• 한국전산유체공학회:학술대회논문집
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• 1999.11a
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• pp.201-206
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• 1999

현재 전세계적으로 과한 기술 연산용 리눅스 클러스터에 대한 연구와 개발이 진행되고 있는 추세이다. 본 논문에서는 펜티엄 프로세서와 알파 프로세서 및 고속 이더넷을 이용한 리눅스 클러스터를 구현하고 이를 전산유체역학 분야에 적용하기 위한 선행연구로서 NAS의 병렬 벤치마크 프로그램인 NPB를 사용하여 리눅스 클러스터들의 성능을 비교 분석하였다. NPB 프로그램은 전산유체역학 분야의 해석프로그램에서 널리 이용되는 알고리즘들로 구성된 벤치마크의 프로그램으로 이를 이용한 성능 평가의 결과는 향후 리눅스 클러스터에서 실제 전산유체역학 코드들의 성능을 나타내는 중요한 지표가 될 수 있다. NPB 벤치마크 결과 리눅스 클러스터는 고가의 슈퍼컴퓨터에 비해 전산유체역학 분야에서 높은 가격 대 성능비를 보임을 알 수 있으며 이를 통하여 저비용 슈퍼컴퓨팅의 가능성을 제시하고자 한다.

• 한국전산유체공학회:학술대회논문집
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• 2002.05a
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• pp.152-157
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• 2002

전산유체역학분야의 고속 연산을 위해서 병렬처리가 보편화되고 있으며 이러한 병렬해석은 주로 클러스터에서 저렴한 비용으로 수행되고 있다. 전산유체역학을 위한 클러스터 컴퓨터에서의 해석프로그램의 성능은 클러스터에 사용되는 프로세서의 성능뿐만 아니라 클러스터 내부의 통신 장비의 성능에 크게 좌우된다. 본 논문에서는 클러스터 컴퓨터의 구축에 널리 사용되고 있는 Myrinet2000, Gigabit Ethernet, Fast Ethernet 등의 네트웍 장치에 대해서 Netpipe, Linpack, NAS NPB, 그리고 MPINS2D Navier-Stokes 해석프로그램을 사용하여 성능을 비교하였다. 이를 통해서 향후 전산유체역학을 위한 클러스터 구축시 최대의 가격대 성능비를 얻을 수 있는 방법을 제시하고자 한다.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.1
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• pp.29-38
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• 2005

The fluid animation procedure consists of physical simulation and visual rendering. In the physical simulation of fluids, the most frequently used practices are the numerical simulation of fluid particles using particle dynamics equations and the continuum analysis of flow via Wavier-Stokes equation. Particle dynamics method is fast in calculation, but the resulting fluid motion is conditionally unrealistic The method using Wavier-Stokes equation, on the contrary, yields lifelike fluid motion when properly conditioned, yet the complexity of calculation restrains this method from being used in real-time applications. Global illumination is generally successful in producing premium-Duality rendered images, but is also excessively slow for real-time applications. In this paper, we propose a rapid fluid animation method incorporating enhanced particle dynamics simulation method and pre-integrated volume rendering technique. The particle dynamics simulation of fluid flow was conducted in real-time using Lennard-Jones model, and the computation efficiency was enhanced such that a small number of particles can represent a significant volume. For real-time rendering, pre-integrated volume rendering method was used so that fewer slices than ever can construct seamless inter-laminar shades. The proposed method could successfully simulate and render the fluid motion in real time at an acceptable speed and visual quality.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.5
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• pp.337-344
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• 2024

This study presents a deep learning-based framework to predict the aerodynamic performance of low Reynolds number airfoils. The framework employs a convolutional neural network (CNN) combined with a variational autoencoder (VAE) to efficiently handle large datasets. Moreover, the signed distance function is used as the network input to represent the airfoil configuration in the image data and parameterize the CNN. A novel generative model based on projection-based manifold learning is proposed to overcome the data mining limitation of computational fluid dynamics which may incur significant computational costs. The interpolation and extrapolation accuracy of the proposed framework is evaluated using the NACA 4-digit airfoil configuration.The results show improved accuracy via data augmentation performed by the proposed generative model.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.41 no.2
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• pp.117-124
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• 2017

The performance of the colored Gauss-Seidel solver on CPU and GPU was investigated for the two- and three-dimensional heat conduction problems by using different mesh sizes. The heat conduction equation was discretized by the finite difference method and finite element method. The CPU yielded good performance for small problems but deteriorated when the total memory required for computing was larger than the cache memory for large problems. In contrast, the GPU performed better as the mesh size increased because of the latency hiding technique. Further, GPU computation by the colored Gauss-Siedel solver was approximately 7 times that by the single CPU. Furthermore, the colored Gauss-Seidel solver was found to be approximately twice that of the Jacobi solver when parallel computing was conducted on the GPU.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.170-170
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• 2017

기후변화 따른 스마트팜 돈사 외부 환경의 변화에 대응하고, 사육 환경을 능동적으로 개선하기 위한 연구가 수행 중이다. 돈사 내 열전달 요소 간 상호 역학성 분석을 위해서 고려해야할 사항은 입기구, 보온 등, 열풍기, 단열제, 위치, 방향, 돈사의 연평균 온도, 습도, 연중 일사량, 가축의 열복사 등 상호 복잡하게 연관되어 있는 물리량이다. 돈사 전체 열손실, 자연발생 에너지량, 강제발생 에너지량, 난방용량 등을 고려한 순간 열부하 산정을 위한 여러 방법 중 우선적으로 CFD(Computational Fluid Dynamics)를 이용하였다. 순간 열부하 산정을 위한 해석 도구 선정에 있어서 다양한 유체 및 기체 전산 유체역학 Solver(Fluent, Open-FOAM, Blender)를 고려하였다. 공간 Mech를 수행하기 위한 도구로는 공개 소프트웨어 인 FreeFem++ 3.51-4 (http://www.freefem.org)를 이용하였다. 이 과정에서 일부 기체 (암모니아)의 농도를 난수로 변화시키는 기법을 적용하여 가상적으로 돈사의 환경을 Pseudo 시뮬레이션 하였다. 결과적으로 Fluent에 비하여 OpenFOAM을 이용하여 얻은 열유동의 방향(속도)과 크기 백터가 상대적으로 크게 나타났다. Fluent가 시계열 상에서 혼합 기체 물리량 변화를 무시할 수 있는 안정되고 균일한 환경에 적합하기 때문인 것으로 판단되었다. Blender의 경우 Lattice Boltzmann methods 과 Smoothed-particle hydrodynamics 방법을 이용한 유체/입자 동력학 모델링을 제공함에 있어 시각적 효과를 강조하는 기능에 중점을 두었다. Fluent와 Blender에서 제공하는 해석 연산 모듈의 정확성 검증을 위해선 공간 분해능을 높인 정밀 계측 시스템을 이용하여 검증할 필요가 있다. Open-FOAM를 이용한 열부하 분석 수행이 상대적으로 높은 절대값을 보이는 특성은 열부하 제어 시스템의 Overshoot를 유발할 가능성이 있으므로 이에 대한 해석 모델의 보정이 추가적으로 필요할 것이다. CFD의 한계인 시간 복잡도를 낮추고 상대적으로 높은 시계열 분해능을 확보할 경우 돈사 내 환기시스템에 맞는 소요 환기량 실시간 산정이 가능해지고 외부기상 및 돈사내부 복사열을 활용함과 동시에 돈군 순환에 상응하는 실시간 열부하 관리 시스템 도출이 가능할 것이다.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.9
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• pp.597-604
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• 2016

A parallel algorithm of bi-conjugate gradient method was developed based on CUDA for parallel computation of the incompressible Navier-Stokes equations. The governing equations were discretized using splitting P2P1 finite element method. Asymmetric stenotic flow problem was solved to validate the proposed algorithm, and then the parallel performance of the GPU was examined by measuring the elapsed times. Further, the GPU performance for sparse matrix-vector multiplication was also investigated with a matrix of fluid-structure interaction problem. A kernel was generated to simultaneously compute the inner product of each row of sparse matrix and a vector. In addition, the kernel was optimized to improve the performance by using both parallel reduction and memory coalescing. In the kernel construction, the effect of warp on the parallel performance of the present CUDA was also examined. The present GPU computation was more than 7 times faster than the single CPU by double precision.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6B
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• pp.379-385
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• 2012

Recent development of computing power and theoretical advances in computational fluid dynamics have made possible numerical simulations of water waves with full Navier-Stokes equations. In this study, an internal wave maker using the mass source function approach was combined with the level set finite element method for generation of waves. The model is first applied to the two-dimensional linear wave generation and propagation. Then, it is applied to the three-dimensional simulation of the same problem. To effectively utilize computational resources and enhance the speed of execution, parallel algorithms are developed and applied for the three-dimensional problem. The results of numerical simulations are compared with theoretical values and good agreements are observed.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.12
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• pp.991-997
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• 2014

This study investigated the swirling flow fields of a gun-type gas burner (GTGB) without a combustion chamber under cold flow conditions. Three velocity components and the static pressure were measured with a straight-type five-hole pressure probe (GHPP) using a non-nulling calibration method and compared with the results of an X-type hot-wire probe (X-probe) and computational fluid dynamics (CFD). The GHPP measured the velocity and static pressure for the swirling flow of the central region of the GTGB better than the X-probe but produced slightly worse results than the CFD.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.641-648
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• 2023

Recently, the rapid growth of artificial intelligence among the 4th industrial revolution has progressed based on the performance improvement of semiconductor, and circuit integration. According to transistors, which help operation of internal electronic devices and equipment that have been progressed to be more complicated and miniaturized, the control of heat generation and improvement of heat dissipation efficiency have emerged as new performance indicators. The DUT(Device Under Test) Shell is equipment which detects malfunction transistor by evaluating the durability of transistor through heat dissipation in a state where the power is cut off at an arbitrary heating point applying the rating current to inspect the transistor. Since the DUT shell can test more transistor at the same time according to the heat dissipation structure inside the equipment, the heat dissipation efficiency has a direct relationship with the malfunction transistor detection efficiency. Thus, in this paper, we propose various method for PCB configuration structure to optimize heat dissipation of DUT shell and we also propose various transformation and thermal analysis of optimal DUT shell using computational fluid dynamics.