This study numerically compares optimum solutions generated by element- and node-wise topology optimization designs for free vibration structures, where element-and node-wise denote the use of element and nodal densities as design parameters, respectively. For static problems optimal solution comparisons of the two types for topology optimization designs have already been introduced by the author and many other researchers, and the static structural design is very common. In dynamic topology optimization problems the objective is in general related to maximum Eigenfrequency optimization subject to a given material limit since structures with a high fundamental frequency tend to be reasonable stiff for static loads. Numerical applications topologically maximizing the first natural Eigenfrequency verify the difference of solutions between element-and node-wise topology optimum designs.

정보통신 기술의 발전과 스마트 기기의 확산으로 스마트러닝이 보편화되었으며 이에 따라 스마트러닝 관련 연구가 활발하게 이루어지고 있으며 연구 성과가 축적되고 있다. 이에 기존의 스마트러닝 연구 중에 서 상관계수 결과를 포함한 논문을 대상으로 메타분석을 실시하여 스마트러닝의 효과크기를 분석하였다. 이 과정에서 선행연구 결과를 검토하여 스마트러닝 특성요인으로 동기유발, 시스템, 콘텐츠, 서비스로 유 목화하고, 결과변수로는 만족도, 성과, 태도를 정의하였다. 메타분석 결과 스마트러닝 전체 관점뿐 아니라 각 특성요인인 동기유발, 시스템, 콘텐츠, 서비스 모든 측면에서 스마트러닝의 효과크기는 유의하게 중간 정도 수준으로 나타났다. 유일하게 유의하지 않은 것으로 나타난 성과에 대한 콘텐츠의 효과크기를 제외 하고는 만족도, 성과, 태도 모든 측면에서 스마트러닝 각 특성요인의 효과크기가 유의하게 중간 정도 수준으로 나타났다. 연구 대상에 따른 효과크기 측면에서는 직장인이 가장 높은 효과를 유의하게 보였다. 표본수에 따른 효과크기 측면에서는 300명에서 999명까지가 유의하게 가장 높게 나타났다. 본 논문이 시도한 스마트러닝 메타분석은 시의성으로나 확장된 연구 대상 논문 수 측면에서 의의를 찾을 수 있으며 수많은 스마트러닝 특성요인과 결과변수를 유목화하고 분류한 뒤 이에 대한 효과크기를 측정하였다는 데에 의의가 있다. 각 연구자들의 시각과 필요에 따라 다양한 표현을 동원한 스마트러닝 특성요인과 결과변수를 본 연구의 연구자들이 종합적인 관점에서 분류한 것은 향후 스마트러닝 연구를 위한 하나의 새로운 밑거름이 될 수 있다.

신뢰성 있는 토양의 이산요소모델을 개발하기 위해서는 토양의 특성을 고려하여 매개변수를 교정해야 한다. 본 연구에서는 이산요소모델을 구성하는 각 매개변수가 토양 입자의 거동에 미치는 영향을 분석하였고, 분석된 결과를 이용하여 토양의 이산요소모델을 개발하였다. 민감도 분석의 대상이 되는 매개변수는 전단 계수, 마찰 계수, 표면 에너지 등으로 선정하였으며, 교정의 기준이 되는 토양의 특성은 가비중, 안식각, 점착력 및 내부마찰각으로 선정하였다. 또한, 토성이 서로 다른 해안가, 논 및 밭을 구성하는 토양을 대상으로 연구를 수행하여 다양한 토성에 대한 적용성을 확인하였다. 결과적으로 본 연구에서 수행한 민감도 분석 결과를 이용하여 각 토양의 거동을 모사할 수 있는 이산요소모델을 교정하였으며, 시험 결과와의 비교를 통해 교정된 이산요소모델을 검증하였다.

In this study, theoretical analyses are performed to investigate the characteristics of the static and dynamic stiffness of a nonlinear vibration isolator system. The vibration isolator system is modeled as an equivalent nonlinear oscillator. Based on the model, the static equilibrium and frequency response solutions are obtained with the variations of external static load and/or system parameters. It is shown that the static stiffness of the nonlinear vibration isolator tends to be hardened with the increase of external static load, which prevents the occurrence of excessively large deflection. This static stiffness-hardening effect is more remarkable with a larger spring constant ratio. The dynamic stiffness is also strengthened when the spring constant ratio increases, which enlarges the force transmissibility and reduces the isolation frequency bandwidth. Thus, the static stiffness- hardening improves the robustness of the nonlinear vibration isolator, whereas the dynamic stiffness-hardening rather degrades its performance. Thus, the opposite tendency of the static and dynamic stiffness-hardening effects should be considered in the design process of the nonlinear vibration isolator.

This study performed the seismic response analysis of an LNG storage tank supported by a disconnected piled raft foundation (DPRF) with a load transfer platform (LTP). For this purpose, a precise analytical model with simultaneous consideration of Fluid-Structure Interaction (FSI) and Soil-Structure Interaction (SSI) was used. The effect of the LTP characteristics (thickness, stiffness) of the DPRF system on the seismic response of the superstructure (inner and outer tanks) and piles was analyzed. The analytical results were compared with the response of the piled raft foundation (PRF) system. The following conclusions can be drawn from the numerical results: (1) The DPRF system has a smaller bending moment and axial force at the head of the pile than the PRF system, even if the thickness and stiffness of the LTP change; (2) The DPRF system has a slight stiffness of the LTP and the superstructure member force can increase with increasing thickness. This is because as the stiffness of the LTP decreases and the thickness increases, the natural frequency of the LTP becomes closer to the natural frequency of the superstructure, which may affect the response of the superstructure. Therefore, when applying the DPRF system, it is recommended that the sensitivity analysis of the seismic response to the thickness and stiffness of the LTP must be performed.

Nowadays, artificial intelligence model approaches such as machine and deep learning have been widely used to predict variations of water quality in various freshwater bodies. In particular, many researchers have tried to predict the occurrence of cyanobacterial blooms in inland water, which pose a threat to human health and aquatic ecosystems. Therefore, the objective of this study were to: 1) review studies on the application of machine learning models for predicting the occurrence of cyanobacterial blooms and its metabolites and 2) prospect for future study on the prediction of cyanobacteria by machine learning models including deep learning. In this study, a systematic literature search and review were conducted using SCOPUS, which is Elsevier’s abstract and citation database. The key results showed that deep learning models were usually used to predict cyanobacterial cells, while machine learning models focused on predicting cyanobacterial metabolites such as concentrations of microcystin, geosmin, and 2-methylisoborneol (2-MIB) in reservoirs. There was a distinct difference in the use of input variables to predict cyanobacterial cells and metabolites. The application of deep learning models through the construction of big data may be encouraged to build accurate models to predict cyanobacterial metabolites.

The study used the whole-life carbon assessment method to conduct a thorough carbon-neutral evaluation of a standard steel structure. To further assess carbon emissions, 11 design-changed models were evaluated, with changes made to the span between beams and columns. The results of the carbon emission assessment showed savings of approximately 13.1% by implementing the stage of the beyond life cycle. Additionally, the evaluation of carbon emissions through design changes revealed a difference of up to 42.2%. These findings confirmed that recycling and structural design changes can significantly reduce carbon emissions by up to 48.6%, making it an effective means of achieving carbon neutrality. It is therefore necessary to apply the stage of beyond life cycle and structural change to reduce carbon emissions.

Metal additive manufacturing (AM) has transformed conventional manufacturing processes by offering unprecedented opportunities for design innovation, reduced lead times, and cost-effective production. Aluminum alloy, a material used in metal 3D printing, is a representative lightweight structural material known for its high specific strength and corrosion resistance. Consequently, there is an increasing demand for 3D printed aluminum alloy components across industries, including aerospace, transportation, and consumer goods. To meet this demand, research on alloys and process conditions that satisfy the specific requirement of each industry is necessary. However, 3D printing processes exhibit different behaviors of alloy elements owing to rapid thermal dynamics, making it challenging to predict the microstructure and properties. In this study, we gathered published data on the relationship between alloy composition, processing conditions, and properties. Furthermore, we conducted a sensitivity analysis on the effects of the process variables on the density and hardness of aluminum alloys used in additive manufacturing.

본 연구는 고속도로용 RC 교각 기둥구조에 대하여 축방향 기존 철근을 중공철근으로 대체하는 설계방안을 제시하였 다. 동일직경 기준으로 기존 이형철근을 중공철근으로 대체할 수 있는 합리적인 설계방안을 제시하였으며, 기존 축방향 배근량 을 감소하는 방안을 제안하였다. 본 연구에서 제안한 설계방안을 검증하기 위하여 3차원 유한요소 구조해석을 수행하였으며, 압 축하중에 의한 변수 수치해석을 통하여 본 연구에서 제안한 방안의 타당성을 제시하였다. 향후 다양한 변수 수치해석 및 실물 시험을 통하여 본 연구에서 제시한 설계방안에 대한 추가 검증이 필요하다.

코로나 19 팬데믹 및 기후 변화 등으로 전 세계적으로 필수적인 생필품과 자원의 품귀 이슈가 지속해서 발생하고 있다. 이러한 현상을 극복하고자 교역량의 수요가 갑자기 증가하였으며 이 결과 컨테이너선의 운임이 대폭 상승하였다. 컨테이너선의 크기 변화는 1960 년대 1,500TEU(twenty-foot equivalent unit)를 시작으로 2021년에는 24,400TEU로 대형화가 진행되고 있다. 컨테이너 적재 능력의 향상은 라싱브 릿지 구조의 대형화와 긴밀하게 연관되어 있고, 안전한 컨테이너 고박 및 항해 시 발생하는 다양한 외력 하중에 안전한 구조설계를 해야 한다. 현재 주요 선급에서는 라싱브릿지 구조 안전성을 평가할 수 있는 구조해석 기반의 지침서를 배포하고 있으나, 허용기준 및 평가 방 법이 달라서 설계 시 엔지니어들에게 혼선을 주고 있다. 본 연구에서는 결과에 영향을 줄 가능성이 큰 주요 변수들(모델링 범위, 오프닝 고 려 여부, 메쉬 크기) 변화에 따른 강도 변화 특성을 정리하였다. 이 결과를 바탕으로 저자들은 합리적인 구조해석 기반 평가에 대한 검토사 항을 제안하였고, 추후 선급 기준 개정 시 참고가 될 수 있을 것으로 기대한다.

An Ant Colony Optimization Algorithm(ACO) is one of the frequently used algorithms to solve the Traveling Salesman Problem(TSP). Since the ACO searches for the optimal value by updating the pheromone, it is difficult to consider the distance between the nodes and other variables other than the amount of the pheromone. In this study, fuzzy logic is added to ACO, which can help in making decision with multiple variables. The improved algorithm improves computation complexity and increases computation time when other variables besides distance and pheromone are added. Therefore, using the algorithm improved by the fuzzy logic, it is possible to solve TSP with many variables accurately and quickly. Existing ACO have been applied only to pheromone as a criterion for decision making, and other variables are excluded. However, when applying the fuzzy logic, it is possible to apply the algorithm to various situations because it is easy to judge which way is safe and fast by not only searching for the road but also adding other variables such as accident risk and road congestion. Adding a variable to an existing algorithm, it takes a long time to calculate each corresponding variable. However, when the improved algorithm is used, the result of calculating the fuzzy logic reduces the computation time to obtain the optimum value.

The column-tree type steel beam-column connections are commonly used in East Asian countries, including Korea. The welding detail between the stub beam and column is similar to the WUF-W connection; thus, it can be expected to have sufficient seismic performance. However, previous experimental studies indicate that premature slip occurs at the friction joints between the stub and link beams. In this study, for the accurate seismic performance evaluation of column-tree type moment connections, a moment-slip model was proposed by investigating the previous test results. As a result, it was found that the initial slip occurred at about 25% of the design slip moment strength, and the amount of slip was about 0.15%. Also, by comparing the analysis results from models with and without the slip element, the influence of slip on the performance of overall beam-column connections was examined. As the panel zone became weaker, the contribution of slip on overall deformation became greater, and the shear demand for the panel zone was reduced.

Submarining is a phenomenon in that the lap belt goes over the pelvis of the occupant during a frontal crash. It is known to be one of the causes of serious abdominal injuries for the belted occupant. The goal of the current study was to investigate the effect of both the belt geometry and dummy variations on the occurrence of submarining. A series of quasi-static belt-pull tests were performed to evaluate the influence of the parameters on the occurrence of the submarining. The main influencing factor of the submarining was the lap belt angle. The tear or wrinkle of the dummy clothing and torso angle relative to the pelvis also affected the propensity of the submarining. Therefore, these parameters need to be closely monitored to obtain repeatable test results.