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박권하(K. Park) 한국전산유체공학회 1997 한국전산유체공학회지 Vol.2 No.2
A new wall impaction model for diesel spray is described in this paper. The gas phase is modelled in terms of the Eulerian continuum conservation equations of mass, momentum, energy and fuel vapour fraction. The liquid phase is modelled following the discrete droplet model approach. The droplet parcel contains many thousands of drops assumed to have the same size, temperature and velocity components. The droplet parcel equations of trajectory, momentum, mass and energy are written in Lagrangian form. The new drop-wall interaction model is proposed, which is based on experimental investigations on individual drops, and it is applied for the general non-orthogonal grid. The model is then assessed through comparison with experiments over a wide range of test conditions of sprays. The results are in good agreement with experimental data.
분사압력변화가 분무특성에 미치는 영향에 관한 수치적 고찰
박권하(K. Park) 한국전산유체공학회 1997 한국전산유체공학회 학술대회논문집 Vol.1997 No.-
This paper addresses to the injection pressure effect on the diesel spray. The injection pressure is varied from lOMPa, in general system, upto 200MPa, in high pressured system in order to understand the effect.<br/> The gas phase is modelled in tenns of the Eulerian continuum conservation equations of mass, momentum, energy and fuel vapour fraction. The liquid phase is modelled following the discrete droplet model approach in Lagrangian form.<br/> The droplet distributions, vapor fractions and gas flows are analyzed in various injection pressure cases.
박권하(K. Park) 한국전산유체공학회 1997 한국전산유체공학회 학술대회논문집 Vol.1997 No.-
The droplets behavior impinged on various shaped lands of normal and angled flat or circular surface has been investigated. The droplet distributions were measured with shadowgraphy optical system and those data were compared with the results calculated with a new spray wall interaction model. The injection pressure and rate measured with experimental apparatus were employed on the calculation.<br/> The gas phase is modelled in terms of the Eulerian continuum conservation equations of mass, momentum, energy and fuel vapour fraction. The liquid phase is modelled following the discrete droplet model approach in Lagrangian form.<br/> The droplets distribution, vapor contour and gas flows are analyzed for various shaped lands.
박권하(K. Park) 한국전산유체공학회 1997 한국전산유체공학회지 Vol.2 No.2
A new wall impaction model for diesel spray is described in this paper. The gas phase is modelled in terms of the Eulerian continuum conservation equations of mass, momentum, energy and fuel vapour fraction. The liquid phase is modelled following the discrete droplet model approach. The droplet parcel contains many thousands of drops assumed to have the same size, temperature and velocity components. The droplet parcel equations of trajectory, momentum, mass and energy are written in Lagrangian form. The new drop-wall interaction model is proposed, which is based on experimental investigations on individual drops, and it is applied for the general non-orthogonal grid. The model is then assessed through comparison with experiments over a wide range of test conditions of sprays. The results are in good agreement with experimental data.
분사압력변화가 분무특성에 미치는 영향에 관한 수치적 고찰
박권하(K. Park) 한국전산유체공학회 1997 한국전산유체공학회지 Vol.2 No.2
High injection pressure system has been developed as a measure to reduce harmful exhaust gases. In order to understand the effect of pressure on diesel spray injection process, wide range of high injection pressure was tested. The gas phase is modelled by the Eulerian continuum conservation equations of mass, momentum, energy and fuel vapour fraction. The liquid phase is modelled following the discrete droplet model approach in Lagrangian form.<br/> The droplet distributions, vapor fractions and gas flows arc analyzed in various injection pressure cases. The distributions of spray and vapor increase and the Sauter mean diameter decreases with increasing injection pressure quickly in a low pressure area but slowly in a high pressure area.
영상 폐색영역 검출 및 해결을 위한 딥러닝 알고리즘 적용 가능성 연구
배경호(Kyoung-Ho Bae),박홍기(Hong-Gi Park) 한국산학기술학회 2019 한국산학기술학회논문지 Vol.20 No.11
최근 드론을 이용한 공간정보 구축이 활성화되면서 공간정보 산업발전에 많은 기여를 하고 있다. 하지만 드론 공간정보는 카메라의 중심투영에 의한 발생하는 폐색영역 뿐 아니라 가로수, 보행자, 현수막과 같은 적치물에 의한 폐색영역이 필연적으로 발생한다. 이러한 폐색영역을 효율적으로 해결하기 위한 다양한 방안이 연구되고 있다. 본 연구에서는 폐색영역 해결을 위해 원초적인 재촬영이 아닌 딥러닝 알고리즘을 적용하기 위한 다양한 알고리즘별 조사 및 비교연구를 수행하였다. 그 결과, 객체 검출 알고리즘인 HOG부터 기계학습 방법인 SVM, 딥러닝 방식인 DNN, CNN, RNN까지 다양한 모델들이 개발 및 적용되고 있으며, 이 중 영상의 분류, 검출에 가장 보편적이고 효율적인 알고리즘은 CNN기법임을 확인하였다. 향후 AI 기반의 자동 객체 탐지와 분류는 공간정보 분야에서 각광받는 최신 과학기술이다. 이를 위해 다양한 알고리즘에 대한 검토와 적용은 중요하다. 따라서, 본 연구에서 제시하는 알고리즘별 적용 가능성은 자동으로 드론 영상의 폐색영역을 탐지하고 해결할 수 있어 공간정보 구축의 시간, 비용, 인력에 대한 효율성 향상에 기여할 것으로 판단된다. Recently, spatial information is being constructed actively based on the images obtained by drones. Because occlusion areas occur due to buildings as well as many obstacles, such as trees, pedestrians, and banners in the urban areas, an efficient way to resolve the problem is necessary. Instead of the traditional way, which replaces the occlusion area with other images obtained at different positions, various models based on deep learning were examined and compared. A comparison of a type of feature descriptor, HOG, to the machine learning-based SVM, deep learning-based DNN, CNN, and RNN showed that the CNN is used broadly to detect and classify objects. Until now, many studies have focused on the development and application of models so that it is impossible to select an optimal model. On the other hand, the upgrade of a deep learning-based detection and classification technique is expected because many researchers have attempted to upgrade the accuracy of the model as well as reduce the computation time. In that case, the procedures for generating spatial information will be changed to detect the occlusion area and replace it with simulated images automatically, and the efficiency of time, cost, and workforce will also be improved.