In today’s rapidly changing business environment, rapid decision making and effective project management are essential for business growth. This study examines how project manager competencies and organizational structures affect business performance. Successful project execution depends on the strategic use of project managers’ skills and organizational resources to maximize performance. An empirical study was conducted with 475 participants from the construction and engineering sectors. The applied analyses included multiple regression analysis and two-way ANOVA to assess how project manager competencies and organizational types affect business performance. The results of the study show that project manager competencies significantly improve business performance, especially when combined with appropriate organizational types. Effective use of organizational frameworks leads to better financial results, increased market competitiveness, and greater innovation. The results of the study are as follows: First, project manager competencies were found to have a significant positive effect on business performance. Second, the use of functional, project, and matrix organizations had a significant positive effect on business performance. This suggests that aligning organizational structures with business objectives is important for achieving optimal performance. Overall, this study provides valuable insights into the academic literature and practical applications of project management and organizational research. In addition, if we can select organizational members based on the learning effects of previous projects when operating new projects in the future, it will help reduce risks. Ultimately, it will improve the project manager’s competency level, promote the individual abilities and knowledge sharing of team members, and provide opportunities for the company to build efficient new systems. This will be evaluated as a valuable study in terms of academic and practical productivity.

The purpose of this study is to present a plan for reducing noise between floors of apartment houses in Korea and to examine the method for evaluating noise blocking performance rating between floors. The definition of floor noise and classification method of floor noise can be described, and floor noise can be distinguished into lightweight impact sound and heavy impact sound. The wall-type structure, which is mainly adopted in domestic apartments, relatively transmits vibration caused by impact sources rather than using columns and beams, so noise problems between floors are relatively higher than systems using columns and beams. Three representative methods for reducing and blocking floor noise are described, and criteria for evaluating the effectiveness of floor noise reduction by each method are described. In addition, the method for noise reduction and blocking grades for each construction method currently applied in Korea was described, and as a result, it was judged that the domestic rating evaluation method was not suitable for the current domestic situation, and a new evaluation method and standard were needed.

High-rise buildings are equipped with TMD (Tuned Mass Damper), a vibration control device that ensure the stability and usability of the building. In this study, the seismic response control performance was evaluated by selecting the design variables of the TMD based on the installation location of the twisted irregular building. To this end, we selected analysis models of 60, 80, and 100 floors with a twist angle of 1 degree per floor, and performed time history analysis by applying historical seismic loads and resonant harmonic loads. The total mass ratio of TMDs was set to 1.0%, and the distributed installation locations of TMDs were selected through mode analysis. The analysis results showed that the top-floor displacement responses of all analysis models increased, but the maximum story drift ratio decreased. In order to secure the seismic response control performance by distributed installation of TMDs in twisted irregular buildings, it is judged that the mass ratio distribution of TMDs will act as a key variable.

Dynamic responses of nuclear power plant structure subjected to earthquake loads should be carefully investigated for safety. Because nuclear power plant structure are usually constructed by material of reinforced concrete, the aging deterioration of R.C. have no small effect on structural behavior of nuclear power plant structure. Therefore, aging deterioration of R.C. nuclear power plant structure should be considered for exact prediction of seismic responses of the structure. In this study, a machine learning model for seismic response prediction of nuclear power plant structure was developed by considering aging deterioration. The OPR-1000 was selected as an example structure for numerical simulation. The OPR-1000 was originally designated as the Korean Standard Nuclear Power Plant (KSNP), and was re-designated as the OPR-1000 in 2005 for foreign sales. 500 artificial ground motions were generated based on site characteristics of Korea. Elastic modulus, damping ratio, poisson’s ratio and density were selected to consider material property variation due to aging deterioration. Six machine learning algorithms such as, Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), eXtreme Gradient Boosting (XGBoost), were used t o construct seispic response prediction model. 13 intensity measures and 4 material properties were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks present good prediction performance considering aging deterioration.

Recent advances in computer technology have made it possible to solve numerous challenges but require faster hardware development. However, the size of the classical computer has reached its physical limit, and researchers' interest in quantum computers is growing, and it is being used in various engineering fields. However, research using quantum computing in structural engineering is very insufficient. Therefore, in this paper, the characteristics of qubits, the minimum unit of quantum information processing, were grafted with the crow search algorithm to propose QCSA (quantum crow search algorithm) and compare the convergence performance according to parameter changes. In addition, by performing the optimal design of the example truss structure, it was confirmed that quantum computing can be used in the architectural field.

The ocean is linked to long-term climate variability, but there are very few methods to assess the short-term performance of forecast models. This study analyzes the short-term prediction performance regarding ocean temperature and salinity of the Global Seasonal prediction system version 5 (GloSea5). GloSea5 is a historical climate re-creation (2001-2010) performed on the 1st, 9th, 17th, and 25th of each month. It comprises three ensembles. High-resolution hindcasts from the three ensembles were compared with the Array for Real-Time Geostrophic Oceanography (ARGO) float data for the period 2001-2010. The horizontal position was preprocessed to match the ARGO float data and the vertical layer to the GloSea5 data. The root mean square error (RMSE), Brier Score (BS), and Brier Skill Score (BSS) were calculated for short-term forecast periods with a lead-time of 10 days. The results show that sea surface temperature (SST) has a large RMSE in the western boundary current region in Pacific and Atlantic Oceans and Antarctic Circumpolar Current region, and sea surface salinity (SSS) has significant errors in the tropics with high precipitation, with both variables having the largest errors in the Atlantic. SST and SSS had larger errors during the fall for the NINO3.4 region and during the summer for the East Sea. Computing the BS and BSS for ocean temperature and salinity in the NINO3.4 region revealed that forecast skill decreases with increasing lead-time for SST, but not for SSS. The preprocessing of GloSea5 forecasts to match the ARGO float data applied in this study, and the evaluation methods for forecast models using the BS and BSS, could be applied to evaluate other forecast models and/or variables.

본 연구는 중국 기악연주 전공 대학생의 전공만족도와 전공선택 동기가 학습몰입과 연주성취도에 미치는 영향을 살펴보고자 하는데 목적이 있 다. 이를 위해 2024년 3월 20일부터 2024년 4월 10일까지 중국 산시성 지역에서 기악연주를 전공하고 있는 대학생 1,153명을 통해 설문지를 수 집하였다. 수집된 설문지는 SPSS 23.0 통계 프로그램을 사용하여 기술 통계 분석, 단일표본 t -검증, 일원 배치 분산분석, Pearson 상관분석 및 중다회귀분석을 수행하였다. 이를 통해 기악연주 전공 대학생의 전공만 족도를 높일 수 있는 다양한 교수법과 프로그램을 제공하는데 필요한 기 초정보를 제공하고자 한다. 또한 중국 기악연주 전공 대학생의 교육의 질을 보다 향상시킬 수 있는 바람직한 방향 제시에 필요한 기초자료를 제공하는데에도 도움을 주고자 한다.

PURPOSES : This study aims to establish a performance measure to evaluate metropolitan transit centers from the perspectives of transportation and urban planning. The developed performance measure indicates the effectiveness of the metropolitan transit center in urban areas, suggesting a policy for design and urban development. METHODS : This study assesses the functionality of a transit center using a linear equation. Seven indicators representing the key functions of the transit center are employed to determine the efficiency of current status. We analyzed four transit centers–Cheongnyangni, Hapjeong, Sadang, and Seoul Station–where transfer centers are proposed owing to high traffic volumes. The coefficients are determined using the weights obtained from an analytic hierarchy process (AHP) survey. RESULTS : Application of the weights from the AHP survey to the indicators of each transit center reveals that overall Seoul Station scored the highest, whereas Cheongnyangni Station scored the lowest. In particular, Seoul Station performed better than other stations in terms of accessibility and simplified coverage area index (SCAI). Although Sadang Station slightly outperformed Hapjeong Station with respect to the total score, the variance was due to Hapjeong Station excelling in urban indicators despite its lower transportation metrics. Cheongnyangni Station scored low on most indicators despite significant physical investments, except for congestion, transfer time and floor area ratio. CONCLUSIONS : The AHP survey identified accessibility and SCAI as the most heavily weighted transportation-related indicators, while the floor area ratio, an urban development indicator, was the least weighted. Seoul Station, which excelled in accessibility and SCAI had the highest total score among the sites studied. However, locations with poorer transportation metrics but superior urban indicators can still function effectively as integrated metropolitan transit centers.

본 연구는 기업의 사회적 책임(CSR)에 대한 중요성에 주목하고, 국내에 진출해 있는 다국적기업들의 종사자들이 소속 회사의 CSR 활동에 대해 어떻게 인식하고 있는지, 그것이 조직성과에 어떻게 영향을 미치는지를 분석하였다. 본 연구는 국내에서 영업활동을 하고 있는 주요 해외기업(미국, 유럽, 중국, 일본)들의 CSR 활동 현황에 대한 조 직 구성원들의 인식이 컨페션적인 감정을 통해 유발되는 심층행동과 경영성과에 미치는 영향을 고찰하였고 조직 내부의 구성원들 간에 형성된 “관계(關係)”가 컴페션과 심층행동에 미치는 영향과 조절효과를 검토하였다. 연구결과 는 소속 회사의 CSR에 대한 인식이 높은 것으로 평가되는 조직일수록 구성원들의 컴페션적인 감정이 더 강하게 유발된다. 조직 구성원들 간에 컴페션적인 행위를 서로 많이 주고받을수록 그들의 심층행동이 강화된다. 조직 구성 원들의 강화된 심층행동은 그들이 속한 기업의 조직성과에 긍정적인 영향을 미치는 것으로 평가되었다. 조직 구성 원들 간의 우호적인 관계는 컴페션과 심층행동을 긍정적인 방향으로 조절하는 효과가 있는 것으로 추정된다.

PURPOSES : This study aimed to evaluate the performance of carbon-reduced asphalt mixtures based on asphalt binder and asphalt mixture tests. METHODS : A carbon-reducing asphalt additive was developed, and samples were prepared by mixing the additive(0.85%, 1.35%, and 1.85%) with virgin asphalt binder to measure changes in the asphalt’s physical properties based on the content of the developed additive. The basic physical properties the penetration, softening point, ductility, and rotational viscosity and performance grade of the samples were measured, and the optimal content of the additive was determined to be 1.35%. An asphalt mixture was produced using the optimal additive content of 1.35%, and stability, indirect tensile strength, tensile strength ratio(TSR), and dynamic stability tests were conducted to compare its performance with that of hot mixed asphalt(HMA). Additionally, a dynamic modulus test that could simulate various loading conditions was conducted. Fuel consumption and CO2 emission were measured at the plant. RESULTS : The developed additive had the effect of reducing the viscosity of the binder while maintaining properties similar to those of the base binder when used at the selected content. The mixture test confirmed that the physical properties related to strength tended to decrease slightly when the additive were applied; however, all specifications were satisfied. In the dynamic modulus test, the results were confirmed to be similar to those of HMA. The fuel consumption and CO2 emission were reduced by 25-30%. CONCLUSIONS : Evidently, asphalt mixtures with carbon-reducing additives can perform at a level equivalent to that of HMA. To bolster this conclusion, it is necessary to track the long-term performance of low-carbon asphalt mixtures on pilot roads.

FRP 복합재료 중 CFRP(탄소 섬유 강화 플라스틱)는 현재 RC 구조물의 내부 및 외부 보강재로서 그리드 형태로 활용되고 있다. 그러나 CFRP 그리드에 대한 성능평가 기준은 매우 미흡하여 FRP 보강근 기준을 사용하고 있다. 따라서 본 연구에서는 그리드 가닥 수와 경계조건과 변수를 고려하여 CFRP 그리드의 인장 성능을 평가하기 위한 실험이 수행되었다. 가닥 수는 1, 2, 3가닥에 대한 인장시험이 수행되었으며, 경계조건의 경우 모르타르, 에폭시, 에폭시 + 모르타르로 변수를 지정하였다. 인장시험을 통하여 최적 가닥 수 및 최적 경계조건으로 개발한 시편을 토대로 고온 노출 시간에 따라 CFRP 그리드의 인장 성능 평가가 수행되었다. 온도는 130°C 로 유지되었으며, 5개의 시편을 각각 70분(Case 2), 100분(Case 3), 120분(Case 4), 150분(Case 5) 고온에 노출하여 비 고온 노출 시편 과 비교하였다. 실험 결과, 비 고온 노출 시편과 비교하여 Case 5에서는 인장강도와 탄성계수가 각각 최대 51.32% 및 44.4% 감소한 것으로 나타났다.

현대 건설산업 분야에서 철근콘크리트는 반영구적인 재료로 인식되어 가장 많이 사용되고 있다. 하지만 콘크리트의 노후화 및 수분 용해 현상 등으로 생긴 균열을 통해 강재의 부식이 발생하게 된다. 이러한 부식은 철근콘크리트의 거동과 구조물의 내구성을 저하시키기 때문에 근본적인 원인인 강재를 대체할 필요가 있다. 최근 건설산업에서 복합재료는 높은 강도, 낮은 중량, 부식에 대한 우 려가 없어 주목받고 있는 재료이다. 복합재료는 섬유와 기지재료로 사용되는 수지에 따라 재료의 특성이 달라지게 되며 이중 탄소섬유 를 활용한 복합재료 CFRP은 복합재료 중 가장 뛰어난 성능을 보여준다. 따라서 본 연구에서는 뛰어난 성능을 보여주는 CFRP와 경제 성을 고려하여 탄소섬유와 유리섬유를 혼합한 CFRP Hybrid를 사용하여 강재의 대체품으로 사용가능성을 확인하고자 한다. 재료의 특 성을 비교하기 위하여 ASTM 규정에 따라 인장시험과 압축시험을 수행하고 반복하중에 대한 저항을 확인하기 위하여 인장반복시험과 압축반복시험을 수행한다. 이때 측정된 응력, 영구변형 등을 그래프로 도식화하고 강재와 비교분석을 진행하였다.

Existing reinforced concrete (RC) building frames constructed before the seismic design was applied have seismically deficient structural details, and buildings with such structural details show brittle behavior that is destroyed early due to low shear performance. Various reinforcement systems, such as fiber-reinforced polymer (FRP) jacketing systems, are being studied to reinforce the seismically deficient RC frames. Due to the step-by-step modeling and interpretation process, existing seismic performance assessment and reinforcement design of buildings consume an enormous amount of workforce and time. Various machine learning (ML) models were developed using input and output datasets for seismic loads and reinforcement details built through the finite element (FE) model developed in previous studies to overcome these shortcomings. To assess the performance of the seismic performance prediction models developed in this study, the mean squared error (MSE), R-square (R2), and residual of each model were compared. Overall, the applied ML was found to rapidly and effectively predict the seismic performance of buildings according to changes in load and reinforcement details without overfitting. In addition, the best-fit model for each seismic performance class was selected by analyzing the performance by class of the ML models.

For low-rise piloti-type buildings that suffered significant damage in the Pohang earthquake, the seismic performance of those designed by codes issued before and after the earthquake has been recently revised. This study started with the expectation that many of the requirements presented in the current codes may be excessive, and among them, the spacing of column stirrup could be relaxed. In particular, the recently revised design code of concrete structures for buildings, KDS 41 20 00, suggests that the column stirrup spacing is 1/2 of the minimum cross-sectional size or 200 mm, which is strengthened compared to KBC 2016, but relaxed than the current KDS, 41 17 00, which is 1/4 of the minimum size or 150 mm. As a result of the study, it was found that the target performance level was sufficiently satisfied by following the current standards and that it could be satisfied even if the relaxed spacing was followed. Therefore, the strict column stirrup spacing of KDS 41 17 00 could be relaxed if a wall other than core walls is recommended in the current guideline for the structural design of piloti-type buildings.

The arrival of the 5G era has made electromagnetic pollution a problem that needs to be addressed, and flexible carbon-based materials have become a good choice. In this study, wet continuous papermaking technology was used to prepare carbon fiber paper (CFP) with a three-dimensional conductive skeleton network; Molybdenum disulfide ( MOS2)/ iron (Fe) @ carbon fiber paper-based shielding material was prepared by impregnating and blending molybdenum disulfide/iron ( MOS2/Fe) phenolic resin MOS2/ Fe@ CFP. The morphology, structure, electrical conductivity, mechanical properties, hydrophobicity, and electromagnetic shielding properties of the composite were characterized. The results show that the three-dimensional network structure based on a short carbon fiber paper-based conductive skeleton and the synergistic effect of the MOS2 dielectric wave absorbing agent and Fe magnetic wave absorbing agent have good electromagnetic shielding performance. Conduct electromagnetic shielding simulation using HFSS software to provide options for the structural design of CFP. The electromagnetic shielding performance of CFP reaches 70 dB, and the tensile strength reaches 34.39 MPa. Based on the mechanical properties, the compactness of carbon fiber paper is ensured. The lightning damage model test using CST software expands the direction for the use of carbon fiber paper. In summary, MOS2/ Fe @CFP with excellent shielding performance has great application prospects in thinner and lighter shielding materials, as well as high sensitivity, defense and military equipment.

Graphene-modified melamine sponges (RGO-MSs) were prepared, as adsorbents with photothermal conversion ability, utilizing solar energy to achieve heavy oil temperature rise, viscosity reduction, and efficient adsorption recovery of highly viscous oil. The RGO-MSs were prepared through a simple impregnation method. The photothermal performance and heavy oil adsorption performances of RGO-MSs with different densities and thicknesses were observed. It was found that as the density increases, the thermal conductivity of RGO-MS increases too, leading to the increase of the average oil absorption rate. The reduction of thickness is beneficial to improving of the adsorption rate. The prepared RGO-MS with a density of 21.5 mg/cm−3 and a height of 1 cm (RGO-MS-3-1) shows excellent mechanical properties and fatigue resistance. Cyclic adsorption–desorption of RGO-MS-3-1 was achieved through extrusion/ ethanol washing. After 10 cycles of reuse through extrusion, the adsorption capacity decreased from 52.90 to 50.02 g g− 1, with a loss of 5.4%. The material was then washed with petroleum ether and ethanol in turn. Its adsorption capacity can restored to 98.8% of the initial value, showing a promising application prospect on heavy oil leakage treatment. The easily prepared RGO-MS exhibits excellent light absorption and photothermal oil adsorption properties, providing a good solution for the problem of heavy oil leakage at sea.