Unlike other facilities, maintaining processes is essential in industrial facilities. Pipe racks, which support pipes of various diameters, are important structures used in industrial facilities. Since the transport process of pipes directly affects the operation of industrial facilities, a fragility curve should be derived based on considering not only the pipe racks' structural safety but also the pipes' transport process. There are several studies where the fragility curves have been determined based on the structural behavior of pipe racks. However, few studies consider the damage criteria of pipes to ensure the transportation process, such as local buckling and tensile failure with surface defects. In this study, an analysis model of a typical straight pipe rack used in domestic industrial facilities is constructed, and incremental dynamic analysis using nonlinear response history analysis is performed to estimate the parameters of the fragility curve by the maximum likelihood estimation. In addition, the pipe rack's structural behavior and the pipe's damage criteria are considered the limit state for the fragility curve. The limit states considered in this paper to evaluate fragility curves are more reasonable to ensure the transportation process of the pipe systems.

The demand for high-strength steel is rising due to its economic efficiency. Low-cycle fatigue (LCF) tests have been conducted to investigate the nonlinear behaviors of high-strength steel. Accurate material models must be used to obtain reliable results on seismic performance evaluation using numerical analyses. This study uses the combined hardening model to simulate the LCF behavior of high-strength steel. However, it is challenging and complex to determine material model parameters for specific high-strength steel because a highly nonlinear equation is used in the model, and several parameters need to be resolved. This study used the particle swarm algorithm (PSO) to determine the model parameters based on the LCF test data of HSA 650 steel. It is shown that the model with parameter values selected from the PSO accurately simulates the measured LCF curves.

The importance of Structural Health Monitoring (SHM) in the industry is increasing due to various loads, such as earthquakes and wind, having a significant impact on the performance of structures and equipment. Estimating responses is crucial for the effective health management of these assets. However, using numerous sensors in facilities and equipment for response estimation causes economic challenges. Additionally, it could require a response from locations where sensors cannot be attached. Digital twin technology has garnered significant attention in the industry to address these challenges. This paper constructs a digital twin system utilizing the Long Short-Term Memory (LSTM) model to estimate responses in a pipe system under simultaneous seismic load and arbitrary loads. The performance of the data-driven digital twin system was verified through a comparative analysis of experimental data, demonstrating that the constructed digital twin system successfully estimated the responses.

Injection molding is a process of shaping resin materials by heating them to a temperature above their melting point and then using a mold. The resin material is injected into and cooled within the mold cavity, solidifying into the desired shape. The core and cavity components that make up the mold cavity are crucial elements for the precision molding in injection molding. In the case of precision mold production, the application of 5-axis machining technology is required to ensure high machining quality for complex shapes, and among these factors, the tool angle is a critical machining condition that determines the surface roughness of the workpiece. In this study, we aim to measure the surface roughness of the machined surface of KP4A specimens during machining processes with variations in the tool angle and analyze the correlation between the tool angle and surface roughness.

This study explores strategies to address the variability of heat energy using renewable energy and heat grids to achieve carbon neutrality. Renewable energy source introduce fluctuations that can impact the stability of power systems, while heat grids provide a systematic infrastructure for efficient supply of heat energy and power generation. Jeju Island is chosen as a case study, focusing on balance control based on groundwater-based geothermal energy to optimize the distribution of heat energy. The results demonstrate that the 3rd control method is the most effective in maintaining the target temperature in greenhouses, and specific temperature settings and objectives are proposed for each control method based on crop requirements. These research findings contribute to achieving carbon neutrality and reducing power consumption.

This paper proposes a standardized vehicle body repair manual for vehicles with major damage to the rear side members caused by rear-end collisions. The manual is used to refine the vehicles. Typical work involves replacing large traffic accident modes with new members or modifying and aligning existing members. If repairs are made for various reasons, the members should be attached based on the body of a new vehicle. Unlike new vehicle members, the accident vehicle repair process depends heavily on the operator's skilled skills (i.e., the performance, purpose, level, and quality of the body replacement work due to the nature of the vehicle body replacement work). When repairing or replacing a rear side member of a body repair, three methods of operation are applied because the damage and deformation vary depending on the object of the other party, although the degree of damage varies. There is no standardized manual for side member over-hole replacement, partial replacement, or partial modification, since these repair methods vary depending on the operator's thoughts and angle of view. Therefore, customers should use standardized vehicle repair manuals to ensure that their vehicle receives the same repair when damaged. This study is expected to develop a standardized vehicle repair manual to reduce the drop in used market prices after replacement or repair of rear side members at vehicle repair plants.

The need for lightweight yet strong materials is being demanded in all industries. Carbon fiber-reinforced plastic is a material with increased strength by attaching carbon fiber to plastic, and is widely used in the aerospace industry, ships, automobiles, and civil engineering based on its low density. Carbon-reinforced fiber plastic is a material widely used in parts and manufactured products, and structural analysis simulation is required during design, and application of actual material properties is necessary for accurate structural analysis simulation. In the case of carbon-reinforced fiber plastics, it is reported that there is a porosity of around 0.5% to 6%, and it is necessary to check the change in material properties according to the porosity and pore shape. It was confirmed by applying the method. It was confirmed that the change in elastic modulus according to the porosity was 10.7% different from the base material when the porosity was 6.0%, and the Poisson's ratio was confirmed to be less than 3.0%. It was confirmed that the elliptical spherical pore derived different material properties from the spherical pore depending on the pore shape, and it was confirmed that the shape of the pore had to be confirmed to derive equivalent material properties.

2021년 7월 자치경찰제가 실시되면서, 지역 안전에 대한 관심이 고조 되었다. 지금까지 지역 안전은 전통적 의미의 치안 관점에서 접근하였으 나, 안전에 대한 여성의 두려움이 증가하면서, 지역에서의 안전이 더이상 치안의 차원에 머무를 수 없게 되었다. 그러나, 지역 안전을 확인할 수 있는 안전지표는 안전에 대한 취약성을 주로 측정하고 있어, 여성의 범 죄에 대한 두려움이나 예방적 차원의 지표는 포함되어 있지 않았다. 따 라서, 본 연구는 지역의 안전을 측정할 수 있는 새로운 안전지표의 구성 이 필요하며, 새로운 안전지표는 성인지적 관점의 적용으로부터 출발하 였다. 새로운 안전지표는 기존 안전이론과 함께 성인지 감수성 이론에 기반하여, 4개 영역 22개 지표를 구성하였다. 이 연구는 새로운 안전지 표를 개발하기 위한 것으로 지표가 적합한지를 탐색적으로 조사하였다. 이를 위해 성인지 전문가와 자치경찰 전문가를 대상으로 델파이 조사를 실시한 후 적합한 지표를 제시하였다. 조사 결과, 영역별 적합도는 높은 편이었고, 22개 세부 지표 가운데 14개 지표는 적합, 1개 지표는 부적 합, 7개 지표는 고려할 필요가 있는 것으로 나타났다. 이러한 결과는 향 후 자치경찰제 실시에 따른 지역 안전 지표를 구성하는 데 기여할 것으 로 기대할 수 있다.

This study aimed to assess and determine the optimal model for predicting the full bloom date of ‘Fuji’ apples across South Korea. We evaluated the performance of four distinct models: the Development Rate Model (DVR)1, DVR2, the Chill Days (CD) model, and a sequentially integrated approach that combined the Dynamic model (DM) and the Growing Degree Hours (GDH) model. The full bloom dates and air temperatures were collected over a three-year period from six orchards located in the major apple production regions of South Korea: Pocheon, Hwaseong, Geochang, Cheongsong, Gunwi, and Chungju. Among these models, the one that combined DM for calculating chilling accumulation and the GDH model for estimating heat accumulation in sequence demonstrated the most accurate predictive performance, in contrast to the CD model that exhibited the lowest predictive precision. Furthermore, the DVR1 model exhibited an underestimation error at orchard located in Hwaseong. It projected a faster progression of the full bloom dates than the actual observations. This area is characterized by minimal diurnal temperature ranges, where the daily minimum temperature is high and the daily maximum temperature is relatively low. Therefore, to achieve a comprehensive prediction of the blooming date of ‘Fuji’ apples across South Korea, it is recommended to integrate a DM model for calculating the necessary chilling accumulation to break dormancy with a GDH model for estimating the requisite heat accumulation for flowering after dormancy release. This results in a combined DM+GDH model recognized as the most effective approach. However, further data collection and evaluation from different regions are needed to further refine its accuracy and applicability.

한반도는 주변국의 안보정세 변화, 북한의 미사일 도발, 병역자원의 급 감, 민간 생활지역 확장으로 훈련장 부족 및 민원증가, 안전사고 등 많은 도전요인에 직면해 있다. 특히 군사대비태세의 근간이라 할 수 교육훈련을 위한 여건은 매우 심각한 수준이다. 이를 극복하기 위해 국방 분야에서는 4차산업혁명 기술을 적용한 LVCG 과학화 훈련체계를 구축하여 추진하고 있다. LVCG 과학화 훈련은 Live 체계(실기동훈련, KCTC), Virtual 체계 (가상현실), Constructive 체계(전투모의), Game 체계(게임) 등을 활용하 여 언제 어디서든지 실전과 같은 훈련 경험이 가능하며, 훈련 결과에 대한 데이터를 활용하여 객관적 평가가 가능하다. 따라서 AI, AR, VR 등 과학기 술의 발달을 기회요인으로 활용하여 체계별 성능을 개량하고 LVCG 체계 를 하나의 환경에서 운용할 수 있는 합성훈련환경(STE)을 구축하여 실전 과 같은 훈련이 되도록 해야 한다.

Determining the size or area of a plant's leaves is an important factor in predicting plant growth and improving the productivity of indoor farms. In this study, we developed a convolutional neural network (CNN)-based model to accurately predict the length and width of lettuce leaves using photographs of the leaves. A callback function was applied to overcome data limitations and overfitting problems, and K-fold cross-validation was used to improve the generalization ability of the model. In addition, ImageDataGenerator function was used to increase the diversity of training data through data augmentation. To compare model performance, we evaluated pre-trained models such as VGG16, Resnet152, and NASNetMobile. As a result, NASNetMobile showed the highest performance, especially in width prediction, with an R_squared value of 0.9436, and RMSE of 0.5659. In length prediction, the R_squared value was 0.9537, and RMSE of 0.8713. The optimized model adopted the NASNetMobile architecture, the RMSprop optimization tool, the MSE loss functions, and the ELU activation functions. The training time of the model averaged 73 minutes per Epoch, and it took the model an average of 0.29 seconds to process a single lettuce leaf photo. In this study, we developed a CNN-based model to predict the leaf length and leaf width of plants in indoor farms, which is expected to enable rapid and accurate assessment of plant growth status by simply taking images. It is also expected to contribute to increasing the productivity and resource efficiency of farms by taking appropriate agricultural measures such as adjusting nutrient solution in real time.

As aerial application increasing, with social concerning in pesticide drift rises, so this study attempts to establish a test bench that can repeatedly and continuously evaluate this. To this end, this study first analyze ISO 22866 and ASABE S561.1 among the international standard test methods related to pesticide fugitive evaluation. A test bench was established at the Naju practice field of Chonnam National University in accordance with international standards, and field tests were carried out (ISO 22866, ASABE S561.1) to verify effectiveness. A test bench that established in this study and a pesticide drift recovery protocol by aerial application can improve the experimental environment where field experiments were complex and it was difficult to achieve the same conditions. In addition, it will be possible to construct a database of pesticide drift that takes into account various factors that affect pesticide drift substances, which is expected to improve the reliability of the data, as well as quantitative evaluation of pesticide drift in the air.

High-strength low-alloy steel is one of the widely used materials in onshore and offshore plant engineering. We investigated the alloying effect of solute atoms in α-Fe based alloy using ab initio calculations. Empirical equations were used to establish the effect of alloying on the Vicker’s hardness, screw energy coefficient, and edge dislocation energy coefficient of the steel. Screw and edge energy coefficients were improved by the addition of V and Cr solute atoms. In addition, the addition of trace quantities of V, Cr, and Mn enhanced abrasion resistance. Solute atoms and contents with excellent mechanical properties were selected and their thermal conductivity and thermal expansion behavior were investigated. The addition of Cr atom is expected to form alloys with low thermal conductivity and thermal expansion coefficient. This study provides a better understanding of the state-of-the-art research in low-alloy steel and can be used to guide researchers to explore and develop α-Fe based alloys with improved properties, that can be fabricated in smart and cost-effective manners.

본 연구에서는 한옥의 해석모델 구축을 지원하고, 구축된 해석모델의 활용도를 높이고자 이를 활용한 가상현실 소프트웨어를 개발 하였다. 한옥의 구조해석 모델은 범용 구조해석 소프트웨어인 midas Gen으로 생성하고, 이를 문자기반 입력파일로 변환한 후 본 연구 에서 개발된 소프트웨어에서 한옥 해석모델의 검토에 필요한 자료들을 저장한다. 개발된 가상현실 소프트웨어 내에서 3차원으로 표 현된 한옥의 해석모델은 시점을 변경하며 살펴볼 수 있고 특정 부재를 선택하여 관련된 자료를 확인할 수 있다. 이러한 과정을 통해 해 석모델의 오류를 확인 및 수정하여 완결된 해석모델을 구축할 수 있다. 개발된 소프트웨어는 3개의 한옥 사례에 적용하여 그 적용성 과 효용성을 검증하였으며, 구조분야 이외의 타 분야에서도 활용될 수 있다.

현대의 방탄 장갑은 우수한 관통 저항성을 갖추어야할 뿐만 아니라 군인과 군용차량의 기동성이 확보되어야 하기 때문에 경량화가 중요한 개발 요소가 되었다. 이종 적층 평판 구조의 방탄 장갑의 방탄 성능은 동일 중량 대비 구성 재료의 배열에 따라 달라진다. 본 논 문에서는 케블라, 초고분자량 폴리에틸렌 그리고 에바 폼으로 구성된 방탄 장갑의 적층 배열에 따른 방탄 성능을 분석한다. 구성 재료 의 두께가 5mm와 6.5mm인 두 가지 경우에서 6가지 적층 배열에 대하여 7.62 × 51mm NATO 탄환의 M80 탄을 856m/s의 속도로 충돌 시키는 피탄 해석을 수행하였다. 방탄 성능을 평가하기 위해 이종 적층 평판을 관통한 발사체의 잔류 속도와 잔류 에너지를 측정하였 다. 시뮬레이션 결과를 통해 케블라, 초고분자량 폴리에틸렌, 에바 폼의 배열 순서를 갖는 적층 구조가 동일 중량에 대해 가장 우수한 방탄 성능을 가짐을 확인하였다.