• Geomechanics and Engineering
• /
• 제36권2호
• /
• pp.167-181
• /
• 2024

The soil-structure relative stiffness is a key factor affecting the seismic response of underground structures. It is of great significance to study the soil-structure relative stiffness for the soil-structure interaction and the seismic disaster reduction of subway stations. In this paper, the dynamic shear modulus ratio and damping ratio of an inhomogeneous soft soil site under different buried depths which were obtained by a one-dimensional equivalent linearization site response analysis were used as the input parameters in a 2D finite element model. A visco-elasto-plastic constitutive model based on the Mohr-Coulomb shear failure criterion combined with stiffness degradation was used to describe the plastic behavior of soil. The damage plasticity model was used to simulate the plastic behavior of concrete. The horizontal and vertical relative stiffness ratios of soil and structure were defined to study the influence of relative stiffness on the seismic response of subway stations in inhomogeneous soft soil. It is found that the compression damage to the middle columns of a subway station with a higher relative stiffness ratio is more serious while the tensile damage is slighter under the same earthquake motion. The relative stiffness has a significant influence on ground surface deformation, ground acceleration, and station structure deformation. However, the effect of the relative stiffness on the deformation of the bottom slab of the subway station is small. The research results can provide a reference for seismic fortification of subway stations in the soft soil area.

• Archives of Plastic Surgery
• /
• 제47권2호
• /
• pp.146-152
• /
• 2020

Background Preoperative computed tomography angiography (CTA) of the abdominal wall vessels is used when planning free flap breast reconstruction (FFBR) because it provides a surgical road map which facilitates flap harvest. However, there are few reports on the effect of abnormal findings on the operative plan. Methods We conducted a retrospective study of all FFBRs performed at a tertiary referral center over a 6-year period (November 2011 to June 2017). One consultant radiologist reported on the findings. Details on patient demographics, CTA reports, and intraoperative details were collected. Results Two hundred patients received preoperative CTAs. Fourteen percent of patients (n=28) had abnormal findings. Of these findings, 18% were vascular anomalies; 36% tumorrelated and 46% were "miscellaneous." In four patients, findings subsequently prevented surgery; they comprised a mesenteric artery aneurysm, absent deep inferior epigastric (DIE) vessels, bilateral occluded DIE arteries, and significant bone metastases. Another patient had no suitable vessels for a free flap and the surgical plan converted to a pedicled transverse rectus abdominis musculocutaneous flap. The remaining incidental findings had no impact on the surgical plan or appropriateness of FFBR. More than one in 10 of those with abnormal findings went on to have further imaging before their operation. Conclusions CTA in FFBR can have a wider impact than facilitating surgical planning and reducing operative times. Incidental findings can influence the surgical plan, and in some instances, avoid doomed-to-fail and unsafe surgery. It is therefore important that these scans are reported by an experienced radiologist.

• 한국컴퓨터정보학회논문지
• /
• 제25권9호
• /
• pp.31-36
• /
• 2020

본 연구에서는 딥러닝 처리기술을 이용한 이미지 분석을 통하여 위치정보가 없는 사진의 위치를 사용자에게 제공하는 장소이미지 수집기술을 설계하였다. 본 서비스는 사용자가 생활 중에 관심 있는 장소의 이미지 사진을 서비스에 업로드하면 해당 장소의 이름과 위치뿐만 아니라 관련 주변 정보를 확인 할 수 있는 서비스 개발을 목적으로 설계되었다. 본 연구는 이미지에 해당하는 정보를 제공하고 그 위치 정보를 기반으로 사용자가 관심 있는 주변정보를 제공할 수 있는 서비스의 기반기술이다. 이를 통하여 다양한 서비스에 활용이 가능하다.

• Geomechanics and Engineering
• /
• 제12권5호
• /
• pp.771-783
• /
• 2017

Using a transparent fracture replica with aperture size and water-cement ratio (w/c), the factors affecting the penetration behavior of rock grouting were investigated through laboratory experiments. In addition, the waterproof efficiency was estimated by the reduction of water outflow through the fractures after the grout curing process. Penetration behavior shows that grout penetration patterns present similarly radial forms in all experimental cases; however, velocity of grout penetration showed clear differences according to the aperture sizes and water-cement ratio. It can be seen that the waterproof efficiency increased as the aperture size and w/c decreased. During grout injection or curing processes, air bubbles formed and bleeding occurred, both of which affected the waterproof ability of the grouting. These two phenomena can significantly prevent the successful performance of rock grouting in field-scale underground spaces, especially at deep depth conditions. Our research can provide a foundation for improving and optimizing the innovative techniques of rock grouting.

• Journal of Ecology and Environment
• /
• 제29권2호
• /
• pp.175-183
• /
• 2006

The discovery of deep-sea hydrothermal vents and their ecosystems is a monumental landmark in the history of Ocean Sciences. Deep-sea hydrothermal vents are scattered along the global mid-ocean ridges and back-arc basins. Under sea volcanic phenomena related to underlying magma activities along mid-ocean ridges generate extreme habitats for highly specialized communities of animals. Multidisciplinary research efforts during past three decades since the first discovery of hydrothermal vents along the Galapagos Rift in 1977 revealed fundamental components of physiology, ecology, and evolution of specialized vent communities of micro and macro fauna. Heterogeneous regional geological settings and tectonic plate history have been considered as important geophysical and evolutionary factors for current patterns of taxonomic composition and distribution of vent faunas among venting sites in the World Ocean basins. It was found that these communities are based on primary production of chemosynthetic bacteria which directly utilize reduced compounds, mostly $H_2S$ and $CH_4$, mixed in vent fluids. Symbioses between these bacteria and their hosts, vent invertebrates, are foundation of the vent ecosystem. Gene flow and population genetic studies in parallel with larval biology began to unveil hidden dispersal barrier under deep sea as well as various dispersal characteristics cross taxa. Comparative molecular phylogenetics of vent animals revealed that vent faunas are closely related to those of cold-water seeps in general. In perspective additional interesting discoveries are anticipated particularly with further refined and expanded studies aided by new instrumental technologies.

• 한국해양공학회:학술대회논문집
• /
• 한국해양공학회 2004년도 학술대회지
• /
• pp.29-34
• /
• 2004

Numerical and experimental studies on pipeline laying for intake Deep Ocean Water are carried out. In the numerical study, an implicit finite difference algorithm is employed for three-dimensional pipe equations. Fluid non-linearity and bending stiffness are considered and solved by Newton-Raphson iteration. Seabed is modeled as elastic foundation with linear spring and damper. Top tension and general configuration of pipeline at a depth are predicted. It is found that control for tension to prevent being large curvature of pipeline is needed on th steep seabed and, it should be considered 23.5 ton of tension at a top of pipe on the process of pipeline laying at 400m of water depth The largest top tension of pipe on condition of the beam sea during pipe laying is shown from the experiment. The results of this study can be contributed to the design of pipeline laying for upwelling deep ocean water.

• 한국지반공학회논문집
• /
• 제15권2호
• /
• pp.139-152
• /
• 1999

근래에 들어 구조물의 대형화에 따라 현장타설 말뚝을 하부 구조물로서 광범위하게 적용하고 있다. 그러나 현장타설 말뚝에 결함이 생기면 상부 하중에 대한 지지력 저하와 함께 침하량이 증가하게 되어 상부 구조물에 치명적인 손실을 초래할 수 있다. 따라서 비파괴시험 기법에 의한 콘크리트 말뚝의 효과적인 건전도 평가기법 개발이 중요하게 대두되고 있다. 본 연구에서는 수치해석을 통하여 콘크리트 말뚝의 건전도 평가에 이용되는 충격반향기법의 적용성을 검토하였다. 3차원 축대칭 유한요소법을 이용하여 건전한 말뚝과 현장타설 말뚝의 전형적인 결함인 병목, 공동, 불량 콘크리트를 포함하는 말뚝, 그리고 지반 및 암반위에 놓인 말뚝에 관한 해석을 수행하였다. 해석결과 현장타설 말뚝에 적용되는 충격반향기법의 적용성 평가에 있어서 유한요소법이 효과적임을 알 수 있었다.

• 한국BIM학회 논문집
• /
• 제9권4호
• /
• pp.31-40
• /
• 2019

With Building Information Modeling(BIM) becoming the de facto standard for data sharing in the AEC industry, additional needs have increased to ensure the data integrity of BIM models themselves. Although the Industry Foundation Classes provide an open and neutral data format, its generalized schema leaves it open to data loss and misclassifications This research applied deep learning to automatically classify BIM elements and thus check the integrity of BIM-to-IFC mappings. Multi-view CNN(MVCC) and PointNet, which are two deep learning models customized to learn and classify in 3 dimensional non-euclidean spaces, were used. The analysis was restricted to classifying subtypes of architectural walls. MVCNN resulted in the highest performance, with ACC and F1 score of 0.95 and 0.94. MVCNN unitizes images from multiple perspectives of an element, and was thus able to learn the nuanced differences of wall subtypes. PointNet, on the other hand, lost many of the detailed features as it uses a sample of the point clouds and perceived only the 'skeleton' of the given walls.

• 한국산업정보학회논문지
• /
• 제23권4호
• /
• pp.81-92
• /
• 2018

Bitcoin is a cryptographic digital currency and has been given a significant amount of attention in literature since it was first introduced by Satoshi Nakamoto in 2009. It has become an outstanding digital currency with a current market capitalization of approximately $60 billion. By 2019, it is expected to have over 5 million users. Nowadays, investing in Bitcoin is popular, and along with the advantages and disadvantages of Bitcoin, learning how to forecast is important for investors in their decision-making so that they are able to anticipate problems and earn a profit. However, most investors are reluctant to invest in bitcoin because it often fluctuates and is unpredictable, which may cost a lot of money. In this paper, we focus on solving the Bitcoin forecasting prediction problem based on deep learning structures and neural decomposition. First, we propose a deep learning-based framework for the bitcoin forecasting problem with deep feed forward neural network. Forecasting is a time-dependent data type; thus, to extract the information from the data requires decomposition as the feature extraction technique. Based on the results of the experiment, the use of neural decomposition and deep neural networks allows for accurate predictions of around 89%.

• 생물환경조절학회지
• /
• 제30권4호
• /
• pp.287-294
• /
• 2021

국가관리 간척지내 원예단지 조성에 필요한 기반기술 중에 하나인, 온실기초 연구가 부족한 실정이며 고사양의 PHC파일을 대체하기 위한 대안을 검토하고자 하였다. 지반개량공법 중 심층혼합처리공법(DCM) 적용시 허용지지력과 침하량 산정을 통하여 온실기초 공법으로써의 적용가능성을 검토하였다. 새만금간척지 농생명용지 1공구 지반조사를 통해 지반 특성을 파악하고, Terzaghi, Meyerhof, Hansen, Schmertmann 이론식을 적용하여 허용지지력과 침하량을 산정하였다. 직경 800mm를 기준으로, 독립 기초 폭과 길이가 3-6m이고, 기초 심도 3-7m 조건에서 허용지지력과 침하량을 검토하였다. 온실기초 심도가 얕고 콘크리트 매트 간격이 넓을수록 시공비가 절감되는 측면을 고려하여 독립 기초 폭과 길이가 4m, 기초 심도가 3m인 경우가 가장 적합한 것으로 판단되었다. 독립 기초 폭과 길이가 4m이고, 기초 심도가 3m인 조건에 대한 해석 결과로 허용지지력은 169kN/m², 침하량은 2.73mm로 지지력은 이론식 대비 5.6%의 오차를, 침하량은 62.3%의 오차범위를 나타냈다. 향후, 위 검증된 설계 값을 기준으로 구조 시험과 침하모니터링을 통해 신뢰성을 검증하고자 한다. 그 외 나무말뚝, 헬리컬기초 등 유리온실, 내재해형온실에 적용 가능한 기초 공법과의 비교 검증을 통해 각각의 장, 단점을 파악하고 PHC 파일의 대체 가능 유무를 검토할 예정이다. 이는 온실 유형별 시공 공법을 선정하는데 필요한 기초 데이터로 제시될 수 있을 것으로 기대된다.