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.

This study identifies the possibility of alignment discrepancies during mortar firing when using inactive fuzes, which make it impossible to visually observe impact points. To address this issue, we studied a quality assurance method for Sight Alignment after firing. To establish a baseline, we analyzed the pre-firing Sight Alignment and the impact group status during firing for 00 mortars and 000 shells. Based on this analysis, we derived the alignment position information range after firing for 36 mortars, distinguishing between 68% and 95% confidence interval. Finally, considering data characteristics, inspection time requirements, and non-conforming data, we selected the Sight Alignment range after firing based on the 95% confidence interval. This study is expected to contribute to the development of quality assurance methods for munitions by serving as an example of quality assurance in the mass production stage of mortars.

This study is to deal with a failure phenomenon that occurred during a vibration test on an Inertial Navigation System mounted on a self-propelled howitzer. Vibration occurs naturally due to the operation characteristics of self-propelled howitzers, The study describes a case of failure that occurred during the durability verification process. It explains the function and configuration of the INS(Inertial Navigation System) and describe how the failure occurred through understanding the phenomenon. Based on the occurrence phenomenon, an in-depth cause analysis was conducted and fundamental improvement measures were presented to prevent recurrence. It is expected that this study will aid as a reference for problem solving when similar failures occur in the future.

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.

In this paper, the cause of mortar baseplate breakage was analyzed by diving into cross-section, material, process, and design aspects. As a result of observing the fracture surface and non-fracture suface using optical equipment, it was possible to confirm changes in the shape of disconnected line and metal surface at a specific area. In addition, a number of linear defects due to overlap were found. Flow analysis was performed using the Deform program to verify changes during the production process. According to the result, a drop test was performed on each of the lap detection baseplate, undetection baseplate, and removed product to verify the presumptive cause of the rupture of the poplite.

Advancements in technology for large aircraft have led to the development of new materials for aviation. Traditional alloy-based components in aircraft, once prevalent, are now being replaced by composite materials that offer superior performance in terms of strength and operational limits. Notably, propellers have evolved from wood to composite materials, finding application in contemporary small aircraft. In this context, there is a need for research on the composite propellers of the 3-blade "W Company," based on the widely used Rotax 914 engine in South Korea. This study aims to investigate the changes in noise and thrust corresponding to variations in propeller blade angles and engine RPM, with the goal of selecting the optimal propeller pitch angle. Particularly, the "W Company's" propellers are durable and cost-effective, widely adopted in domestic aircraft. The research seeks to propose an effective method to minimize noise while maintaining the necessary thrust, contributing to the smooth operation of aircraft and promoting coexistence with local communities.

PURPOSES : The aim of this study is to develop a road fog information system based on the geostationary meteorological satellite (GK2A) for road weather services on highways. METHODS : Three threshold values sensitive to fog intensity in the GK2A fog algorithm were optimized using multi-class receiver operating characteristic analysis to produce road fog information depending on day and night. The developed a GK2A road fog algorithm that can detect three levels of road fog based on the visibility distance criteria (1km, 500m, and 200m). Furthermore, the GK2A road fog product was not only substituted with visibility objective analysis data in unknown and cloud-covered areas of satellite data, but also integrated with visibility distance data obtained from visibility gauges and CCTV image analysis to improve the accuracy of road fog information. RESULTS : The developed road fog algorithm based on meteorological satellite data provides real-time road fog information categorized into three levels (attention, caution, and danger) based on the visibility distance, with a spatial resolution of 1km × 1km and temporal resolution of 5 minutes. The road fog algorithm successfully detected road fog in five out of seven fog-related traffic accidents reported by Korean media outlets from 2020 to 2022, resulting in a detection success rate of 71.4%. The Korea Meteorological Administration is currently in the process of installing additional visibility gauges on 26 highways until 2025, and the next high-resolution meteorological satellite (GK5) is planned to be launched in 2031. We look forward to significantly improving the accuracy of the road fog hazard information service in the near future. CONCLUSIONS : The road fog information test service was initiated on the middle inner highway on July 27, 2023, and this service is accessible to all T-map and Kakao-map users through car navigation systems free of charge. After 2025, all drivers on the 26 Korean highways will have access to real-time road fog information services through their navigation systems.

Machine learning is widely applied to various engineering fields. In structural engineering area, machine learning is generally used to predict structural responses of building structures. The aging deterioration of reinforced concrete structure affects its structural behavior. Therefore, the aging deterioration of R.C. structure should be consider to exactly predict seismic responses of the structure. In this study, the machine learning based seismic response prediction model was developed. To this end, four machine learning algorithms were employed and prediction performance of each algorithm was compared. A 3-story coupled shear wall structure was selected as an example structure for numerical simulation. Artificial ground motions were generated based on domestic site characteristics. Elastic modulus, damping ratio and density were changed to considering concrete degradation due to chloride penetration and carbonation, etc. Various intensity measures 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 and extreme gradient boosting algorithms present good prediction performance.

Since atypical high-rise buildings are vulnerable to gravity loads and seismic loads, various structural systems must be applied to ensure the stability of the structure. In this study, the authors selected a 60-story twisted-shaped structure among atypical high-rise structures as an analytical model to investigate its structural behavior concerning the outrigger system. The structural analyses were performed varying the number of installed layers and the arrangement of the outrigger system, as well as the placement of the mega column, as design variables. The analysis revealed that the most effective position for the outrigger was 0.455H from the top layer, consistent with previous studies. Additionally, connecting outriggers and mega columns significantly reduced the displacement response of the model. From an economic standpoint, it is deemed efficient to connect and install outriggers and mega columns at the structure's ends.

본 연구에서는 경기도 내 유통 중인 간편조리세트 55건 내 농·축·수산물 원재료의 미생물 오염도를 조사하였다. 55 건의 간편조리세트 중 농산물이 원재료로 들어가는 제품 은 48건, 축산물이 원재료로 들어가는 제품은 43건, 수산 물이 원재료로 들어가는 제품은 16건이었다. 농·축·수산물 에서 일반세균은 100%의 검출률을 보였으며, 일반세균 평균 검출량은 농산물 6.57 log CFU/g, 축산물 4.60 log CFU/g, 수 산물 5.47 log CFU/g으로 나타났다. 농·축·수산물에서 대 장균군은 각각 81.25%, 69.77%, 43.75%의 검출률을 보였 고, 대장균군 평균 검출량은 농산물 2.83 log CFU/g, 축산 물 1.34 log CFU/g, 수산물 1.12 log CFU/g으로 나타났다. 대 장균은 13건(30.23%)의 축산물에서 0.70-2.36 log CFU/g 범위로 검출된 반면, 수산물에서는 1건(6.25%)만 검출되 었고, 농산물에서는 검출되지 않았다. 농·축·수산물에서 진 균은 각각 97.92%, 93.02%, 93.75%의 검출률을 보였고, 진균 평균 검출량은 농산물 3.82 log CFU/g, 축산물 2.92 log CFU/g, 수산물 2.82 log CFU/g으로 나타났다. 농·축· 수산물에서 식중독균은 각각 35.42%, 37.21%, 31.25%의 분리율을 보였고, 바실루스 세레우스, 살모넬라균 등 7종 의 45개 식중독균을 분리하였다. 간편조리세트로 인한 식 중독 사고 예방을 위하여 세척, 충분한 가열 섭취 및 조 리과정 중 교차오염에 대한 주의가 필요하다.

In this study, we investigated the dynamic characteristics of three irregular building models to analyze the effectiveness of displacement response control with Tuned Mass Damper (TMD) installation in twisted irregular buildings. The three irregular models were developed with a fixed angle of twist per story at one degree, subjected to three historical seismic loads and resonant harmonic loads. By designing TMDs with linear and dashpot attributes, we varied the total mass ratio of the installed TMDs from 0.00625% to 1.0%, encompassing a total of 10 values. Two TMDs were installed at the center of the top story of the analysis model in both X and Y directions to evaluate displacement response control performance based on TMD installation. Our findings suggest that the top displacement response control performance was most effective when a 1.0% TMD was installed at the top layer of the analysis model.

In this study, an experimental analysis of noise reduction in road traffic by applying the Micro Grooving technique to concrete highway pavements is explored. Initiated in 1984 to address the aging and damage issues observed in South Korea's concrete highways, Micro Grooving is known for creating fine grooves on the cement pavement surface to increase friction, prevent hydroplaning, and inhibit ice formation, while reducing vehicle friction noise by 3∼5dB(A). It is determined from noise measurement results that the application of the Micro Grooving method can be expected to reduce roadside noise and enhance the safety of drivers' driving experience.

This paper proposes the armored combat bulldozer, essential for amphibious tasks, requires water ingress prevention and submersion capabilities, typically addressed by a centrifugal pump. This study aims to boost the bulldozer's drainage pump efficiency by replacing the traditional aluminum 3-blade impeller with one made of ASA material using 3D printing. Analysis via ANSYS Fluent revealed that the 5-blade impeller increased discharge volume by 19.31% and efficiency by 6.07%, while the 6-blade variant saw a 27.07% increase in discharge volume and 8.81% efficiency improvement. Further scrutiny with ANSYS Static Structure ensured the new impellers' structural integrity and robustness under extreme conditions. This research confirms the potential of 3D printing in enhancing military equipment, demonstrating significant improvements in pump performance and opening paths for advanced manufacturing techniques to meet the demanding needs of combat vehicles.

Numerous factors contribute to the deterioration of reinforced concrete structures. Elevated temperatures significantly alter the composition of the concrete ingredients, consequently diminishing the concrete's strength properties. With the escalation of global CO2 levels, the carbonation of concrete structures has emerged as a critical challenge, substantially affecting concrete durability research. Assessing and predicting concrete degradation due to thermal effects and carbonation are crucial yet intricate tasks. To address this, multiple prediction models for concrete carbonation and compressive strength under thermal impact have been developed. This study employs seven machine learning algorithms—specifically, multiple linear regression, decision trees, random forest, support vector machines, k-nearest neighbors, artificial neural networks, and extreme gradient boosting algorithms—to formulate predictive models for concrete carbonation and thermal impact. Two distinct datasets, derived from reported experimental studies, were utilized for training these predictive models. Performance evaluation relied on 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 analytical outcomes demonstrate that neural networks and extreme gradient boosting algorithms outshine the remaining five machine learning approaches, showcasing outstanding predictive performance for concrete carbonation and thermal effect modeling.

In this study, the seismic response characteristics of the three analysis model with or without TMD were investigated to find out the effective dome shape. The three analysis models are rib type, lattice type and geodesic type dome structure composed of space frame. The maximum vertical and horizontal displacements were evaluated at 1/4 point of the span by applying the resonance harmonic load and historical earthquake loads (El Centro, Kobe, Northridge earthquakes). The study of the effective TMD installation position for the dome structure shows that seismic response control was effective when eight TMDs were installed in all types of analysis model. The investigation of the efficiency of TMD according to dome shape presents that lattice dome and geodesic dome show excellent control performance, while rib dome shows different control performance depending on the historical seismic loads. Therefore, lattice and geodesic types are desirable for seismic response reduction using TMD compared to rib type.

Raman distributed temperature sensor can be used as temperature instruments as well as monitoring abnormalities in next-generation nuclear systems. Since noise reduction and Measuring Frequency enhancement are required, integration time adjustment has been mainly used so far. In this study, a new data processing method using Moving Average Filter was analyzed to see if noise reduction and Measuring Frequency could be reduced, and improvement measures were suggested.

This paper is a study on the malfunction that occurred during the power supply logic of the Gunner Display Device during Mortar Functional Firing under low temperature conditions. As a result of the phenomenon reproduction test and its analysis, the cause of the malfunction of the Gunner Display Device was Glitch, which occurred in the process of converting the image signal, and the improved software was applied to the Gunner's Display System by ignoring some of the image signal conversion process that causes Glitch. The improved Gunner Display Device passed the validity test and applied the improvement to the mortars. As a result of this study, several suggestions for power supply and control logic were proposed. It is expected that this study will be used as a reference in the future design of similar weapons systems.