• 한국측량학회지
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• 제39권2호
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• pp.93-101
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• 2021

Recently, with the urban redevelopment and the spread of the planned cities, there is increasing interest in the wind environment, which is related not only to design of buildings and landscaping but also to the comfortability of pedestrians. Numerical analysis for wind environment prediction is underway in many fields, such as dense areas of high-rise building or composition of the apartment complexes, a precisive 3D building model is essentially required in this process. Many studies conducted for wind environment analysis have typically used the method of creating a 3D model by utilizing the building layer included in the GIS (Geographic Information System) data. These data can easily and quickly observe the flow of atmosphere in a wide urban environment, but cannot be suitable for observing precisive flow of atmosphere, and in particular, the effect of a complicated structure of a single building on the flow of atmosphere cannot be calculated. Recently, drone photogrammetry has shown the advantage of being able to automatically perform building modeling based on a large number of images. In this study, we applied photogrammetry technology using a drone to evaluate the flow of atmosphere around two buildings located close to each other. Two 3D models were made into an automatic modeling technique and manual modeling technique. Auto-modeling technique is using an automatically generates a point cloud through photogrammetry and generating models through interpolation, and manual-modeling technique is a manually operated technique that individually generates 3D models based on point clouds. And then the flow of atmosphere for the two models was compared and analyzed. As a result, the wind environment of the two models showed a clear difference, and the model created by auto-modeling showed faster flow of atmosphere than the model created by manual modeling. Also in the case of the 3D mesh generated by auto-modeling showed the limitation of not proceeding an accurate analysis because the precise 3D shape was not reproduced in the closed area such as the porch of the building or the bridge between buildings.

• Composites Research
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• 제26권6호
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• pp.363-372
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• 2013

RTM (Resin Transfer Molding) 공정을 수치해석하기 위해 Level set 방법과 결합된 확장 유한 요소 법을 적용하였다. 유동 전면 부에서 비연속적인 구배를 가지는 압력을 계산하기 위해 확장 유한 요소 법을 이용하여 계산의 정밀성을 높였다. 확장 유한 요소 법에 이용되는 확장 형상 함수는 Level set 값을 이용하여 정의하였다. 이 확장 형상 함수는 요소를 통과하는 수지 유동 전면부의 위치를 반영할 수 있다. 게다가 Level set 법이 금형 충전 동안 수지 유동 전면부의 위치를 계산할 때 적용되었다. 수지 유동 전면부의 위치를 계산하는 미분방정식은 내연적 특성 Galerkin 유한 요소 법을 적용하여 풀었다. 선형 시스템 계산에서는 IPSAP의 다중 프론트 솔버를 이용한다. 본 연구에서 계산한 해석 값은 이론 값과 비교하여 검증하였다. 계산 효율을 높이기 위해 확장 유한 요소 법과 Level set 방법의 국소화 기법이 제안되었다. 이 기법은 계산 영역을 수지 유동 전면 부 근처의 영역으로 축소한다. 그러므로 전체 계산 양은 최소화될 수 있었다. 이 기법의 계산 효율은 채널 유동 모델을 이용하여 평가된다. 본 연구의 해석 능력을 보여주기 위해 몇 가지 적용 예제를 계산하였다. 첫 번째 예제를 이용해서 복잡하게 흘러가는 수지 전면부의 갈라짐과 합쳐지는 현상 해석하였다. 그리고 금형 내부의 Race-tracking 효과와 기공 생성 현상을 확인하기 위해 복잡한 모양의 구조물을 시뮬레이션 하였다.

• 방송공학회논문지
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• 제20권1호
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• pp.40-47
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• 2015

본 논문은 비디오 스트리밍 서비스를 위한 MMT (MPEG Media Transport) 시스템에서 제공하는 서비스 방식 중 노력형 서비스(Best-effort service)의 QoS 향상에 대한 연구이다. 퍼클래스(per-class), 퍼플로우(per-flow), 그리고 노력형 서비스와 같은 MMT 서비스 종류 중, 다른 서비스와는 달리 노력형 서비스는 보장된 대역폭을 제공받지 못한다. 따라서, 서비스 우선순위가 가장 낮은 노력형 서비스는 상대적으로 낮은 수준의 영상 서비스를 제공받게 된다. 본 논문에서는 위와 같은 노력형 서비스의 제한된 대역폭의 한계를 극복하기 위해 전송 비트율이 낮은 저해상도의 영상을 전송하고 상향표본화(Upsampling)하는 방식을 연구하고 실험 결과를 통해 전달된 영상의 화질 측면에서 제안하는 방식의 타당성을 증명한다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집E
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• pp.386-391
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• 2001

A finite element code based on P2P1 tetra element has been developed for the large eddy simulation (LES) of turbulent flows around a complex geometry. Fractional 4-step algorithm is employed to obtain time accurate solution since it is less expensive than the integrated formulation, in which the velocity and pressure fields are solved at the same time. Crank-Nicolson method is used for second order temporal discretization and Galerkin method is adopted for spatial discretization. For very high Reynolds number flows, which would require a formidable number of nodes to resolve the flow field, SUPG (Streamline Upwind Petrov-Galerkin) method is applied to the quadratic interpolation function for velocity variables, Noting that the calculation of intrinsic time scale is very complicated when using SUPG for quadratic tetra element of velocity variables, the present study uses a unique intrinsic time scale proposed by Codina et al. since it makes the present three-dimensional unstructured code much simpler in terms of implementing SUPG. In order to see the effect of numerical diffusion caused by using an upwind scheme (SUPG), those obtained from P2P1 Galerkin method and P2P1 Petrov-Galerkin approach are compared for the flow around a sphere at some Reynolds number. Smagorinsky model is adopted as subgrid scale models in the context of P2P1 finite element method. As a benchmark problem for code validation, turbulent flows around a sphere and a MIRA model have been studied at various Reynolds numbers.

• 한국전산유체공학회지
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• 제10권2호
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• pp.38-47
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• 2005

Substructuring methods are often used in finite element structural analyses. In this study a multi-level substructuring(MLSS) algorithm is developed and proposed as a possible candidate for finite element fluid solvers. The present algorithm consists of four stages such as a gathering, a condensing, a solving and a scattering stage. At each level, a predetermined number of elements are gathered and condensed to form an element of higher level. At the highest level, each sub-domain consists of only one super-element. Thus, the inversion process of a stiffness matrix associated with internal degrees of freedom of each sub-domain has been replaced by a sequential static condensation of gathered element matrices. The global algebraic system arising from the assembly of each sub-domain matrices is solved using a well-known iterative solver such as the conjugare gradient(CG) or the conjugate gradient squared(CGS) method. A time comparison with CG has been performed on a 2-D Poisson problem. With one domain the computing time by MLSS is comparable with that by CG up to about 260,000 d.o.f. For 263,169 d.o.f using 8 x 8 sub-domains, the time by MLSS is reduced to a value less than $30\%$ of that by CG. The lid-driven cavity problem has been solved for Re = 3200 using the element interpolation degree(Deg.) up to cubic. in this case, preconditioning techniques usually accompanied by iterative solvers are not needed. Finite element formulation for the incompressible flow has been stabilized by a modified residual procedure proposed by Ilinca et al.[9].

• 한국항공우주학회지
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• 제31권1호
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• pp.1-7
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• 2003

익형에 대한 공력 최적설계 프로그램을 개발하였으며, 점성 유동장에 대한 보다 정확한 정보를 설계에 반영하기 위하여 나비어-스톡스 방정식을 사용하였다. 최적설계 방법으로는 민감도 해석을 위하여 수정유용방향탐색방법(Modified Method of Feasible Directions, MMFD)을 사용하였으며 이동거리 계산을 위하여 다항식 보간법을 사용하였다. 또한 설계시간을 단축하기 위하여 MPI를 사용하여 병렬화하였다. 전체 유동장을 8개의 영역으로 분할하였으며 분할된 영역은 지정된 프로세서에 할당하여 계산을 수행하였다. 민감도 계산을 위하여 각 프로세서에 할당하여 계산을 수행하였다. 민감도 계산을 위하여 각 프로세서에 각 탐색방향을 할당하여 민감도를 병렬계산하였다. 본 연구의 수행 결과 양력은 허용한도 내의 일정한 값을 유지하는 가운데 항력이 감소된 최적화된 익형의 형상을 설계할 수 있었다.

• Membrane and Water Treatment
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• 제9권2호
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• pp.115-121
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• 2018

Artificial neural network (ANN) simulation is used to predict the dynamic change of permeate flux during wheat starch industry wastewater microfiltration with and without static turbulence promoter. The experimental program spans range of a sedimentation times from 2 to 4 h, for feed flow rates 50 to 150 L/h, at transmembrane pressures covering the range of $1{\times}10^5$ to $3{\times}10^5Pa$. ANN predictions of the wastewater microfiltration are compared with experimental results obtained using two different set of microfiltration experiments, with and without static turbulence promoter. The effects of the training algorithm, neural network architectures on the ANN performance are discussed. For the most of the cases considered, the ANN proved to be an adequate interpolation tool, where an excellent prediction was obtained using automated Bayesian regularization as training algorithm. The optimal ANN architecture was determined as 4-10-1 with hyperbolic tangent sigmoid transfer function transfer function for hidden and output layers. The error distributions of data revealed that experimental results are in very good agreement with computed ones with only 2% data points had absolute relative error greater than 20% for the microfiltration without static turbulence promoter whereas for the microfiltration with static turbulence promoter it was 1%. The contribution of filtration time variable to flux values provided by ANNs was determined in an important level at the range of 52-66% due to increased membrane fouling by the time. In the case of microfiltration with static turbulence promoter, relative importance of transmembrane pressure and feed flow rate increased for about 30%.

• 농업과학연구
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• 제46권1호
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• pp.67-78
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• 2019

The purpose of this study was to predict the water quality using the RNN (recurrent neutral network) and LSTM (long short-term memory). These are advanced forms of machine learning algorithms that are better suited for time series learning compared to artificial neural networks; however, they have not been investigated before for water quality prediction. Three water quality indexes, the BOD (biochemical oxygen demand), COD (chemical oxygen demand), and SS (suspended solids) are predicted by the RNN and LSTM. TensorFlow, an open source library developed by Google, was used to implement the machine learning algorithm. The Okcheon observation point in the Geum River basin in the Republic of Korea was selected as the target point for the prediction of the water quality. Ten years of daily observed meteorological (daily temperature and daily wind speed) and hydrological (water level and flow discharge) data were used as the inputs, and irregularly observed water quality (BOD, COD, and SS) data were used as the learning materials. The irregularly observed water quality data were converted into daily data with the linear interpolation method. The water quality after one day was predicted by the machine learning algorithm, and it was found that a water quality prediction is possible with high accuracy compared to existing physical modeling results in the prediction of the BOD, COD, and SS, which are very non-linear. The sequence length and iteration were changed to compare the performances of the algorithms.

• 물과 미래
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• 제25권3호
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• pp.65-77
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• 1992

본 연구의 목적은 기존에 발표된 이력현상 모형들을 분류하여 각 모형들의 특징을 비교하고 새로운 이력현상 모형의 형태에 대해 논하고자 한다. 기존에 발표된 이력현상 모형은 내삽모형, 축척모형과 영역모형으로 대별되며, 그중 영역모형만이 이론적 배경을 가지고 있다. 모형의 보정을 위해 한 개의 주곡선의 자료가 필요한 기존의 모형들의 타당성을 검증하기 위하야 Rubicon Sandy Loam과 Dune Sand의 실측자료와 비교하여 본 겨롸, 이들 모형들은 실측자료를 잘 모사할 수 없음을 알 수 있었다. 따라서 새로운 모형의 형태의 가능성을 종속여역모형에서 찾을수 있으며, 종속영역모형주에서도 순수한 매체에 대해 공극으로 공기의 진입에 대한 이웃하는 공극들의 방해효과의 정도를 설명하는 가중치를 도입한 모형(Model III-1, Mualem, 1984)을 단순화시키기 위해 이 모형에 적절한 가정을 부가한 형태의 모형이 새로운 형태의 모형에 대한 하나의 대안이 될 수 있음을 본 연구는 제시하고 있다.

• 한국유체기계학회 논문집
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• 제5권3호
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• pp.40-45
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• 2002

Since the previous cut-and-try design algorithm requires much cost and time, the automated design technique with the CFD and optimum design algorithm has recently been concerned. In this work, the Navier-Stokes equation was solved to gain more detailed viscous flow information of cascade with rotor-stator interactions. The H-grid embedded by O-grid was generated to obtain more accurate solution by eliminating the branch cut of H-grid near airfoil surface. To handle the relative motion of the rotor to the stationary stator, the sliding multiblock method was applied and the cubic-spline interpolation was used on the block interface boundary. To validate present procedure, the time-averaged aerodynamic loads were compared with experimeatal data. A good agreement was obtained. The Modified Method of Feasible Direction (MMFD) was used to carry out the sensitivity analysis of the change of aerodynamic performance by the changes of the cascade geometry. The present optimization of the cascade gave a dramatic reduction of the drag while the lift maintains at the value within the user-specified tolerance.