture using threedimensionally printed specimens. To reflect the pavement surface texture characteristics in the specimen, the MTD was set as the pavement surface texture depth, and the exposed aggregate number (EAN) was set as a variable. Additionally, the aggregate shape was controlled to reflect the characteristics of the pavement surface texture of the specimen. Subsequently, a shape index was proposed and implemented in a statistical analysis to investigate its effect on pavement friction. The pavement surface friction was measured via the British pendulum test, which enables measurement to be performed in narrow areas, considering the limited size of the three-dimensionally printed specimens. On wet pavement surfaces, the pavement surface friction reduced significantly because of the water film, which intensified the effect of the pavement surface texture. Therefore, the pavement surface friction was measured under wet conditions. Accordingly, a BPN (wet) prediction model was proposed by statistically analyzing the relationship among the MTD, EAN, aggregate shape, and BPN (wet). RESULTS : Pavement surface friction is affected by adhesion and hysteresis, with hysteresis being the predominant factor under wet conditions. Because hysteresis is caused by the deformation of rubber, pavement surface friction can be secured through the formation of a pavement surface texture that causes rubber deformation. Hysteresis occurs through the function of macro-textures among pavement surface textures, and the effects of macro-texture factors such as the EAN, MTD, and aggregate shape on the BPN (wet) are as follows: 1) The MTD ranges set in this study are 0.8, 1.0, and 1.2, and under the experimental conditions, the BPN (wet) increases linearly with the MTD. 2) An optimum EAN is indicated when the BPN (wet) is the maximum, and the BPN decreases after its maximum value is attained. This may be because when the EAN increases excessively, the space for the rubber to penetrate decreases, thereby reducing the hysteresis. 3) The shape of the aggregate is closely related to the EAN; meanwhile, the maximum value of the pavement surface friction and the optimum EAN change depending on the aggregate shape. This is believed to be due to changes in the rubber penetration volume based on the aggregate shape. Based on the results above, a statistical prediction model for the BPN (wet) is proposed using the MTD, EAN, and shape index as variables. CONCLUSIONS : The EAN, MTD, and aggregate shape are crucial factors in predicting skid resistance. Notably, the EAN and aggregate shape, which are not incorporated into existing pavement surface friction prediction models, affect the pavement surface friction. However, the texture of the specimen created via three-dimensional printing differs significantly from the actual pavement surface texture. Therefore, the pavement surface friction prediction model proposed in this study should be supplemented with comparisons with actual pavement surface data in the future.

The enamel powders used traditionally in Korea are produced by a ball-milling process. Because of their irregular shapes, enamel powders exhibit poor flowability. Therefore, polygonal enamel powders are only used for handmade cloisonné crafts. In order to industrialize or automate the process of cloisonné crafts, it is essential to control the size and shape of the powder. In this study, the flowability of the enamel powders was improved using the spheroidization process, which employs the RF plasma treatment. In addition, a simple grid structure and logo were successfully produced using the additive manufacturing process (powder bed fusion), which utilizes spherical enamel powders. The additive manufacturing technology of spherical enamel powders is expected to be widely used in the field of cloisonné crafting in the future.