The purpose of this study was to develop a more accurate model for predicting the in-situ compressive strength of concrete pavements using Internet-of-Things (IoT)-based sensors and deep-learning techniques. This study aimed to overcome the limitations of traditional methods by accounting for various environmental conditions. Comprehensive environmental and hydration data were collected using IoT sensors to capture variables such as temperature, humidity, wind speed, and curing time. Data preprocessing included the removal of outliers and selection of relevant variables. Various modeling techniques, including regression analysis, classification and regression tree (CART), and artificial neural network (ANN), were applied to predict the heat of hydration and early compressive strength of concrete. The models were evaluated using metrics such as mean absolute error (MAE) to determine their effectiveness. The ANN model demonstrated superior performance, achieving a high prediction accuracy for early-age concrete strength, with an MAE of 0.297 and a predictive accuracy of 99.8%. For heat-of-hydration temperature prediction, the ANN model also outperformed the regression and CART models, exhibiting a lower MAE of 1.395. The analysis highlighted the significant impacts of temperature and curing time on the hydration process and strength development. This study confirmed that AI-based models, particularly ANNs, are highly effective in predicting early-age concrete strength and hydration temperature under varying environmental conditions. The ability of an ANN model to handle non-linear relationships and complex interactions among variables makes it a promising tool for real-time quality control in construction. Future research should explore the integration of additional factors and long-term strength predictions to further enhance the model accuracy.

The purpose of this study was to derive an optimal mix design for bridge deck pavements that can compensate for the limitations of latexmodified concrete (LMC). To address the limitations of LMC, this paper proposes the incorporation of silica fume into LMC. Concrete mixtures with varying ratios of latex and silica fume were prepared, and tests for compressive strength, flexural strength, and chloride-ion penetration resistance were conducted to compare and analyze the fundamental performance of each mix. Latex contributed to the improvement of the initial pore structure and significantly affected the chloride-ion penetration resistance in the early stages of curing. However, its influence gradually diminished over time. In contrast, silica fume induced additional C-S-H formation and further improved the pore structure through pozzolanic reactions as time progressed, thus exerting a greater impact in the later stages of curing. The L7-SF8 variable demonstrated the best performance in terms of compressive strength and chloride-ion penetration resistance. Given the characteristics of bridge-deck pavements, this variable is considered the most suitable for ensuring long-term durability. Therefore, this paper proposes a mixture of 7% latex and 8% silica fume as the optimal mix design.

This study aimed to develop a pavement management system suitable for the climate and traffic characteristics of Gangwon Province. This research focused on analyzing the asphalt pavement performance characteristics of national highways in Gangwon Province by region and developing prediction models for the current pavement performance and annual changes in performance. Quantitative indicators were collected to evaluate the condition of national highway pavements in Gangwon Province, including factors affecting road performance, such as weather data and traffic volume. The Gangwon region was then classified according to its topography, climate, weather, traffic volume, and pavement performance. Prediction models for the current pavement performance and annual changes in performance were developed for national highways. This study also compared the predicted values for the Gangwon region using a nationwide pavement performance-prediction model from other studies with the predicted values from the developed annual changes in the performance prediction model. This study established a foundation for implementing a pavement management system tailored to the unique climate and traffic characteristics of Gangwon Province. By developing region-specific performance prediction models, this study provided valuable insights into more effective and efficient pavement maintenance strategies in Gangwon Province.

This study aimed to improve the accuracy of road pavement design by comparing and analyzing various statistical and machine-learning techniques for predicting asphalt layer thickness, focusing on regional roads in Pakistan. The explanatory variables selected for this study included the annual average daily traffic (AADT), subbase thickness, and subgrade California bearing ratio (CBR) values from six cities in Pakistan. The statistical prediction models used were multiple linear regression (MLR), support vector regression (SVR), random forest, and XGBoost. The performance of each model was evaluated using the mean absolute percentage error (MAPE) and root-mean-square error (RMSE). The analysis results indicated that the AADT was the most influential variable affecting the asphalt layer thickness. Among the models, the MLR demonstrated the best predictive performance. While XGBoost had a relatively strong performance among the machine-learning techniques, the traditional statistical model, MLR, still outperformed it in certain regions. This study emphasized the need for customized pavement designs that reflect the traffic and environmental conditions specific to regional roads in Pakistan. This finding suggests that future research should incorporate additional variables and data for a more in-depth analysis.

This study aimed to evaluate the performance criteria of low-noise asphalt pavements under laboratory conditions. Laboratory tests were performed on eight porous and three non-porous asphalt mixtures. Draindown, Cantabro, tensile strength ratio (TSR), and dynamic stability tests were conducted to evaluate durability. The functionality was assessed using sound-absorption and indoorpermeability- coefficient tests. The laboratory results showed that all mixtures satisfied the quality standards for the draindown and TSR tests. In the dynamic stability test, all the mixtures demonstrated adequate rutting resistance. For porous mixtures, the Cantabro test results indicated sufficient shatter resistance and the indoor-permeability-coefficient test confirmed proper drainage performance. All mixtures exhibited satisfactory sound absorption, with the porous mixtures exhibiting slightly better sound absorption than the non-porous mixtures. Both porous and non-porous mixtures are durable and functional and are used in Korea. Future field tests are required to evaluate the noise reduction performance under different conditions and to compare the in-situ performance results with those from laboratory tests.

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.