• Journal of computational fluids engineering
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• v.2 no.1
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• pp.109-116
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• 1997

The objective of this paper is to develop a computational model for the prediction of the pollutant spread from a mass source over a complex terrain. The model comprises a two-dimensional, steady state flow model and a concentration model which employs the results of the computed flow field. The computational model is applied to predict the spread of pollutants for Sanbon city, and the two cases have been compard with the results of SF/sub 6/ trace experiments.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.17 no.1
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• pp.9-14
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• 1984

To study the correlation of the net drag force, net height, and towing speed, three kinds of similiar size model trawl nets were experimented in the still watertank ($60m{\times}4m{\times}3m$). The scale ratios of model nets, 2 seam, 4 seam, and 6 scam net were 1/31.3, 1/20.0, and 1/44.4 respectively, The maximum streched circumferences of the bag net were same length, i. e. 140cm. Net drags were propotional to the $1.75{\sim}1.98th$ order of towing speed and showed similar result as Koyama's net drag equation. Net heights were propotional to the $-0.85{\sim}-0.72th$ order of towing speed. It could observe that the towing nets showed normal shape in $3.0{\sim}3.5$ knot full scale towing speed but bad shape below $1.0{\sim}1.5$ knot. And it showed tendency to lift the bag net and codend with increasing speed.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.60-67
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• 2008

The vibrations and noise origin in electric material is due to several coupled physical phenomena. The revolving electric machine complete modeling is complex; it does not allow simple parametric machine structure studies for various operation modes. This work presents a simple electromagnetic model which makes possible the machine principal parts flow estimation from flux density. Special interest is given in determining Switched Reluctance Machine (S.R.M) radial acceleration in accordance with the current supply. Our focus will be only on the magnetic origin efforts that are dominating in the S.R.M. The efforts calculation versus the current is presented in the case of a machine with a linearized rate. These efforts are considered as a tangential force producing the torque and a radial force that generates no torque. The application is realized on a 6/4 low power S.R.M type (6 stator teeth and 4 teeth rotor). The mechanical response is substituted in a transfer function. The model takes account of the power supply of the machine, the relation between the current supply and the efforts as well as the vibratory response of the machine to these efforts. Finally, the model is validated by comparison with similar experimental results within the framework of the definite assumptions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.517-523
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• 2019

PM₁₀ concentration is a spatiotemporal phenomenta and capturing data for such continuous phenomena is a difficult task. This study designed a model that enhances spatiotemporal resolution of PM₁₀ concentration levels using satellite imagery, atmospheric and meteorological sensor data, and multiple deep learning models. The designed deep learning model was trained using input data whose factors may affect concentration of PM₁₀ such as meteorological conditions and land-use. Using this model, PM₁₀ images having 15 minute temporal resolution and 30m×30m spatial resolution were produced with only atmospheric and meteorological data.

• Journal of the Korean Society of Safety
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• v.30 no.6
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• pp.63-69
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• 2015

In this study, a 2D hydrodynamic model equipped with critical dry depth scheme was developed to reproduce the flow over staircase. The channel geometry of hydraulic experiment conducted by Ishigaki et al. was generated in the computational space, and the developed model was validated against flow properties such as discharge, velocity and momentum. In addition, the water surface profile and the velocity distribution evolved in flow over two layers staircases were analyzed. When the initial water depth at the upper floor was 0.3 m, the maximum velocity at lower floor was 4.2 m/s, and the maximum momentum was $1.2m^3/s^2$, and its conversion to force per unit width was 1.2 kN/m. This value was equivalent to the hydrostatic force with 50 cm water depth, and evacuation became difficult, as proposed by Ishigaki et al. For the flow over staircases connecting two layers, the maximum run-up height in flat part connecting two layers was approximately two times higher than the initial water depth in upper floor, and the rapid shock wave with sharp front and long tail was propagated.

• Journal of Biosystems Engineering
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• v.28 no.1
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• pp.35-44
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• 2003

This study was conducted to develop proper model for cold storage facility that could of for uniform heat movement and air movement f3r green grocery and improve improper design of the existing container-type cold storage facility. For that reason, new model(dome-type) cold storage facility was developed using 3-D CFD(computational fluid dynamics) simulation. The size was 6m${\times}$6m${\times}$5m. Its size and configuration were same to simulation model. Unit cooler was designed to send cold air in 4 side ways. A dome-type cold storage facility showed uniform distributions of air temperature and velocity because cold air was forced to move down along the ceiling and the wall and then circulated to the unit cooler from the central part of the floor. Dome-type cold storage facility also showed by low wind velocity, below 1 m/s that could minimized cold damage and quality deterioration.

• Korean Journal of Remote Sensing
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• v.18 no.4
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• pp.221-231
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• 2002

In this study we applied a DEM generation algorithm developed in-house to satellite images at various resolution and discussed the results. We tested SPOT images at l0m resolution, EOC images at 6.6m and IKONOS images at 1m resolution. These images include the same urban area in Daejeon city. For camera model, we used Gupta & Hartley's(1997) DLT model for all three image sets. We carried out accuracy assessment using USGS DTED for SPOT and EOC and 23 check points for IKONOS. The assessment showed that SPOT DEM had about 38m RMS error, EOC DEM 12m RMS error and IKONOS DEM 6.5m RMS error. In terms of image resolution, SPOT and EOC DEM error corresponds to 2∼4 pixels where as IKONOS DEM error 6∼7pixels. IKONOS DEM contains more errors in pixels. However, in IKONOS DEM, individual buildings, apartments and major roads are identifiable. All three DEMs contained errors due to height discontinuity, occlusion and shadow. These experiments show that our algorithm can generate urban DEM from 1m resolution and that, however, we need to improve the algorithm to minimize effects of occlusion and building shadows on DEMs.

• Computers and Concrete
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• v.3 no.6
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• pp.439-454
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• 2006

This paper develops an artificial neural network (ANN) model for uniformly loaded restrained reinforced concrete (RC) slabs incorporating membrane action. The development of membrane action in RC slabs restrained against lateral displacements at the edges in buildings and bridge structures significantly increases their load carrying capacity. The benefits of compressive membrane action are usually not taken into account in currently available design methods based on yield-line theory. By extending the existing knowledge of compressive membrane action, it is possible to design slabs in building and bridge decks economically with less than normal reinforcement. The processes involved in the development of ANN model such as the creation of a database of test results from previous research studies, the selection of architecture of the network from extensive trial and error procedure, and the training and performance validation of the model are presented. The ANN model was found to predict accurately the ultimate strength of fully restrained RC slabs. The model also was able to incorporate strength enhancement of RC slabs due to membrane action as confirmed from a comparative study of experimental and yield line-based predictions. Practical applications of the developed ANN model in the design process of RC slabs are also highlighted.

• The Korean Journal of Pain
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• v.12 no.1
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• pp.8-15
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• 1999

Following peripheral nerve injury, rats will show a tactile allodynia and hyperalgesia. But the mechanism of allodynia is still obscure. The present studies, using rats rendered allodynia by loosely constrictive ligation of the common sciatic nerve (Bennett Model) and tight ligation of L5 & L6 spinal nerve (Chung Model), aimed to investigate the changes of metabotrophic glutamate receptor type 5 on the development of tactile allodynia. Male Sprague-Dawley rats (130~200 g) were anesthetized with halothane, the rats were randomly divided into one of these three groups, Group 1 (Sham operation), Group 2 (Bennett model) and Group 3 (Chung model). Seven days after surgical procedure, the animal was reanesthetized and decapitated. The spinal cord was quickly removed and stored at deep freezer for polymerase chain reaction (RT-PCR). In Group 2&3, rats showed that tactile allodynia checked by up-down method with calibrated 8 von Frey hair. The level of gene expression of mGluR5 mRNA was significantly increased in group 2 and 3. These increases was significantly different from sham operation, group 1. It was also showed that the increasing patterns of group 2 and 3 in the gene expression were similar correlation with the results of the threshold for tactile allodynia on von Frey hair test. Even though there were some differences between Bennett model and Chung model, these results suggested that mGluR5 had partly attributed to making a tactile allodynia from these models.

• Asian-Australasian Journal of Animal Sciences
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• v.8 no.4
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• pp.365-368
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• 1995

Lactation curves of dairy cows were generated using three models, namely; incomplete gamma function (model 1), polynomial inverse function (model 2) and non-linear regression (model 3). Secondary milk yield data of 27 cows which had completed 6 lactations were used in this study. Milk yield records (once a week) throughout the lactation and from the first three months of lactation were fitted to the models. Estimation of total milk yield by model 3 using the data once a week throughout the lactation resulted in smaller % bias and standard error than those generated from model 1 and 2. But, model 2 was more accurate in predicting the 305-day milk yield equivalent closer to actual yields with smaller bias % and error using partial records up to 3 months. Also, model 2 was able to estimate the time to reach peak yield close to the actual data using partial records and model 2 could be used as a tool to advise farmers on appropriate feeding and management practices to be adopted.