PURPOSES : This study evaluates the noise reduction effects of various road paving methods and focuses on low-noise pavements as a cost-effective alternative to sound barriers and tunnels. In addition, this study assesses how noise levels vary with vehicle speed across different paving methods. METHODS : An analysis of variance (ANOVA) was conducted to evaluate the noise performance of different paving methods, and this followed by a post-hoc analysis to examine the differences among the paving methods. Another ANOVA was conducted to evaluate the impact of speed on noise performance. This ANOVA was followed by a post hoc analysis to assess differences by speed. Finally, a covariance analysis was conducted, using speed as a covariate, to evaluate the noise reduction effects of the various paving methods. RESULTS : The results of the analyses showed that noise levels follow the order of General ≈ Non-draining > Single-layer ≈ Doublelayer, thus grouping the paving methods into two categories with significant differences in noise performance. In addition, the noise levels increased with speed, except at 70 and 80 km/h. The covariance analysis resulted in a regression coefficient of 0.267 for speed across all paving methods. A post-hoc analysis grouped the paving methods into three distinct categories: General, Non-draining ≈ Single-layer ≈ Double-layer, with notable noise differences between them. CONCLUSIONS : The analysis of noise performance showed that both the paving method and speed significantly affected the noise levels. The covariance analysis, using speed as a covariate, revealed a consistent regression coefficient of 0.267 across all the paving methods. After controlling for speed, noise differences were observed. The General method showed higher noise levels than did the Non-draining, Doublelayer, and Single-layer methods.

본 논문에서는 다양한 기상 조건에서 시인성과 내구성을 향상시키도록 설계된 도로 표시용 UV 경화 코팅 시스템 개발을 위해 수행한 연구의 결과를 나타내었다. 제조된 UV 코팅을 사용해 차선 표시의 재귀반사도와 내마모성을 강화하고 포장가속시험(APT), 휠 트래킹 내구성 테스트 등 다양한 테스트를 통해 성능을 평가하였다. 이 결과를 바탕으로 도로 안전을 위한 야간 시인성 및 미끄럼을 개선하 고자 한다.

본 논문에서는 건설 현장 관리의 과제를 다루고 IoT 기술 활용을 위한 기술 적용에 대해 정리하였다. 도로 포장 장비의 유휴 시간을 모니터링하는 IoT 장치를 설계 및 구현하여 효율적인 장비 관리 시스템을 개발하는 것을 목표한다. 또한, 본 연구에서는 통신방식 선 정, 사용자 친화적인 플랫폼 설계, 데이터 수집 및 분석을 위한 진동센서 기반 IoT 디바이스 개발을 통한 실시간 관리에 중점을 두고 있다. 플랫폼을 통해 공사현황을 실시간으로 모니터링하고 장비 유휴시간을 관리해 효율성을 높일 수 있으며, IoT 디바이스는 90% 이 상의 데이터 정확도를 보장한다. 현장 테스트를 통해 장비 사용 추적 효과가 확인되어 보다 효율적인 건설 관리에 기여하고자 한다.

기후변화에 따라 수자원의 취약성이 증가하고 있고, 그로 인해 지하수 자원의 필요성이 강조되고 있다. 특히, 낙동강권역이 자리 잡은 한반도 남부는 매년 봄 가뭄과 같은 물 부족 현상이 빈번하게 발생하고 있다. 물 부족의 대안 으로 지하수 자원 이용이 대두되고 있으나, 지하수 자원의 활용에는 수질 안정성이 반드시 요구된다. 이 연구는 2023년 8월과 10월, 2회에 걸쳐 낙동강 하류 광려천 유역을 대상으로 지하수 관정 총 54개소와 하천수 총 5개의 지점에서 시 료를 채취하여 현장 수질 및 실내 수질 분석을 수행하였다. 현장에서 측정한 전기전도도의 값은 지하수와 하천수 모두 연구 지역 수계 하류로 갈수록 농도가 증가하는 경향을 보여 준다. 이는 하류의 농업 활동이 하천수에 직접적으로 유 입됨을 지시한다. 실내 수질 분석 결과 연구 지역의 수질 유형은 주로 [Ca-HCO3] 유형이 가장 많고, [Ca-SO4] 유형이 그 뒤를 이었다. 8월과 10월 시간에 따른 수질 유형의 변화를 확인하면, Ca 함량이 우세한 지역이 Na 함량이 우세한 지역으로 변화하고, 이러한 지하수 관정은 주로 하류에 위치하고 있음을 확인하였다. 결국 연구 지역 하류의 하천수·지 하수의 농도 변화는 공장단지, 폐수 처리시설, 농경지의 분포 현황 및 낙동강 하류의 유입과 밀접한 관계가 있고, 이를 통해 인위적인 오염이 발생하였음을 유추할 수 있다.

세계 각국은 온실가스 배출을 줄이기 위하여 활발한 노력을 하고 있다. 한국도 노후화된 석탄발전을 폐지하고 LNG 발전으로 전환하는 정책을 추진하고 있다. 그러나, 한국은 가스터빈 제작 기술이 국산화되지 않아서 해외 제작사로부터 전량 수입하여 설치하고 있다. 따라서, 본 논고에서는 가스터빈 발전산업에 대한 국내·외 환경을 살펴보고, 이를 기반으로 PEST-SWOT-AHP 방법론을 적용하여 한국형 가스터빈 기술개발 및 보급 확대 추진전략을 제안하였다. 연구결과, 한국형 가스터빈 기술개발과 보급 확대 전략은 1) 가스터빈 기술개발 및 사업화 촉진을 위한 발전공기업의 역할 강화, 2) 온실가스 감축을 위한 LNG 발전 비중 확대, 3) 정부의 적극적인 가스터빈 산업 생태계 조성 노력, 4) LNG 발전소 건설에 대한 국민 공감대 형성 등으로 요약할 수 있다.

PURPOSES : The aim of this study is to investigate the enhancement of performance and the mix design method for asphalt mixtures utilizing ferronickel slag, an industrial by-product METHODS : To enhance the performance of FNS asphalt, waste tire powder (CR) was incorporated, and the characteristics of FNS asphalt aggregate, along with the impact of CR, were evaluated through the mix design process. RESULTS : CR is found to be suitable with a size of 30 mesh, and the optimal usage amount is determined to be 1±0.1% of the mixture weight, considering dense grade asphalt mixture. Volumetric design considering the swelling characteristics of CR is necessary, and a mixing design with a consistent tendency can be achieved only when an appropriate VMA is secured. CONCLUSIONS : The mix design for FNS-R asphalt mixture requires an increase of approximately 1% in VMA compared to conventional dense-graded asphalt mixtures to accommodate the swelling of CR. Additionally, FNS-R asphalt exhibits improved resistance to rutting comparable to modified asphalt and meets quality standards, including stripping resistance.

PURPOSES : Derive a road pavement design method using Geocells, aim to derive a road pavement design and construction method suitable for the characteristics of the Bangladesh region METHODS : To assess long-term performance during road construction in Southeast Asia using Geocells, field tests and numerical analysis are conducted to verify stability. RESULTS : A total of 12 displacement measurements were conducted during the field tests, confirming an average load of 15.75 kN and an average displacement of 0.542mm. Inverse analysis was performed to obtain the properties of Geocell combined with compacted soil. The numerical analysis results confirmed that the insertion of Geocell provides better stability compared to the case with only compacted soil. CONCLUSIONS : Based on field tests and numerical analysis, a road design plan suitable for the Southeast Asian environment was proposed. A preliminary test section was selected in the Comilla region of Bangladesh, and test construction has been completed. Subsequent evaluations of the structural performance by soil layer in the test construction area will be conducted to develop a Geocell road pavement method, taking into consideration the characteristics of the Bangladesh region.

PURPOSES : This study aims to conduct a laboratory evaluation on the use of ferronickel slag for manufacturing Hot Mix Asphalat mixtures. METHODS : This research was based on laboratory evaluation only, where conventional aggregate and FNS at a ratio of 7:3 were used in HMA and the volumetric properties, physical and mechanical properties, and long-term performance of FNS in asphalt mixture were evaluated. RESULTS : The overall results showed that FNS can be applied as aggregate in a hot mix asphalt since volumetric, physical and mechanical properties and long-term performance of HMA mixture with ferronickel slags as aggregate met the required standards according to Korean standards for Asphalt Concrete. CONCLUSIONS : The tensile strength ratio results of HMA mixtures with ferronickel aggregate did not meet the required standards, yet the addition of anti-stripping agent and waste glass fibers to the HMA mixture with ferronickel slags improved the tensile strength results to meet the standards. Additionally, compared to the HMA mixture of the same aggregate gradation but with only natural aggregate, HMA mixture with ferronickel slags had almost the same results for the majority of tests conducted.

PURPOSES : This study is aimed to economic analysis of the ferronickel slag pavement method carried out to suggest the necessity of developing ferronickel slag pavement technology. METHODS : A life cycle cost analysis of the application of the Ferronickel Slag pavement method and the cutting + overlay pavement method was performed to compare the economic indicators and greenhouse gas emissions for each pavement method. RESULTS : As a result of the analysis, regardless of the Ferronickel Slag mixing rate, if the common performance of the Ferronickel Slag pavement method is the same or superior to the existing pavement method, it is more economical than the existing pavement method. Furthermore, the lower the maintenance cost of the Ferronickel Slag pavement method, the higher the economic feasibility due to the high Ferronickel Slag mixing rate. Greenhouse gas emissions can be reduced from at least 9% to up to 53% through the application of the Ferronickel Slag pavement method, except for some scenario analysis results. CONCLUSIONS : This study provided that the Ferronickel Slag pavement method was superior to the existing pavement method in terms of economic and environmental aspects. Therefore, it was found that the objective justification of developing road pavement technology using Ferronickel Slag was secured.

PURPOSES : The objective of this study is to develop the data driven pavement condition index by considering the traffic and climatic characteristics in Incheon city. METHODS : The Incheon pavement condition index (IPCI) was proposed using the weighted sum concept with standardization and coefficient of variation for measured pavement performance data, such as crack rate, rut depth, and International Roughness Index (IRI). A correlation study between the National Highway Pavement Condition Index (NHPCI) and Seoul Pavement Condition Index (SPI) was conducted to validate the accuracy of the IPCI. RESULTS : The equation for determining the IPCI was developed using standardization and the coefficient of variation for the crack rate, rut depth, and IRI collected in the field. It was found from the statistical analysis that the weight factors of the IPCI for the crack rate were twice as high as those for the rut depth and IRI. It was also observed that IPCI had a close correlation with the NHPCI and SPI, albeit with some degree of scattering. This correlation study between the NHPCI and SPI indicates that the existing pavement condition index does not consider the asymmetry of the original measured data. CONCLUSIONS : The proposed pavement condition provides an index value that considers the characteristics of the original raw data measured in the field. The developed pavement condition index is extensively used to determine the timing and method of pavement repair, and to establish pavement maintenance and rehabilitation strategies in Incheon.

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.

PURPOSES : Local governments in Korea, including Incheon city, have introduced the pavement management system (PMS). However, the verification of the repair time and repair section of roads remains difficult owing to the non-existence of a systematic data acquisition system. Therefore, data refinement is performed using various techniques when analyzing statistical data in diverse fields. In this study, clustering is used to analyze PMS data, and correlation analysis is conducted between pavement performance and influencing factors. METHODS : First, the clustering type was selected. The representative clustering types include K-means, mean shift, and density-based spatial clustering of applications with noise (DBSCAN). In this study, data purification was performed using DBSCAN for clustering. Because of the difficulty in determining a threshold for high-dimensional data, multiple clustering, which is a type of DBSCAN, was applied, and the number of clustering was set up to two. Clustering for the surface distress (SD), rut depth (RD), and international roughness index (IRI) was performed twice using the number of frost days, the highest temperature, and the average temperature, respectively. RESULTS : The clustering result shows that the correlation between the SD and number of frost days improved significantly. The correlation between the maximum temperature factor and precipitation factor, which does not indicate multicollinearity, improved. Meanwhile, the correlation between the RD and highest temperature improved significantly. The correlation between the minimum temperature factor and precipitation factor, which does not exhibit multicollinearity, improved considerably. The correlation between the IRI and average temperature improved as well. The correlation between the low- and high-temperature precipitation factors, which does not indicate multicollinearity, improved. CONCLUSIONS : The result confirms the possibility of applying clustering to refine PMS data and that the correlation among the pavement performance factors improved. However, when applying clustering to PMS data refinement, the limitations must be identified and addressed. Furthermore, clustering may be applicable to the purification of PMS data using AI.