• Korean Journal of Materials Research
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• v.30 no.11
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• pp.573-580
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• 2020

YAG (Yttrium Aluminum Garnet, Y₃Al₅O₁₂) has excellent plasma resistance and recently has been used as an alternative to Y₂O₃ as a chamber coating material in the semiconductor process. However, due to the presence of an impurity phase and difficulties in synthesis and densification, many studies on YAG are being conducted. In this study, YAG powder is synthesized by an organic-inorganic complex solution synthesis method using PVA polymer. The PVA solution is added to the sol in which the metal nitrate salts are dissolved, and the precursor is calcined into a porous and soft YAG powder. By controlling the molecular weight and the amount of PVA polymer, the effect on the particle size and particle shape of the synthesized YAG powder is evaluated. The sintering behavior of the YAG powder compact according to PVA type and grinding time is studied through an examination of its microstructure. Single phase YAG is synthesized at relatively low temperature of 1,000 ℃ and can be pulverized to sub-micron size by ball milling. In addition, sintered YAG with a relative density of about 98 % is obtained by sintering at 1,650 ℃.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.123-131
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• 2015

Training neural networks is a complex task with great importance in the field of supervised learning. In the training process, a set of input-output patterns is repeated to an artificial neural network (ANN). From those patterns weights of all the interconnections between neurons are adjusted until the specified input yields the desired output. In this paper, a new hybrid algorithm is proposed for global optimization of connection weights in an ANN. Dynamic swarms are shown to converge rapidly during the initial stages of a global search, but around the global optimum, the search process becomes very slow. In contrast, the gradient descent method can achieve faster convergence speed around the global optimum, and at the same time, the convergence accuracy can be relatively high. Therefore, the proposed hybrid algorithm combines the dynamic particle swarm optimization (DPSO) algorithm with the backpropagation (BP) algorithm, also referred to as the DPSO-BP algorithm, to train the weights of an ANN. In this paper, we intend to show the superiority (time performance and quality of solution) of the proposed hybrid algorithm (DPSO-BP) over other more standard algorithms in neural network training. The algorithms are compared using two different datasets, and the results are simulated.

• Proceedings of the KAIS Fall Conference
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• 2000.10a
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• pp.39-41
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• 2000

Newly modified spray Pyrolysis system was developed to Produce ultra Pure and fine Powder by spray Pyrolysis Process. In this system, raw material solution was effectively atomized and sprayed into the reaction furnace. Also, thermal decomposition process fully completed in the three zone reaction furnace, and produced powder was effectively collected. A technology to reduce impurities in complex acid solution below 20ppm was also developed. The characteristics of produced powder were studied by changing the reaction conditions such as reaction temperature, the injection velocity of the solution and air, nozzle tip size and concentration of solution. The morphology of powder had spherical shape under the most experimental conditions, and the composition and the particle size distribution were almost uniform. Under the most experimental conditions average particle size of most produced powder was below 100nm.

• Korean Journal of Materials Research
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• v.29 no.6
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• pp.343-348
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• 2019

Structural and mechanical effects of the dynamical precipitation in two copper-base alloys have been investigated over a wide range of deformation temperatures. Basing upon the information gained during the experiment, also some general conclusion may be formulated. A one concerns the nature of dynamic precipitation(DP). Under this term it is commonly understood decomposition of a supersaturated solid solution during plastic straining. The process may, however, proceed in two different ways. It may be a homogeneous one from the point of view of distribution and morphological aspect of particles or it may lead to substantial difference in shape, size and particles distribution. The effect is controlled by the mode of deformation. Hence it seems to be reasonable to distinguish DP during homogeneous deformation from that which takes place in heterogeneously deformed alloy. In the first case the process can be analyzed solely in terms of particle-dislocation-particle interrelation. Much more complex problem we are facing in heterogeneously deforming alloy. Deformation bands and specific arrangement of dislocations in form of pile-ups at grain boundaries generate additional driving force and additional nucleation sites for precipitation. Along with heterogeneous precipitation, there is a homogeneous precipitation in areas between bands of coarse slip which also deform but at much smaller rate. This form of decomposition is responsible for a specially high hardening rate during high temperature straining and for thermally stable product of the decomposition of alloy.

• Advances in Computational Design
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• v.7 no.1
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• pp.1-17
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• 2022

In this study, a new strategy is presented to transmit the fundamental elastic beam problem into the modern optimization platform and solve it by using artificial intelligence (AI) tools. As a practical example, deflection of Euler-Bernoulli beam is mathematically formulated by 2nd-order ordinary differential equations (ODEs) in accordance to the classical beam theory. This fundamental engineer problem is then transmitted from classic formulation to its artificial-intelligence presentation where the behavior of the beam is simulated by using neural networks (NNs). The supervised training strategy is employed in the developed NNs implemented in the heuristic optimization algorithms as the fitness function. Different evolutionary optimization tools such as genetic algorithm (GA) and particle swarm optimization (PSO) are used to solve this non-linear optimization problem. The step-by-step procedure of the proposed method is presented in the form of a practical flowchart. The results indicate that the proposed method of using AI toolsin solving beam ODEs can efficiently lead to accurate solutions with low computational costs, and should prove useful to solve more complex practical applications.

• Journal of the Earthquake Engineering Society of Korea
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• v.27 no.6
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• pp.275-281
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• 2023

The demand for high-strength steel is rising due to its economic efficiency. Low-cycle fatigue (LCF) tests have been conducted to investigate the nonlinear behaviors of high-strength steel. Accurate material models must be used to obtain reliable results on seismic performance evaluation using numerical analyses. This study uses the combined hardening model to simulate the LCF behavior of high-strength steel. However, it is challenging and complex to determine material model parameters for specific high-strength steel because a highly nonlinear equation is used in the model, and several parameters need to be resolved. This study used the particle swarm algorithm (PSO) to determine the model parameters based on the LCF test data of HSA 650 steel. It is shown that the model with parameter values selected from the PSO accurately simulates the measured LCF curves.

• Journal of Radiation Industry
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• v.17 no.2
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• pp.191-197
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• 2023

Abstract KOMAC(Korea Multi-Purpose Accelerator Complex, KAERI) has been operating a 100 MeV proton accelerator and is going to produce ⁶⁸Ga isotope which is useful for diagnosis of cancer. So, it is necessary to develop a transport container for radio-activated targets. In this study, we carry out shielding analysis and structural analysis for the radio-activated target transport container using simulation programs. According to the Type A standard, the transport container includes an inner container and an overpack container. The main material of inner container is lead, and the shape is cylindrical with diameter of 152mm, height of 142mm and weight about 29 kg. It is planned to verify the possibility of field application through production of the transport container prototype in the future.

• Structural Engineering and Mechanics
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• v.91 no.1
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• pp.103-121
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• 2024

The smoothed particle hydrodynamics (SPH) method is a numerical technique used in dynamic analysis to simulate the fluid-like behavior of materials under extreme conditions, such as those encountered in explosions or high velocity impacts. In SPH, fluid or solid materials are discretized into particles. These particles interact with each other based on certain smoothing kernels, allowing the simulation of fluid flows and predict the response of solid materials to shock waves, like deformation, cracking or failure. One of the main advantages of SPH is its ability to simulate these phenomena without a fixed grid, making it particularly suitable for analyzing complex geometries. In this study, the structural damage to a masonry arch bridge subjected to blast loading was investigated. A high-fidelity micro-model was created and the explosives were modeled using the SPH approach. The Johnson-Holmquist II damage model and the Mohr-Coulomb material model were considered to evaluate the masonry and backfill properties. Consistent with the principles of the JH-II model, the authors developed a VUMAT code. The explosive charges (50 kg, 168 kg, 425 kg and 1000 kg) were placed in close proximity to the deck and pier of a bridge. The results showed that the 50 kg charges, which could have been placed near the pier by a terrorist, had only a limited effect on the piers. Instead, this charge caused a vertical displacement of the deck due to the confinement effect. Conversely, a 1000 kg TNT charge placed 100 cm above the deck caused significant damage to the bridge.

• Structural Engineering and Mechanics
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• v.68 no.3
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• pp.335-344
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• 2018

The execution of an experiment is a complex affair. It includes the preparation of test specimens, the measurement process itself and also the evaluation of the experiment as such. Financial requirements can differ significantly. In contrast, the cost of numerical simulations can be negligible, but what is the credibility of a simulated experiment? Discussions frequently arise concerning the methodology used in simulations, and particularly over the geometric model used. Simplification, rounding or the complete omission of details are frequent reasons for differences that occur between simulation results and the results of executed experiments. However, the creation of a very complex geometry, perhaps all the way down to the resolution of the very structure of the material, can be complicated. The subject of the article is therefore a means of creating the material structure of concrete contained in a test specimen. Because a complex approach is taken right from the very start of the numerical simulation, maximum agreement with experimental results can be achieved. With regard to the automation of the process described, countless material structures can be generated and randomly produced samples simulated in this way. Subsequently, a certain degree of randomness can be observed in the results obtained, e.g., the shape of the failure - just as is the case with experiments. The first part of the article presents a description of a complex approach to the creation of a geometry representing real concrete test specimens. The second part presents a practical application in which the numerical simulation of the compressive testing of concrete is executed using the generated geometry.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.35 no.3
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• pp.137-145
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• 2009

As an efficient controlled release system for rhBMP-2, a functional nanoparticle-hydrogel complex, incorporated with matrix metalloproteinase(MMP) sensitive peptide cross-linker, was developed and used as a bone transplant. In vivo bone formation was evaluated by soft x-ray, histology, alkaline phosphatase(ALP) activity and mineral contents analysis, based on the rat calvarial critical size defect(8mm in diameter) model. Significantly, effective bone regeneration was achieved with the rhBMP-2 loaded MMP sensitive hyaluronic acid(HA) based hydrogel-Nanoparticles(NP) complex, as compared to only MMP HA, the MMP HA-NP without rhBMP-2, or even with the rhBMP-2. These improvements included the formation pattern of bone and functional marrow, the degree of calcium quantification, and the ALP activity. These results indicate that the MMP sensitive HA with nano-particle complex can be a promising candidate for a new bone defect replacement matrix, and an enhanced rhBMP-2 scaffold.