• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2005년도 추계 학술대회논문집
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• pp.11-19
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• 2005

First, methods of numerical analysis of gas-particle flows is classified into micro, meso and macro scale approaches based on the concept of multi-scale mechanics. Next, the explanation moves on to discrete particle simulation where motion of individual particles is calculated numerically using the Newtonian equations of motion. The author focuses on the cases where particle-to-particle interaction has significant effects on the phenomena. Concerning the particle-to-particle interaction, two cases are considered: the one is collision-dominated flows and the other is the contact-dominated flows. To treat this interaction mathematically, techniques named DEM(Distinct Element Method) or DSMC (Direct Simulation Monte Carlo) have been developed DEM, which has been developed in the field of soil mechanics, is useful for the contact -dominated flows and DSMC method, developed in molecular gas flows, is for the collision-dominated flows. Combining DEM or DSMC with CFD (computer fluid dynamics), the discrete particle simulation becomes a more practical tool for industrial flows because not only the particle-particle interaction but particle-fluid interaction can be handled. As examples of simulations, various results are shown, such as hopper flows, particle segregation phenomena, particle mixing in a rotating drum, dense phase pneumatic conveying, spouted bed, dense phase fluidized bed, fast circulating fluidized bed and so on.

• 산업경영시스템학회지
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• 제40권1호
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• pp.95-104
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• 2017

This paper deals with solution methods for discrete and multi-valued optimization problems. The objective function of the problem incorporates noise effects generated in case that fitness evaluation is accomplished by computer based experiments such as Monte Carlo simulation or discrete event simulation. Meta heuristics including Genetic Algorithm (GA) and Discrete Particle Swarm Optimization (DPSO) can be used to solve these simulation based multi-valued optimization problems. In applying these population based meta heuristics to simulation based optimization problem, samples size to estimate the expected fitness value of a solution and population (particle) size in a generation (step) should be carefully determined to obtain reliable solutions. Under realistic environment with restriction on available computation time, there exists trade-off between these values. In this paper, the effects of sample and population sizes are analyzed under well-known multi-modal and multi-dimensional test functions with randomly generated noise effects. From the experimental results, it is shown that the performance of DPSO is superior to that of GA. While appropriate determination of population sizes is more important than sample size in GA, appropriate determination of sample size is more important than particle size in DPSO. Especially in DPSO, the solution quality under increasing sample sizes with steps is inferior to constant or decreasing sample sizes with steps. Furthermore, the performance of DPSO is improved when OCBA (Optimal Computing Budget Allocation) is incorporated in selecting the best particle in each step. In applying OCBA in DPSO, smaller value of incremental sample size is preferred to obtain better solutions.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2015년도 제51회 KOSCO SYMPOSIUM 초록집
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• pp.173-175
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• 2015

We simulate the particle bed motions with combustion and reduction in steel making rotary kilns. The particle bed motions are simulated by a Lagrangian approach called Discrete Phase Model (DPM). To reduce the number of tracking particles, the Coarse Grain Model (CGM) was applied. The model for particle motions showed good agreements with experimental results. In addition to the particle motion, the combustion and reduction simulation was performed. The combustion and reduction simulation can consider heat, mass and momentum transfer between the gas phase and particle beds.

• 지질공학
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• 제5권2호
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• pp.155-165
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• 1995

열극암반내의 지하수유동 및 용질이동 해석을 위해서는 추계론적인(Simulation Techique) 3차원 불연속체 모형(Discrete Fracture Model)이 요구된다. Monte Carlo 모의기법(Simulation Techique)에 의해 구성된 추계론적 불연속체모형을 지하 유류저장공동의 기밀성평가를 위한 지하수유동 및 용질이동 모의에 적용하였다. 불연속체모형구성에 영향을 미치는 열극 특성요소는 방향서 및 크기로 분석되었으며, 구성도니 모형(Model)에서의 지하수유동에 영향을 미치는 요소는 투수성 열극밀도로 분석되었다. Particle Tracking 기법을 사용한 불연속체모형의 용질이동 모의에서는 열극의 투수성에 의해 이동경로 및 이동속도에 많은 차이가 관찰되었다. 검증된 추계론적 불연속체모형은 지하 유류저장공동 기밀성평가에 적용이 가능함이 부분적으로 인정되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권7호
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• pp.1802-1814
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• 2012

In order to guide users to select the most optimal access network in heterogeneous wireless networks, a network selection algorithm is proposed which is designed based on multi-objective discrete particle swarm optimization (Multi-Objective Discrete Particle Swarm Optimization, MODPSO). The proposed algorithm keeps fast convergence speed and strong adaptability features of the particle swarm optimization. In addition, it updates an elite set to achieve multi-objective decision-making. Meanwhile, a mutation operator is adopted to make the algorithm converge to the global optimal. Simulation results show that compared to the single-objective algorithm, the proposed algorithm can obtain the optimal combination performance and take into account both the network state and the user preferences.

• 한국분말재료학회지
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• 제22권5호
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• pp.337-343
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• 2015

Powder compaction is a continually and rapidly evolving technology where it is a highly developed method of manufacturing reliable components. To understand existing mechanisms for compaction, parameter investigation is required. Experimental investigations on powder compaction process, followed by numerical modeling of compaction are presented in this paper. The experimental work explores compression characteristics of soft and hard ductile powder materials. In order to account for deformation, fracture and movement of the particles, a discrete-finite element analysis model is defined to reflect the experimental data and to enable investigations on mechanisms present at the particle level. Effects of important simulation factors and process parameters, such as particle count, time step, particle discretization, and particle size on the powder compaction procedure have been explored.

• 한국분말야금학회:학술대회논문집
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• 한국분말야금학회 2006년도 Extended Abstracts of 2006 POWDER METALLURGY World Congress Part 1
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• pp.262-263
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• 2006

The free sintering of metallic powders blended with non sintering inclusions is investigated by the Discrete Element Method (DEM). Each particle, whatever its nature (metallic or inclusion) is modeled as a sphere that interacts with its neighbors. We investigate the retarding effect of the inclusions on the sintering kinetics. Also, we present a simple coarsening model for the metallic particles, which allows large particles to grow at the expense of the smallest.

• Geomechanics and Engineering
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• 제35권5호
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• pp.475-486
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• 2023

Ballast particles have an irregular shape and are discrete in nature. Due to the discrete nature of ballast, it exhibits complex mechanical behaviour under loading conditions. The discrete element method (DEM) can model the behaviour of discrete particles under a multitude of loading conditions. DEM is used in this paper to simulate a series of three-dimensional direct shear tests in order to investigate the shear behaviour of railway ballast and its interaction at the microscopic level. Particle flow code in three dimension (PFC3D) models the irregular shape of ballast particles as clump particles. To investigate the influence of particle size distribution (PSD), real PSD of Indian railway ballast specification IRS:GE:1:2004, China high-speed rail (HSR) and French rail specifications are generated. PFC3D built-in linear contact model is used to simulate the interaction of ballast particles under various normal stresses, shearing rate and shear box sizes. The results indicate how shear resistance and volumetric changes in ballast assembly are affected by normal stress, shearing rate, PSD and shear box size. In addition to macroscopic behaviour, DEM represents the microscopic behaviour of ballast particles in the form of particle displacement at different stages of the shearing process.

• 한국분무공학회지
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• 제16권1호
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• pp.37-43
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• 2011

The present study conducted computational simulation for multiphase flow in the flame spray coating process with commercially available Ni-Cr powders. The flows in a flame spray gun is characterized by very complex phenomena including combustion, turbulent flows, and convective and radiative heat transfer. In this study, we used a commercial computational fluid dynamics (CFD) code of Fluent (ver. 6.3.26) to predict gas dynamics involving combustion, gas and particle temperature distributions, and multi-dimensional particle trajectories with the use of the discrete phase model (DPM). We also examined the effect of particle size on the flame spray process. It was found that particle velocity and gas temperature decreased rapidly in the radial direction, and they were substantially affected by the particle size.

• 한국유체기계학회 논문집
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• 제15권1호
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• pp.27-35
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• 2012

A numerical simulation for particle collection efficiency in a wire-plate electrostatic precipitator (ESP) has been performed. Method of characteristics and finite differencing method (MOC-FDM) were employed to obtain electric field and space charge density, and lattice boltzmann method (LBM) was used to predict the Electrohydrodynamic (EHD) flow according to the ion convection. Large eddy simulation (LES) was considered for turbulent flow and particle simulation was performed by discrete element method (DEM) which considered field charging, electric force, drag force and wall-collision. One way coupling from FDM to LBM was used with small and low density particle assumption. When the charged particle collided with the collecting plate, particle-wall collision was calculated for re-entertainment effect and the effect of gravity force was considered.