Powder characteristics, such as density, size, shape, thermal properties, and surface area, are of significant importance in the powder bed fusion (PBF) process. The powder required is exclusive for an efficient PBF process. In this study, the particle size distribution suitable for the powder bed fusion process was derived by modeling the PBF product using simulation software (GeoDict). The modeling was carried out by layering sintered powder with a large particle size distribution, with 50 μm being the largest particle size. The results of the simulation showed that the porosity decreased when the mean particle size of the powder was reduced or the standard deviation increased. The particle size distribution of prepared titanium powder by the atomization process was also studied. This study is expected to offer direction for studies related to powder production for additive manufacturing.

PURPOSES: This study proposes a cohesive shrinkage particle model that can be used to simulate a variety of dynamic behaviors and phase changes of construction materials, including road subsidence and debris flow, and phase change curing, via discrete element method (DEM). METHODS : From the perspective of DEM modeling, the water-content-dependent characteristics of soil particles and related modeling techniques are reviewed from literature. The static friction, cohesion, and particle size change are considered as the major parameters that should be reflected in DEM modeling for a more realistic simulation. The relationships of water content with cohesive force and particle radius, as determined from experimental test results in the relevant study, are utilized to develop the cohesive shrinkage model. For each water content value, the snapshot in simulation is compared to that in the experimental study. RESULTS: The numerical simulation shows very good agreement with the experimental test in terms of overall sample radius and thickness change due to drying. However, the local curling of soil sample in the DEM simulation does not perfectly match that in the experimental test. CONCLUSIONS : The cohesive shrinking particle model seems to be good enough for simulating the volumetric and phase changes of soil samples due to drying. However, it seems necessary to consider both bonding and cohesive contact models in DEM modeling because the only cohesive contact model exhibited limitations in the simulation of curling and crack development.

This study investigated the effect of the grinding media of a ball mill under various conditions on the raw material of copper powder during the milling process with a simulation of the discrete element method. Using the simulation of the three-dimensional motion of the grinding media in the stirred ball mill, we researched the grinding mechanism to calculate the force, kinetic energy, and medium velocity of the grinding media. The grinding behavior of the copper powder was investigated by scanning electron microscopy. We found that the particle size increased with an increasing rotation speed and milling time, and the particle morphology of the copper powder became more of a plate type. Nevertheless, the particle morphology slightly depended on the different grinding media of the ball mill. Moreover, the simulation results showed that rotation speed and ball size increased with the force and energy.

입자기반 전산유체역학 기법은 유체역학에서의 라그란지안 접근법에 기반을 두고 있다. 입자기반 방식은 입자 각각이 물리량을 가지고 움직이며 이러한 입자의 움직임을 추적하는 방식으로 유체의 거동을 구현할 수 있다. 이러한 방식은 격렬한 움직임에 의한 자유표면 혹은 경계면의 운동 재현에 우수성이 있으나 연속체역학을 위반할 수 있다는 문제점 역시 포함하고 있다. 이를 반대로 말하자면 특별한 조치를 취하지 않는 경우에는 연속체가 아닌 물질에 대한 구현이 매우 쉽게 가능하다는 것이기도 하다. 이에 따라, 기존의 유체에서 사용되는 입자기반 전산해석방식을 지배방정식 단계에서부터 고체입자형으로 변형이 가능하다는 것을 알 수있다. 본 연구에서는 입자기반 전산해석방식을 고체입자에 알맞은 형태로 변환하였다. 변환을 위해 유체에서 사용되는 점성항을 제거하고 대신 마찰항을 추가하였다. 본 연구에서 개발된 고체입자형 전산해석 프로그램을 이용하여 고체입자의 붕괴를 구현하였으며 이를 유체입자 붕괴와의 비교를 통해 입증하였다. 또한 유체입자가 가질 수 없는 고체입자만의 특성인 안식각을 구현하여 고체입자를 위한 입자기반 전산해석 프로그램을 완성하였다.

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

Particle morphology change and different experimental condition analysis during composite fabrication process by traditional ball milling with discrete element method (DEM) simulation were investigated. A simulation of the three dimensional motion of balls in a traditional ball mill for research on the grinding mechanism was carried out by DEM simulation. We studied the motion of the balls, the ball behavior energy and velocity; the forces acting on the balls were calculated using traditional ball milling as simulated by DEM. The effect of the operational variables such as the rotational speed, ball material and size on the flow velocity, collision force and total impact energy were analyzed. The results showed that increased rotation speed with interaction impact energy between balls and balls, balls and pots and walls and balls. The rotation speed increases with an increase of the impact energy. Experiments were conducted to quantify the grinding performance under the same conditions. Furthermore, the results showed that ball motion affects the particle morphology, which changed from irregular type to plate type with increasing rotation speed. The evolution was also found to depend on the impact energy increase of the grinding media. These findings are useful to understand and optimize the particle motion and grinding behavior of traditional ball mills.

The purpose of this paper was to apply and express to a particle production system based on mathematical models to raise a cloud of spray. It was used that a crash was used to conflict expanding wave generation model and applying the block cover. Also, we applied to the KD-tree in order to reduce trial search. The block cover was created with the creation on the phase of height values. The waves and wind made by character's emotions, which input use as the value. Reached a certain level in both cases, waves and waves are generated a cloud of spray by the collision. The repetition of generated waver was applied with the Windows function. Handling conflict is affected in a cloud of spray. Generated KD-Tree renewal grid is beyond the range in block cover and is not a uniform height. It is built that the processing of collision is not performed by the level on height of a wave. This process was designed by the best statistical analysis after reviewing sufficient factual nature. This paper is applied with a cloud of splay for emotional online games like game that tried to apply the spray can apply for the environment. If you use a physically-based model requires a lot of calculation time, the physically-based models ask a lot of complicated calculation time for solver this program and high-performance systems. However, a block-cover can be role of a very effective way for enough performance. Through the analysis result can be obtained a sufficient result in easy implementation of the cloud of spray

PURPOSES: Simulation of aggregate slump test using equivalent sphere particle in DEM and its validity evaluation against lab aggregate slump test METHODS : In this research, aggregate slump tests are performed and compared with DEM simulation. To utilize spheric particles in YADE, equivalent sphere diameter concept is applied. As verification measures, the volume in slump cone filled with aggregate is used and it is compared with volume in slump cone filled with equivalent sphere particle. Slump height and diameter are also used to evaluate the suggested numerical method with equivalent concept RESULTS : Simulation test results show good agrement with lab test results in terms of loose packing volume, height and diameter of slumped particle clump. CONCLUSIONS : It is concluded that numerical simulation using DEM is applicable to evaluate the effect of aggregate morphological property in loose packing and optimum gradation determination based on the aggregate slump test simulation result.

For precise property control of sintered products, it is important to understand accurately the packing density of the powder. We developed a packing simulation program that could make a packed bed of spherical particles having particle size distribution. In addition, the influence of the particle shape of the actual powder on the packing density was quantitatively analyzed. The predicted packing densities corresponded well to the actual data.

This study focuses on computational particle fluid dynamics (CPFD) modeling for the fast pyrolysis of biomass in a conical spouted bed reactor. The CPFD simulation was conducted to understand the hydrodynamics, heat transfer, and biomass fast pyrolysis reaction of the conical spouted bed reactor and the multiphase-particle in cell (MP-PIC) model was used to investigate the fast pyrolysis of biomass in a conical spouted bed reactor. A two-stage semi-global kinetics model was applied to model the fast pyrolysis reaction of biomass and the commercial code (Barracuda) was used in simulations. The temperature of solid particles in a conical spouted bed reactor showed a uniform temperature distribution along the reactor height. The yield of fast pyrolysis products from the simulation was compared with the experimental data; the yield of fast pyrolysis products was 74.1wt.% tar, 17.4wt.% gas, and 8.5wt.% char. The comparison of experimental measurements and model predictions shows the model’s accuracy. The CPFD simulation results had great potential to aid the future design and optimization of the fast pyrolysis process for biomass.