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Numerical Analysis of Grout Flow and Injection Pressure Affected by Joint Roughness and Aperture (절리 거칠기와 간극 변화에 따른 그라우트 유동과 주입압에 관한 수치해석적 연구)

  • Jeon, Ki-Hwan;Ryu, Dong-Woo;Kim, Hyung-Mok;Park, Eui-Seob;Song, Jae-Jun
    • Tunnel and Underground Space
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    • v.20 no.2
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    • pp.82-91
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    • 2010
  • Grouting technology is one of the ground improvement methods used in water controlling and reinforcement of rock mass in underground structure construction. It is necessarily required to find out the characteristics of grout flow through discontinuities in a rock mass for an adequate grout design and performance assessment. Laminar flow is not always applicable in simulating a grout flow in a rock mass, since the rock joints usually have apertures at a micro-scale and the flow through these joints is affected by the joint roughness and the velocity profile of the flow changes partially near the roughness. Thus, the influence of joint roughness and aperture on the grout flow in rough rock joint was numerically investigated in this study. The commercial computational fluid dynamics code, FLUENT, was applied for this purpose. The computed results by embedded Herschel-Bulkley model and VOF (volume of fluid) model, which are applicable to simulate grout flow in a narrow rock joint that is filled with air and water, were well compared with that of analytical results and previously published laboratory test for the verification. The injection pressure required to keep constant injection rate of grout was calculated in a variety of Joint Roughness Coefficient (JRC) and aperture conditions, and the effect of joint roughness and aperture on grout flow were quantified.

A Full Scale Hydrodynamic Simulation of High Explosion Performance for Pyrotechnic Device (파이로테크닉 장치의 고폭 폭발성능 정밀 하이드로다이나믹 해석)

  • Kim, Bohoon;Yoh, Jai-ick
    • Journal of the Korea Society for Simulation
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    • v.28 no.2
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    • pp.1-14
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    • 2019
  • A full scale hydrodynamic simulation that requires an accurate reproduction of shock-induced detonation was conducted for design of an energetic component system. A detailed hydrodynamic analysis SW was developed to validate the reactive flow model for predicting the shock propagation in a train configuration and to quantify the shock sensitivity of the energetic materials. The pyrotechnic device is composed of four main components, namely a donor unit (HNS+HMX), a bulkhead (STS), an acceptor explosive (RDX), and a propellant (BPN) for gas generation. The pressurized gases generated from the burning propellant were purged into a 10 cc release chamber for study of the inherent oscillatory flow induced by the interferences between shock and rarefaction waves. The pressure fluctuations measured from experiment and calculation were investigated to further validate the peculiar peak at specific characteristic frequency (${\omega}_c=8.3kHz$). In this paper, a step-by-step numerical description of detonation of high explosive components, deflagration of propellant component, and deformation of metal component is given in order to facilitate the proper implementation of the outlined formulation into a shock physics code for a full scale hydrodynamic simulation of the energetic component system.

Evaluation of Shear Strength by Experiment and Finite Element Analysis of SFRC Hollow Members (SFRC 중공 부재의 실험 및 유한요소 해석에 의한 전단강도 평가)

  • Kim, Seong-Eun;Jeong, Jae-Won;Kim, Seung-Hun
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.23 no.4
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    • pp.78-85
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    • 2019
  • This study targets SFRC hollow members with small depth under shear force and bending. To evaluate the effect of web width on shear strength of SFRC members, experiment and finite element analysis were conducted and compared with existing equations. The web width was planned to be 1/2 times and 2/3 times, and the shear span ratio was planned to be 1.5 times. In the shear test results, the maximum shear strength increased by 10.3 to 28.0% with the web width increased by 33%. When the overall depth of specimens was increased by 1.5 times, the shear strength of the specimen with a web width of 100mm was increased by 29.2%. On the other hand, specimen with the 150mm only increased by 11.3%. These results indicate that the smaller the web width, the greater the shear strength increase with the increase of depth. Also, the smaller the web width, the greater the contribution of steel fiber. It has been shown that the KCI code evaluates the shear strength of experiments as very safe side, and that the proposed formula of Shin et al. predicts the experimental strength relatively well. As the web width increases by 2, 3, and 6 times, the mean shear strength by FEA appears to be 1.18, 1.80, and 2.19 times respectively. This indicates that the shear strength does not increase in proportion to the increase in web width.

Research Analysis in Automatic Fake News Detection (자동화기반의 가짜 뉴스 탐지를 위한 연구 분석)

  • Jwa, Hee-Jung;Oh, Dong-Suk;Lim, Heui-Seok
    • Journal of the Korea Convergence Society
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    • v.10 no.7
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    • pp.15-21
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    • 2019
  • Research in detecting fake information gained a lot of interest after the US presidential election in 2016. Information from unknown sources are produced in the shape of news, and its rapid spread is fueled by the interest of public drawn to stimulating and interesting issues. In addition, the wide use of mass communication platforms such as social network services makes this phenomenon worse. Poynter Institute created the International Fact Checking Network (IFCN) to provide guidelines for judging the facts of skilled professionals and releasing "Code of Ethics" for fact check agencies. However, this type of approach is costly because of the large number of experts required to test authenticity of each article. Therefore, research in automated fake news detection technology that can efficiently identify it is gaining more attention. In this paper, we investigate fake news detection systems and researches that are rapidly developing, mainly thanks to recent advances in deep learning technology. In addition, we also organize shared tasks and training corpus that are released in various forms, so that researchers can easily participate in this field, which deserves a lot of research effort.

Machine Learning Model to Predict Osteoporotic Spine with Hounsfield Units on Lumbar Computed Tomography

  • Nam, Kyoung Hyup;Seo, Il;Kim, Dong Hwan;Lee, Jae Il;Choi, Byung Kwan;Han, In Ho
    • Journal of Korean Neurosurgical Society
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    • v.62 no.4
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    • pp.442-449
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    • 2019
  • Objective : Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost. The present study was to demonstrate the utility of artificial intelligence and machine learning algorithm for assessing osteoporosis using Hounsfield units (HU) of preoperative lumbar CT coupling with data of QCT. Methods : We reviewed 70 patients undergoing both QCT and conventional lumbar CT for spine surgery. The T-scores of 198 lumbar vertebra was assessed in QCT and the HU of vertebral body at the same level were measured in conventional CT by the picture archiving and communication system (PACS) system. A multiple regression algorithm was applied to predict the T-score using three independent variables (age, sex, and HU of vertebral body on conventional CT) coupling with T-score of QCT. Next, a logistic regression algorithm was applied to predict osteoporotic or non-osteoporotic vertebra. The Tensor flow and Python were used as the machine learning tools. The Tensor flow user interface developed in our institute was used for easy code generation. Results : The predictive model with multiple regression algorithm estimated similar T-scores with data of QCT. HU demonstrates the similar results as QCT without the discordance in only one non-osteoporotic vertebra that indicated osteoporosis. From the training set, the predictive model classified the lumbar vertebra into two groups (osteoporotic vs. non-osteoporotic spine) with 88.0% accuracy. In a test set of 40 vertebrae, classification accuracy was 92.5% when the learning rate was 0.0001 (precision, 0.939; recall, 0.969; F1 score, 0.954; area under the curve, 0.900). Conclusion : This study is a simple machine learning model applicable in the spine research field. The machine learning model can predict the T-score and osteoporotic vertebrae solely by measuring the HU of conventional CT, and this would help spine surgeons not to under-estimate the osteoporotic spine preoperatively. If applied to a bigger data set, we believe the predictive accuracy of our model will further increase. We propose that machine learning is an important modality of the medical research field.

Effect of Hooked-end Steel Fiber Volume Fraction and Aspect Ratio on Flexural and Compressive Properties of Concrete (후크형 강섬유 혼입율 및 형상비에 따른 콘크리트의 휨 및 압축 특성)

  • Kim, Dong-Hui;Jang, Seok-Joon;Kim, Sun-Woo;Park, Wan-Shin;Yun, Hyun-Do
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.25 no.3
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    • pp.40-47
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    • 2021
  • This study investigates the influence of hooked-end steel fiber volume fraction and aspect ratio on the mechanical properties, such as compressive and flexural performance, of concrete with specified compressive strength of 30MPa. Three types of hooked-end steel fibers with aspect ratios of 64, 67 and 80 were selected. The flexural tests of steel fiber reinforced concrete (SFRC) prismatic specimens were conducted according to EN 14651. The compressive performance of SFRC with different volume fractions (0.25, 0.50 and 0.75%) were evaluated through standard compressive strength test method (KS F 2405). Experimental results indicated that the flexural strength, flexural toughness, fracture energy of concrete were improved as steel fiber volume fraction increases but there is no unique relationship between steel fiber volume fraction and compressive performance. The flexural and compressive properties of concrete incorporating hooked-end steel fiber with aspect ratio of 64 and 80 are a little better than those of SFRC with aspect ratio of 67. For each SFRC mixture used in the study, the residual flexural tensile strength ratio defined in Model Code 2010 was more than the limit value to be able to substitute rebar or welded mesh in structural members with the fiber reinforcement.

Two Types of Post-human in Recent Korean SF Films : Focusing on (2021), (2021) (최근 한국영화 속 포스트-휴먼의 두 가지 양상: <승리호>(2021), <서복>(2021)을 중심으로)

  • Yoo, Jae-eung;Lee, Hyun-Kyung
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.1
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    • pp.379-384
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    • 2022
  • The year 2021 is a monumental year for the history of Korean cinema that inferiority of the sci-fi genre, by the appearance of two sci-fi blockbuster films- produced by Netflix and produced by TVing-at the same time. Coincidentally, both of movies are sci-fi films which appear post-human such as robot and clone. As can be seen in 『Frankenstein』 story, the progenitor of science fictions, the mankind have imagined beings similar to humen or post-human who are another human being for a long time. deals with the unusual subject matter of a space scavenger and a space janitor, and the main character is a robot that very familiar with human. is the story of a man who lives for a limited life protects and accompanies a clone named Seobok who was created as a test subject. This film deals with the philosophical themes like death and eternal life through the existential concerns of two characters. use Korean Shinpa -Korean specific senimental code-sentiment on narrative, and has the character of a road movie set in Korea's geographical space.

A Study on Building Object Change Detection using Spatial Information - Building DB based on Road Name Address - (기구축 공간정보를 활용한 건물객체 변화 탐지 연구 - 도로명주소건물DB 중심으로 -)

  • Lee, Insu;Yeon, Sunghyun;Jeong, Hohyun
    • Journal of Cadastre & Land InformatiX
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    • v.52 no.1
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    • pp.105-118
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    • 2022
  • The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.

Study of Mechanical Properties and Porosity of Composites by Using Glass Fiber Felt (유리섬유 부직포 사용에 따른 복합재의 기공률 및 물성에의 영향 분석)

  • Lee, Ji-Seok;Yu, Myeong-Hyeon;Kim, Hak-Sung
    • Composites Research
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    • v.35 no.1
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    • pp.42-46
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    • 2022
  • In this study, when the carbon fiber composite was manufactured, the correlation between the porosity and mechanical properties according to the number of glass fiber felts laminated together and the stacking sequence was confirmed. The carbon fiber composite was manufactured by stacking glass fiber felts, which are highly permeable materials, and using vacuum assisted resin transfer molding (VARTM). Porosity was measured by photographing the cross-section of the specimen with an optical microscope and then using porosity calculation code of MATLAB, and mechanical properties were measured for tensile strength, modulus by tensile test. Furthermore, Pearson correlation coefficient between porosity and mechanical properties was calculated to confirm the correlation between two variables. As a result, the number of glass fiber felt increased and the distance from the center of laminated composites increased, the porosity increasing were confirmed. In addition, tensile strength/modulus showed a weak positive correlation with porosity. Also, in order to confirm the effect of only porosity on tensile strength and modulus, mechanical properties calculated by CLPT (Classical Laminate Plate Theory) and experimental values were compared, and the difference in tensile strength showed a strong positive correlation with porosity and the difference in modulus showed a weak positive correlation with porosity.

RANS simulation of secondary flows in a low pressure turbine cascade: Influence of inlet boundary layer profile

  • Michele, Errante;Andrea, Ferrero;Francesco, Larocca
    • Advances in aircraft and spacecraft science
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    • v.9 no.5
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    • pp.415-431
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    • 2022
  • Secondary flows have a huge impact on losses generation in modern low pressure gas turbines (LPTs). At design point, the interaction of the blade profile with the end-wall boundary layer is responsible for up to 40% of total losses. Therefore, predicting accurately the end-wall flow field in a LPT is extremely important in the industrial design phase. Since the inlet boundary layer profile is one of the factors which most affects the evolution of secondary flows, the first main objective of the present work is to investigate the impact of two different inlet conditions on the end-wall flow field of the T106A, a well known LPT cascade. The first condition, labeled in the paper as C1, is represented by uniform conditions at the inlet plane and the second, C2, by a flow characterized by a defined inlet boundary layer profile. The code used for the simulations is based on the Discontinuous Galerkin (DG) formulation and solves the Reynolds-averaged Navier-Stokes (RANS) equations coupled with the Spalart Allmaras turbulence model. Secondly, this work aims at estimating the influence of viscosity and turbulence on the T106A end-wall flow field. In order to do so, RANS results are compared with those obtained from an inviscid simulation with a prescribed inlet total pressure profile, which mimics a boundary layer. A comparison between C1 and C2 results highlights an influence of secondary flows on the flow field up to a significant distance from the end-wall. In particular, the C2 end-wall flow field appears to be characterized by greater over turning and under turning angles and higher total pressure losses. Furthermore, the C2 simulated flow field shows good agreement with experimental and numerical data available in literature. The C2 and inviscid Euler computed flow fields, although globally comparable, present evident differences. The cascade passage simulated with inviscid flow is mainly dominated by a single large and homogeneous vortex structure, less stretched in the spanwise direction and closer to the end-wall than vortical structures computed by compressible flow simulation. It is reasonable, then, asserting that for the chosen test case a great part of the secondary flows details is strongly dependent on viscous phenomena and turbulence.