• Title/Summary/Keyword: 구 모델링

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Accuracy Assessment of the Upward Continuation using the Gravity Model from Ultra-high Degree Spherical Harmonics (초 고차항 구 조화 중력모델링에 의한 상향 연속의 정확도 검증)

  • Kwon Jay-Hyoun;Lee Jong-Ki
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.24 no.2
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    • pp.183-191
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    • 2006
  • The accuracy of the upward continuation is assessed through the gravity modeling using an ultra-high degree spherical harmonic expansion. The difficulties in the numerical calculation of Legendre function with ultra-high degree, underflow and/or overflow, is successfully resolved in 128 bit calculation scheme. Using the generated Legendre function, the gravity anomaly with spatial resolution of $1'{\times}1'$ on the geoid is calculated. The generated gravity anomaly is degraded and extracted with various noise levels and data intervals, then upward continuation is applied to each data sets. The comparison between the upward continued gravity disturbances and the directly calculated from the spherical harmonics showed that the accuracy on the direct method was significantly better than that of Poisson method. In addition, it is verified that the denser and less noised gravity data on the geoid generates better gravity disturbance vectors at an altitude. Especially, it is found that the gravity noise level less than 5mGal, and the data interval less than 2arcmin is necessary for next generation precision INS navigation which requires the accuracy of 5mGal or better at an altitude.

A Study on Installed Performance Analysis Modelling for a Helicopter Propulsion System Considering Intake Loss (흡입구 손실을 고려한 헬리콥터 추진시스템의 장착성능 해석 모델에 관한 연구)

  • Kong, Chang-Duk;Koo, Young-Ju;Kho, Seong-Hee;Ki, Ja-Young;Cha, Bong-Jun;Yu, Hyeok
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2008.05a
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    • pp.263-267
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    • 2008
  • In this work the realistic install performance analysis of a helicopter was performed together with power extraction enabling to operate auxiliary system as well as intake pressure loss, loss due to bleed air, etc. which must be considered in practical propulsion system's performance modelling to be installed to the airframe. The pressure loss occurring in intake was estimated from the intake performance map with relationships of Mach Number and pressure loss. In order to evaluate the proposed installed performance model, the experimental data for comparison must be needed when mounted in propulsion system. However because of lack of accessibility to such real data at the moment, the alternative way was made through comparison that the analysis results by the proposed model were compared with a wellknown commercial program GASTURB's analysis results. The validity of the proposed installed performance model was consequently confirmed because its average deferences from the GASTURB's results were within 0.5%.

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A Dynamic Analysis of Complex Structures with Joints (결합부가 있는 복합 구조물의 동적 해석)

  • 이재운;고강호;이수일;이장무
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 1994.10a
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    • pp.238-243
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    • 1994
  • 본 논문에서는 여러가지 형태의 결합부에 적용할 수 있는 일반적인 모델링 기법에 대하여 기술하였다. 기존의 해석방법은 특정한 결합부에만 적용이 가능하고 유한요소해석과 실험이 상호 보완적인 관계를 가진 형태의 해석방법이므로 실험이 불가능한 경우에 대해서는 적용하기 어려운 경우도 있다. 본 논문에서는 별도의 실험을 수행하지 않고 결합부 영역만을 상세하게 유한요소 모델링을 하여서 선택된 자유도에 대한 유연성 행렬(Flexibility Matrix)을 구하여 결합부의 특성을 구하는 일반적 모델링 기법을 제시하였다. 이 방법은 수치적으로 축약할 수 없는 모델-결합부가 접촉면(Contact Surface)을 가지고 있는 구조물을 효과적으로 축약할 수 있는 장점이 있다. 또한 모델링되는 결합부의 경계조건의 영향을 배제할 수 있으며 결합부에 존재하는 비선형성도 적정범위내에서 선형화할 수 있다. 제시한 일반적 모델링 기법을 나사 결합부, 접착제 결합부(Glued Joints), 볼트 결합부에 적용하여 결합부이 특성을 구하였으며 실험을 통하여 제시한 해석방법의 타당성을 검증하였다.

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An Automatic Modeling Method of Volume Data Using Metacubes (메타큐브를 이용한 볼륨 데이터 자동 모델링 방법)

  • 김은석;김재정
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.10b
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    • pp.499-501
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    • 2000
  • 음함수 곡면 모델의 대표적인 구조 요소인 메타볼은 다양한 형태의 곡면을 모델링하는데 뛰어난 성능을 갖는다[1]. 그러나 복잡한 형태의 물체는 곡면 뿐 아니라 평면적인 요소를 포함하기 때문에 메타볼만으로 부정형 물체를 모델링하는 데에는 많은 어려움이 따른다. 메타큐브는 메타볼의 장점을 수용하면서 적은 수의 데이터로 평면 형태의 물체가지 모델링할 수 있는 메타볼의 확장 형태로서, 두 개의 매개변수만으로 구에서 정육면체까지 자유로운 확장이 가능하다[2]. 본 논문은 메타큐브를 이용하여 볼륨 데이터로부터 3차원 물체를 자동 모델링하는 방법을 제안한다. 제안 방법은 볼륨 데이터의 형태에 기반하여 분할된 볼륨 트리를 이용하여 비교적 빠른 시간에 볼륨 데이터로부터 비슷한 형태의 3차원 물체를 재구성하는 메타큐브 집합을 추출한다. 다양한 볼륨데이타에 대한 실험 결과를 제시함으로써 제안 방법의 효용성을 증명한다.

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Mathematical Modelling of the H1N1 Influenza (신종 인플루엔자의 수학적 모델링)

  • Lee, Sang-Gu;Ko, Rae-Young;Lee, Jae-Hwa
    • Communications of Mathematical Education
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    • v.24 no.4
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    • pp.877-889
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    • 2010
  • Mathematical modelling is a useful method for reinterpreting the real world and for solving real problems. In this paper, we introduced a theory on mathematical modelling. Further, we developed a mathematical model of the H1N1 influenza with Excel. Then, we analyzed the model which tells us what role it can play in an appropriate prediction of the future and in the decision of accompanied policies.

Study on Installed Performance Simulation of Aircraft Gas-Turbine Engine Considering Inlet and Exhaust Losses (흡배기구 손실예측 및 이를 고려한 항공기 가스터빈의 장착 성능모사 연구)

  • Kong, Chang-Duk;Owino, George.Omollo.
    • Journal of the Korean Society of Propulsion Engineers
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    • v.10 no.4
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    • pp.100-108
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    • 2006
  • Experimental study has been a general way to evaluate inlet and exhaust duct performances, but this is not only costly but also time consuming. Computational simulation is hence replacing experimental study and consequently time and cost saving. This paper therefore aims to investigate typical component performance of the intake and exhaust ducts using 3D representation. In this study a specific inlet and exhaust was modeled and analyzed to estimate its losses and flow field using computational fluid dynamic program with flow visualization capabilities. A process that requires geometry data to be modeled. That allowed for possibility of design trade off in designing phase. Installed performance of a specific turbo shaft engine was finally evaluated with the estimated inlet, exhaust and other accessories losses.

A Development of a Seismic Vulnerability Model and Spatial Analysis for Buildings (건물에 대한 지진취약도 모델링 및 공간 분석)

  • Kim, Sang-Bin;Kim, Seong-Hoon
    • Journal of the Korea Convergence Society
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    • v.11 no.10
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    • pp.9-18
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    • 2020
  • The purpose of this study is to suggest a method of predicting seismic vulnerability and safety conditions of each building in a targeted area. The scope of this study includes 'developing a simulation model for precaution activities,' 'testing the validity of the developed model', From the facility point of view, target of this study is a local building system. According to the literature review, the number of earthquake prediction modeling and cases with GIS applied is extremely few and the results are not proficient. This study is conducted as a way to improve the previous researches. Statistic analyses are conducted using 348 domestic and international data. Finally, as a result of the series of statistical analyses, an adequate model is developed using optimization scale method. The ratio of correct expectation is estimated as 87%. In order to apply the developed model to predict the vulnerability of the several chosen local building systems, spatial analysis technique is applied. Gangnam-gu and Jongro-gu are selected as the target areas to represent the characteristics of the old and the new downtown in Seoul. As a result of the analysis, it is discovered that buildings in Gangnam-gu are relatively more dangerous comparing to those of Jongro-gu and Eunpyeong-gu.

Music Genre Classification based on Deep Neural Network using Spikegram (스파이크그램을 이용한 심층 신경망 기반의 음악 장르 분류)

  • Yun, Ho-Won;Jang, Woo-Jin;Shin, Seong-Hyeon;Jang, Won;Cho, Hyo-Jin;Park, Ho-Chong
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2017.06a
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    • pp.29-30
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    • 2017
  • 본 논문에서는 인간의 청각 기관을 모델링 한 스파이크그램 (spikegram)을 이용한 심층 신경망 기반의 음악 장르 분류 기술을 제안한다. 분류 대상은 GTZAN 데이터 세트의 10개 장르로 정의한다. 본 논문에서는 청각 기관의 인식 방법을 모델링한 방법을 이용하여 스파이크그램을 구하고, 스파이크그램에서 새로운 특성 벡터를 추출하는 방법을 제안한다. 제안하는 방법을 통해 심층 신경망에 적합한 특성 벡터를 구하고 이렇게 구한 특성 벡터로 신경망을 학습시켜 기존에 사용하던 다양한 방법들보다 높은 성능을 얻을 수 있다.

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