• 대한기계학회논문집B
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• 제23권9호
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• pp.1178-1184
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• 1999

The in-cylinder flow field of gasoline engine comprises unsteady compressible turbulent flows caused by the intake port, combustion chamber geometry and the change of the spatial shape. Thus the quantitative analysis of the in-cylinder bulk flow plays an important role in the improvement of engine performances and the reduction of exhaust emission. The influences of tumble intensifying valve (TIV) and swirl intensifying valve (SIV), and various intake-flow conditions are compared with the tumble ratio obtained by the measured results of the in-cylinder gas flow. In order to obtain the quantitative analysis of the in-cylinder gas flows of gasoline engine this investigation applied the particle tracking method to the analysis of gas flow characteristics. Various intake conditions such as tumble and swirl intensifying valve, the deactivated condition of one valve among two intake valves, and the other factors of gas flow are considered.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2796-2798
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• 2005

This Paper presents a method that a mobile robot can track persons in complex environment using particle filters. The topic of person following using mobile robot is researched in many different areas. The main problems of following a person are real time constraint, motion change of person during the tracking and occlusion with other objects. We present appearance adaptive models in a particle filter to realize robust visual tracking algorithm. Adaptive appearance model can handle occlusion with other people while target is moving.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2007년도 춘계 학술대회논문집
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• pp.53-57
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• 2007

The quality of chaotic mixing in square cavity flow was studied numerically by CFD simulation and particle tracking technique. The chaotic mixing was generated by using time-periodic electro-osmotic flow. Finite Volume Method (FVM) was employed to get the stretching and folding field in cavity domain. With adjusting the initial condition of concentration distribution, the best values of modulation period and Peclet number which gave us good mixing performance was determined precisely. From $Poicar{\acute{e}}section$and Lyapunov exponents for characteristic trajectories we find that mixing performance also depends on modulation period. The higher value of modulation period, the better mixing performance wag achieved in this case. Furthermore, the results for tracking particle trajectories were also compared between using of Bilinear Interpolation and Higher-order scheme. The values of modulation period for obtaining best mixing effect were matched between using FVM and particle tracking techniques.

• Journal of Mechanical Science and Technology
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• 제15권1호
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• pp.108-116
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• 2001

The in-cylinder flow field of gasoline engine comprises unsteady compressible turbulent flows caused by the intake port, combustion chamber geometry. Thus, the quantitative analysis of the in-cylinder flow characteristics plays an important role in the improvement of engine performances and the reduction of exhaust emission. In order to obtain the quantitative analysis of the in-cylinder gas flows for a gasoline engine, the single-frame particle tracking velocimetry was developed, which is designed to measure 2-dimensional gas flow field. In this paper, influences of the swirl and tumble intensifying valves on the in-cylinder flow characteristics under the various intake flow conditions were investigated by using this PTV method. Based on the results of experiment, the generation process of swirl and tumble flow in a cylinder during intake stroke was clarified. Its effect on the tumble ratio at the end of compression stroke was also investigated.

• Nuclear Engineering and Technology
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• 제38권8호
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• pp.763-778
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• 2006

Injection of microbubbles within the turbulent boundary layer has been investigated for several years as a method to achieve drag reduction. However, the physical mechanism of this phenomenon is not yet fully understood. Experiments in a channel flow for single phase (water) and two phase (water and microbubbles) flows with various void fraction values are studied for a Reynolds number of 5128 based on the half height of the channel and bulk velocity. The state-of-the art Particle Tracking Velocimetry (PTV) measurement technique is used to measure the instantaneous full-field velocity components. Comparisons between turbulent statistical quantities with various values of local void fraction are presented to elucidate the influence of the microbubbles presence within the boundary layer. A decrease in the Reynolds stress distribution and turbulence production is obtained with the increase of microbubble concentration. The results obtained indicate a decorrelation of the streamwise and normal fluctuating velocities when microbubbles are injected within the boundary layer.

• 인터넷정보학회논문지
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• 제17권3호
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• pp.25-32
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• 2016

본 논문에서는 에지를 사용한 관측 모델과 파티클 필터를 이용하여 실시간으로 객체를 추적하는 방법을 제안한다. 논문에서 제안하는 방법은 먼저, 초기 프레임에서 추적하고자 하는 객체를 지정한다. 지정된 객체에 대해 에지 관측 모델과 N개의 파티클 필터 집합을 생성한다. 에지 관측 모델과 파티클의 8방향 에지 모델의 중간 거리 평균을 비교하여 가중치를 계산하고, 계산된 값으로 가중치를 업데이트한다. 업데이트된 가중치를 이용해 파티클들을 리샘플링한 후, 추적 객체의 상태인 현재 위치를 추정할 수 있다. 마지막으로 본 논문에서 제안하는 방법은 여러 실험 데이터를 이용하여 기존의 방법과의 비교분석을 통해 안정적인 추적에 대한 성능을 입증한다.

• 제어로봇시스템학회논문지
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• 제18권7호
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• pp.638-643
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• 2012

This paper presents an intelligent reduction method for external noise. The main idea comes from PSO-FCM (Particle Swam Optimization Fused fuzzy C-Means) clustering. The data of the target is transformed from the antenna coordinates to the vessel one and to the system coordinates. In the conversion, the overall noises hinder observer to get the exact position and velocity of the maneuvering target. While the filter is used for tracking system, unexpected acceleration becomes the main factor which makes the uncertainty. In this paper, the tracking efficiency is improved with the PSO-FCM and the compensation methodology. The acceleration is approximated from the external noise splitted by the proposed clustering method. After extracting the approximated acceleration, the rest in the noise is filtered by the filter and the compensation is added to after that. Proposed tracking method is applicable to the linear model and nonlinear one together. Also, it can do to the on-line system. Finally, some examples are provided to examine the reliability of the proposed method.

• 한국지능시스템학회논문지
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• 제19권4호
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• pp.586-591
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• 2009

본 논문에서는 Particle filter를 이용한 특징 벡터 기반 이동 물체 추적 알고리즘을 제안한다. 이를 위해, 첫 번째, RGB 칼라 모델을 이용하여 초기 이동 물체의 움직임 영역(blob)을 추출하고, KLT-알고리즘을 이용하여 입력 영상에 대한 특징 벡터를 구한다. 그 다음, 초기 추출된 이동 물체의 움직임 영역에 이 특징 벡터를 매칭시켜 1차 특징 벡터를 구한다. 두 번째로, RGB와 HSI 칼라모델을 이용하여 이동 물체의 움직임 영역을 추출하고, 앞서 구한 1차 특징 벡터에 Snake 알고리즘을 적용함으로써 새로운 특징 벡터를 구한다. 그 다음, 기 추출된 이동 물체의 움직임 영역에 이 새롭게 구한 특징 벡터를 매칭시켜 2차 특징 벡터를 구한다. 최종적으로, 2차 특징 벡터에 Particle filter를 적용함으로써 본 논문에서 제안한 이동물체를 추적하는 알고리즘을 완성한다. 마지막으로, 본 논문에서 제안한 알고리즘은 복잡하고 다양한 환경에서 실험을 통해 그 응용 가능성을 증명한다.

• Nuclear Engineering and Technology
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• 제53권7호
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• pp.2334-2340
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• 2021

Radioactive particle tracking (RPT) is a minimally invasive nuclear technique that tracks a radioactive particle inside a volume of interest by means of a mathematical location algorithm. During the past decades, many algorithms have been developed including ones based on artificial intelligence techniques. In this study, RPT technique is applied in a simulated test section that employs a simplified mixer filled with concrete, six scintillator detectors and a¹³⁷Cs radioactive particle emitting gamma rays of 662 keV. The test section was developed using MCNPX code, which is a mathematical code based on Monte Carlo simulation, and 3516 different radioactive particle positions (x,y,z) were simulated. Novelty of this paper is the use of a location algorithm based on a deep learning model, more specifically a 6-layers deep rectifier neural network (DRNN), in which hyperparameters were defined using a Bayesian optimization method. DRNN is a type of deep feedforward neural network that substitutes the usual sigmoid based activation functions, traditionally used in vanilla Multilayer Perceptron Networks, for rectified activation functions. Results show the great accuracy of the DRNN in a RPT tracking system. Root mean squared error for x, y and coordinates of the radioactive particle is, respectively, 0.03064, 0.02523 and 0.07653.

• Nuclear Engineering and Technology
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• 제42권2호
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• pp.211-218
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• 2010

An analysis model on debris transport in the containment floor of pressurized water reactors is developed in which the flow field is calculated by Eulerian conservation equations of mass and momentum and the debris particles are traced by Lagrange equations of motion using the pre-determined flow field data. For the flow field calculation, two-dimensional Shallow Water Equations derived from Navier Stokes equations are solved using the Finite Volume Method, and the Harten-Lax-van Leer scheme is used for accuracy to capture the dry-to-wet interface. For the debris tracing, a simplified two-dimensional Lagrangian particle tracking model including drag force is developed. Advanced schemes to find the positions of particles over the containment floor and to determine the position of particles reflected from the solid wall are implemented. The present model is applied to calculate the transport fraction to the Hold-up Volume Tank in Advanced Power Reactors 1400. By the present model, the debris transport fraction is predicted, and the effect of particle density and particle size on transport is investigated.