In this study, we performed thermal safety design of the electric module of a heat-loaded equipment with consideration of its heat dissipation performance. Initially, we calculated the heat dissipation of natural convection to choose a cooling method. Based on this, we found that some modules required forced convection and selected an air-cooling method with an outdoor temperature of 43 degrees Celsius, which is the maximum temperature in Korea. Prior to module production, we performed thermal analysis of each module and proceeded with a design to increase the thermal conductivity of the module as a primary step, and subsequently proceeded with Heat Sink design to maximize the heat dissipation performance. After considering various constraints according to the system requirements and designing the cooling path, we experimentally and analytically secured thermal safety at the operating temperature of the equipment.

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 : In this study, the alkali aggregate reactivity and expansion characteristics of mortar mixed with waste glass (a recycled aggregate) were confirmed to verify the alkali-silica reaction (ASR) stability and review the appropriateness of the alkali aggregate reactivity test method following the replacement of recycled aggregate. METHODS : The alkali-aggregate reactivity of waste glass aggregates was measured using the chemical and physical methods described in KS F 2545 and ASTM C 1260, respectively. The reactivity was classified by comparing the results. Cement with a high-alkali content was used to simulate an environment that can induce ASR. Non-reactive fine aggregates, waste glass fine aggregates, reactive general aggregates, and Ferronickel slag aggregates were used as control groups. RESULTS : Waste glass fine aggregates were classified as reactive when applying the chemical method. In the physical method, they were classified as reactive at 100% and latent reactive at 1%, based on the mixing ratio. Additionally, we discovered that the reliability of the chemical method was low since the ASR of the aggregates was classified differently based on the evaluation method, while the results of the chemical and physical test methods were inconsistent. CONCLUSIONS : To determine the alkali reactivity of recycled aggregates, the complex use of chemical and physical methods and analysis based on the mixing ratio of the reactive aggregates are required. Small amounts of waste glass aggregate replacements affected the ASR. Because ASR reaction products can affect the long-term thermal expansion of the structure, further research is needed to use ASR aggregates in structures.

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.

PURPOSES : The purpose of this study is to confirm the thermal expansion characteristics of concrete mixed with 1% waste glass fine aggregates, which is the amount stipulated for recycled aggregates in the current quality standard. METHODS : The coefficient of thermal expansion was measured by applying AASHTOT 336-10 using a LVDT. The results measured were used as physical properties in a finite element analysis to confirm the change in tensile stress and the displacement of the right angle section of the upper slab of a concrete pavement due to admixture substitution. RESULTS : The thermal expansion coefficients of concrete based on the replacement rate of the admixture when the waste glass fine aggregates are replaced are within the range of the thermal expansion coefficients of concrete specified in the Federal Highway Administration report. As the replacement rate of the admixture increases, the thermal expansion coefficient of concrete decreases. As the thermal expansion coefficient decreases, the slab pavement curling displacement and the tensile stress of the center of the upper slab of concrete decrease. CONCLUSIONS : In the short term, the presence or absence of waste glass fine aggregates does not significantly affect the thermal expansion coefficient of concrete. However, in the long term, waste glass fine aggregates are reactive aggregates that causes ASR, which creates an expandable gel around the aggregates and results in concrete expansion. Therefore, the relationship between ASR and the thermal expansion coefficient must be analyzed in future studies.

PURPOSES : In this study, surface distress (SD), rutting depth (RD), and international roughness index (IRI) prediction models are developed based on the zones of Incheon and road classes using regression analysis. Regression analysis is conducted based on a correlation analysis between the pavement performance and influencing factors. METHODS : First, Incheon was categorized by zone such as industrial, port, and residential areas, and the roads were categorized into major and sub-major roads. A weather station triangle network for Incheon was developed using the Delaunay triangulation based on the position of the weather station to match the road sections in Incheon and environmental factors. The influencing factors of the road sections were matched Based on the developed triangular network. Meanwhile, based on the matched influencing factors, a model of the current performance of the road pavement in Incheon was developed by performing multiple regression analysis. Sensitivity analysis was conducted using the developed model to determine the influencing factor that affected each performance factor the most significantly. RESULTS : For the SD model, frost days, daily temperature range, rainy days, tropical nights, and minimum temperatures are used as independent variables. Meanwhile, the truck ratio, freeze–thaw days, precipitation days, annual temperature range, and average temperatures are used for the RD model. For the IRI model, the maximum temperature, freeze–thaw days, average temperature, annual precipitation, and wet days are used. Results from the sensitivity analysis show that frost days for the SD model, precipitation days and freeze–thaw days for the RD model, and wet days for the IRI model impose the most significant effects. CONCLUSIONS : We developed a road pavement performance prediction model using multiple regression analysis based on zones in Incheon and road classes. The developed model allows the influencing factors and circumstances to be predicted, thus facilitating road management.

재생에너지의 보급과 기후변화를 대응하기 위한 해결책으로 수소에너지에 대한 관심이 늘어나고 있다. 수소는 미 이용 전력을 대용량 장주기로 저장하기에 가장 적합한 수단이며 이러한 수소를 생산하는 기술 중 수전해는 물에 전기에너지 를 인가하여 수소를 생산하는 친환경적 수소생산 기술로 알려져 있다. 수전해의 구성 요소 중 분리막은 음극과 양극을 물리 적으로 분리할 뿐만 아니라 생성되는 수소와 산소의 섞임 현상을 방지하며 이온의 전달을 가능하게 하는 복합적인 역할을 수 행한다. 특히 기존의 수전해 기술들의 단점을 보완할 수 있는 차세대 음이온 교환막 수전해에서의 핵심은 우수한 음이온 교 환막을 확보하는 것이다. 높은 이온 전도성과 알칼리 환경에서 우수한 내구성을 동시에 가지려는 많은 연구들이 진행되고 있 으며 다양한 소재에 대한 탐색이 이루어지고 있다. 본 총설에서는 상용 블록 공중합체인 Polystyrene-b-poly(ethylene- co-butylene)-b-polystyrene (SEBS)를 기반으로 하는 음이온 교환막에 대한 연구에 대해 살펴보며 최신 연구 동향과 앞으 로 나아가야할 점에 대해 논하고자 한다.

Most of the prior studies on the servitization of manufacturing companies have been actively studied, focusing on the performance and cases of servitization at the single company level. According to the results, most of the servitization at the single company level has been expanded based on the relevance of the company’s core products. However, the form of companies that form a large axis of the Korean economy is a large-scale business group, and these business groups incorporate service affiliates for various purposes, so they show different characteristics from that of a single corporate. In addition, since the purpose of forming a business group is different for each business group, the service relevance between affiliates within the business group is different. Therefore, this study aims to examine the effect of service relevance between affiliates within a business group on the management performance of each business group. To this end, an empirical analysis will be conducted using panel data for 10 years from 2011 to 2020 for a total of 98 affiliates listed on KOSPI and KOSDAQ of 9 domestic business groups. Based on these results, the direction for improving management performance and establishing future servitization strategies for large business groups in Korea will be expected to be made.

본고는 이형기 시에 나타난 멜랑콜리의 특성을 해명하려고 한다. 멜랑콜리는 현대시를 이해하는 중요한 철학적 개념이다. 멜랑콜리는 대상 상실에서 자아 상실로 변화하며 드러난다. 대표적인 증상으로는 ‘자애 심의 추락’을 들 수 있다. 멜랑콜리는 부정적인 정신병리의 결과가 아니라 긍정적인 감정의 발산이며 문학의 새로운 방법론이다. 이형기의 시에 나타난 멜랑콜리는 사회학적 토대 위에서 발현된 자기부정과 문명비판이 수합되어 있다. 이형기는 문명의 발달로 인한 인간성의 상실과 공동체의 붕괴가 일어난 시기에 주로 활동하였다. 이형기의 시는 문명을 통해 경험한 상실의 멜랑콜리, 극복과 포용의 세계로 나아가기 위한 영웅적 멜랑콜리의 양상을 드러낸다. 상실의 멜랑콜리는 죽음으로부터 새로움을 발견하는 영웅적 멜랑콜리를 통해 변증법적 인식으로 나아간다. 이형기 시세계를 멜랑콜리를 통해 분석하는 것은 새로운 방법론이다. 이를 통해 이형기 시세계의 해석 지평을 넓히는 계기가 되고자 한다.

PURPOSES : The objective of this study is to develop regression models for surface distress (SD), rut depth (RD), and international roughness index (IRI) of Jeju Island local road by analyzing the correlations between the pavement performance and its influencing factors. METHODS : First, the differences between pavements in inland Korea and Jeju Island in terms of performance and influencing factors were investigated. Influencing factors were assigned to pavement sections on Jeju Island using the inverse distance weighting method, and the correlations between the pavement performance and influencing factors were analyzed. As a result, maximum temperature, heat wave days, annual temperature range, precipitation days, precipitation intensity, ESAL, etc. were determined as independent variables for the pavement performance prediction models. Multiple regression analysis was performed to develop the pavement performance models using the selected independent variables. RESULTS : The RD, maximum temperature, and precipitation days were determined to be the independent variables for the SD predictive model. The SD, maximum temperature, annual temperature range, heat wave days, and precipitation days were selected as independent variables of the RD prediction model. In addition, the RD, annual temperature range, heat wave days, precipitation days, and ESAL were selected as independent variables for the IRI prediction model. CONCLUSIONS : As a result of the study, an actual forecast model for SD, RD, and IRI was developed. Based on this model, it is possible to estimate the predictive value of the missing performance data in the studied interval. If the factors affecting performance are managed in terms of maintenance beyond a certain level, it can help those responsible for road maintenance to rationally select the maintenance method and timing.

PURPOSES : The surface distress of asphalt pavements is one of the major factors affecting the safety of road users. The aim of this study was to analyze the factors influencing the occurrence of surface distress and statistically predict its annual change to contribute to more reasonable asphalt pavement management using the data periodically collected by the national highway pavement data management system. METHODS : In this study, the factors that were expected to influence the surface distress were determined by reviewing the literature. The normality was secured by changing the forms of the variables to make the distribution of the variables got closer to normal distribution. In addition, min-max normalization was performed to minimize the effect of the unit and magnitude of the candidate independent variables on the dependent variable. The final candidate independent variables were determined by analyzing the correlation between the annual surface distress change and each candidate independent variable. In addition, a prediction model was developed by performing data grouping and multi-regression analysis. RESULTS : An annual surface distress change prediction model was developed using present surface distress, age, and below 0 ℃ days as the independent variables. As a result of sensitivity analysis, the surface distress affected the annual surface distress change the most. The positive correlation between the dependent variable and each independent variable demonstrated engineering and statistical meaningfulness of the prediction model. CONCLUSIONS : The surface distress in the future can be predicted by applying the annual surface distress prediction model to the national highway asphalt pavement sections with survey data. In addition, the prediction model can be applied to the national highway pavement condition index (NHPCI) evaluating the national highway asphalt pavement conditions to be used in the prediction of future NHPCI.

PURPOSES : In this study, a driving simulation testing equipment was developed to derive the optimal longitudinal tinting that can reduce the lateral vibration of the vehicle. Various types of longitudinal textures and tires were evaluated through simulation testing with the equipment. Based on the results, 3×3×16mm tinning as the optimal longitudinal texture was selected among 8 textures. METHODS : Based on the literature review, the causes of lateral vibration were analyzed, and parts and types for testing equipment development were reviewed. Driving simulation with testing equipment was conducted considering various textures and tires. To verify the test results, finite element analysis was performed under the similar conditions. And field test for two textures was conducted to find the optimal longitudinal texture. RESULTS : Based on the literature review, driving simulation test, finite element analysis and field test, longitudinal texture of 3×3×16mm is show the better performance compared to 7 textures. CONCLUSIONS : 3×3×16mm as longitudinal tinning for fresh concrete is show less lateral vibration than 3×3×12mm.