• Title/Summary/Keyword: 벽함수

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Flow Resistance and Modeling Rule of Fishing Nets 5. Total Resistance of Bottom Trawl Nets Subjected Simultaneously to the Water Flow and the Bottom Friction (그물어구의 유수저항과 모형수칙 5. 저층 트롤그물의 예망저항)

  • KIM Dae-An
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.30 no.5
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    • pp.700-707
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    • 1997
  • In order to express exactly the total resistance of bottom trawl nets subjected simultaneously to the water flow and the bottom friction, the influence of frictional force was added to the formular for the flow resistance of trawl nets obtained by previous papev and the experimental data obtained by other investigators were analyzed by the formula. The analyzation produced the total resistance R (kg) expressed as $$R=4.5(\frac{S_n}{S_m})^{1.2}S\;v^{-1.8}+20(Bv)^{1.1}$$ where $S(m^2)$ was the wall area of nets, $S_m\;(m^2)$ the cross-sectional area of net mouths, $S_n\;(m^2)$ the area of nets projected to the plane perpendicular to the water flow, B (m) the made-up circumference at the fore edge of bag parts, and v(m/sec) the dragging velocity. From the viewpoint that expressing R in the form of $R=kSv^2$ was a usual practice, however, the resistant coefficient $k(kg{\cdot}sec^2/m^4)$ was compared with the factors influencing it by reusing the experimental data. The comparison gave that the coefficient k might be expressed approximately as a function of BL only and so the resistance R (kg) as $$R=18{\alpha}B^{0.5}L\;v^{1.5}$$ where L (m) was the made-up total length of nets and $\alpha=S/BL$. But the values of a in the nets did not deviate largely from their mean, 0.48, for all the nets and so the general expression of R (kg) for all the bottom trawl nets could be written as $$R=9\;B^{0.5}\;L\;v^{1.5}$$.

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A Study on Electron Dose Distribution of Cones for Intraoperative Radiation Therapy (수술중 전자선치료에 있어서 선량분포에 관한 연구)

  • Kang, Wee-Saing;Ha, Sung-Whan;Yun, Hyong-Geun
    • Progress in Medical Physics
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    • v.3 no.2
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    • pp.1-12
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    • 1992
  • For intraoperative radiation therapy using electron beams, a cone system to deliver a large dose to the tumor during surgical operation and to save the surrounding normal tissue should be developed and dosimetry for the cone system is necessary to find proper X-ray collimator setting as well as to get useful data for clinical use. We developed a docking type of a cone system consisting of two parts made of aluminum: holder and cone. The cones which range from 4cm to 9cm with 1cm step at 100cm SSD of photon beam are 28cm long circular tubular cylinders. The system has two 26cm long holders: one for the cones larger than or equal to 7cm diamter and another for the smaller ones than 7cm. On the side of the holder is an aperture for insertion of a lamp and mirror to observe treatment field. Depth dose curve. dose profile and output factor at dept of dose maximum. and dose distribution in water for each cone size were measured with a p-type silicone detector controlled by a linear scanner for several extra opening of X-ray collimators. For a combination of electron energy and cone size, the opening of the X-ray collimator was caused to the surface dose, depths of dose maximum and 80%, dose profile and output factor. The variation of the output factor was the most remarkable. The output factors of 9MeV electron, as an example, range from 0.637 to 1.549. The opening of X-ray collimators would cause the quantity of scattered electrons coming to the IORT cone system. which in turn would change the dose distribution as well as the output factor. Dosimetry for an IORT cone system is inevitable to minimize uncertainty in the clinical use.

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Detection with a SWNT Gas Sensor and Diffusion of SF6 Decomposition Products by Corona Discharges (탄소나노튜브 가스센서의 SF6 분해생성물 검출 및 확산현상에 관한 연구)

  • Lee, J.C.;Jung, S.H.;Baik, S.H.
    • Journal of the Korean Vacuum Society
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    • v.18 no.1
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    • pp.66-72
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    • 2009
  • The detection methods are required to monitor and diagnose the abnormality on the insulation condition inside a gas-insulated switchgear (GIS). Due to a good sensitivity to the products decomposed by partial discharges (PDs) in $SF_6$ gas, the development of a SWNT gas sensor is actively in progress. However, a few numerical studies on the diffusion mechanism of the $SF_6$ decomposition products by PD have been reported. In this study, we modeled $SF_6$ decomposition process in a chamber by calculating temperature, pressure and concentration of the decomposition products by using a commercial CFD program in conjunction with experimental data. It was assumed that the mass production rate and the generation temperature of the decomposition products were $5.04{\times}10^{-10}$ [g/s] and over 773 K respectively. To calculate the concentration equation, the Schmidt number was specified to get the diffusion coefficient functioned by viscosity and density of $SF_6$ gas instead rather than setting it directly. The results showed that the drive potential is governed mainly by the gradient of the decomposition concentration. A lower concentration of the decomposition products was observed as the sensors were placed more away from the discharge region. Also, the concentration increased by increasing the discharge time. By installing multiple sensors the location of PD is expected to be identified by monitoring the response time of the sensors, and the information should be very useful for the diagnosis and maintenance of GIS.

Quantitative Assessment Technology of Small Animal Myocardial Infarction PET Image Using Gaussian Mixture Model (다중가우시안혼합모델을 이용한 소동물 심근경색 PET 영상의 정량적 평가 기술)

  • Woo, Sang-Keun;Lee, Yong-Jin;Lee, Won-Ho;Kim, Min-Hwan;Park, Ji-Ae;Kim, Jin-Su;Kim, Jong-Guk;Kang, Joo-Hyun;Ji, Young-Hoon;Choi, Chang-Woon;Lim, Sang-Moo;Kim, Kyeong-Min
    • Progress in Medical Physics
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    • v.22 no.1
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    • pp.42-51
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    • 2011
  • Nuclear medicine images (SPECT, PET) were widely used tool for assessment of myocardial viability and perfusion. However it had difficult to define accurate myocardial infarct region. The purpose of this study was to investigate methodological approach for automatic measurement of rat myocardial infarct size using polar map with adaptive threshold. Rat myocardial infarction model was induced by ligation of the left circumflex artery. PET images were obtained after intravenous injection of 37 MBq $^{18}F$-FDG. After 60 min uptake, each animal was scanned for 20 min with ECG gating. PET data were reconstructed using ordered subset expectation maximization (OSEM) 2D. To automatically make the myocardial contour and generate polar map, we used QGS software (Cedars-Sinai Medical Center). The reference infarct size was defined by infarction area percentage of the total left myocardium using TTC staining. We used three threshold methods (predefined threshold, Otsu and Multi Gaussian mixture model; MGMM). Predefined threshold method was commonly used in other studies. We applied threshold value form 10% to 90% in step of 10%. Otsu algorithm calculated threshold with the maximum between class variance. MGMM method estimated the distribution of image intensity using multiple Gaussian mixture models (MGMM2, ${\cdots}$ MGMM5) and calculated adaptive threshold. The infarct size in polar map was calculated as the percentage of lower threshold area in polar map from the total polar map area. The measured infarct size using different threshold methods was evaluated by comparison with reference infarct size. The mean difference between with polar map defect size by predefined thresholds (20%, 30%, and 40%) and reference infarct size were $7.04{\pm}3.44%$, $3.87{\pm}2.09%$ and $2.15{\pm}2.07%$, respectively. Otsu verse reference infarct size was $3.56{\pm}4.16%$. MGMM methods verse reference infarct size was $2.29{\pm}1.94%$. The predefined threshold (30%) showed the smallest mean difference with reference infarct size. However, MGMM was more accurate than predefined threshold in under 10% reference infarct size case (MGMM: 0.006%, predefined threshold: 0.59%). In this study, we was to evaluate myocardial infarct size in polar map using multiple Gaussian mixture model. MGMM method was provide adaptive threshold in each subject and will be a useful for automatic measurement of infarct size.