• Korean Journal of Materials Research
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• v.25 no.7
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• pp.322-329
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• 2015

The magnitude of wear should be at a minimum for numerous automobile and aeronautical components. In the current work, composites were prepared by varying the cenosphere content using the conventional stir casting method. A uniform distribution of particles was ensured with the help of scanning electron microscopy (SEM). Three major parameters were chosen from various factors that affect the wear. A wear test was conducted with a pin-on-disc apparatus; the controlling parameters were volume percentages of reinforcement of 5, 10, 15, and 20%, applied loads of 9.8, 29.42, and 49.03 N, and sliding speeds of 1.26, 2.51, and 3.77 m/s. The design of the experiments (DOE) was performed by varying the different influencing parameters using the full factorial method. An analysis of variance (ANOVA) was used to analyze the effects of the parameters on the wear rate. Using regression analysis, a response curve was obtained based on the experimental results. The parameters in the resulting curve were optimized using the Genetic Algorithm (GA). The GA results were compared with those of an alternate efficient algorithm called Neural Networks (NNs).

• Transactions of Materials Processing
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• v.17 no.3
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• pp.218-224
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• 2008

A recent trend in automotive parts has been an integration of sub-assemblies with unified shapes. Tube structures also have been integrated to one body structure by using a near net shape forming instead of adopting welding. A cylindrical elastomer-forming process can be utilized to form a steel tube compressed in a radial direction. This process has some advantages compared to a hydro-forming or a swaging process in the viewpoint of a lower investment and a higher productivity. In order to predict a feasible specification of products within a work capability of the elastomer-forming equipment developed previously, effects of geometrical parameters of a tube on its shape accuracy are examined. Two characteristic parameters to account for the shape accuracy are chosen. One is the curvature radius at the corner part and the other is the straight ratio of the formed region. Careful examination of two parameters has led that the shape accuracy can be easily predicted by the regression equation obtained from the response surface method.

• Journal of Electrochemical Science and Technology
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• v.10 no.3
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• pp.276-283
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• 2019

Nitinol is an alloy of nickel and titanium. Nitinol is one of the shape memory alloys(SMA) that are restored to a remembered form, changing the crystal structure at a given temperature. Because of these unique features, it is used in medical devices, high precision sensors, and aerospace industries. However, the conventional method of mechanical machining for nitinol has problems of thermal and residual stress after processing. Therefore, the electrochemical machining(ECM), which does not produce residual stress and thermal deformation, has emerged as an alternative processing technique. In addition, to replace the existing experimental planning methods, this study used deep neural network(DNN), which is the basis for AI. This method was shown to be more useful than conventional method of design of experiments(RSM, Taguchi, Regression) by applying deep neural network(DNN) to electrochemical machining(ECM) and comparing root mean square errors(RMSE). Comparison with actual experimental values has shown that DNN is a more useful method than conventional method. (DOE - RSM, Taguchi, Regression). The result of the machining was accurately and efficiently predicted by applying electrochemical machining(ECM) and deep neural network(DNN) to the shape memory alloy(SMA), which is a hard-mechinability material.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.11
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• pp.831-836
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• 2010

In this paper, Plasma Enhanced Chemical Vapor Deposition (PECVD) $SiO_2$ film properties are modeled using statistical analysis and neural networks. For systemic analysis, Box-Behnken's 3 factor design of experiments (DOE) with response surface method are used. For characterization, deposited film thickness and film stress are considered as film properties and three process input factors including plasma RF power, flow rate of $N_2O$ gas, and flow rate of 5% $SiH_4$ gas contained at $N_2$ gas are considered for modeling. For film thickness characterization, regression based model showed only 0.71% of root mean squared (RMS) error. Also, for film stress model case, both regression model and neural prediction model showed acceptable RMS error. For sensitivity analysis, compare to conventional fixed mid point based analysis, proposed sensitivity analysis for entire range of interest support more process information to optimize process recipes to satisfy specific film characteristic requirements.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1885-1890
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• 2008

3-D heterogeneous nucleation was simulated by classical molecular dynamics (MD), where the Lennard-Jones (LJ) gas and solid cluster-seed molecules have argon and aluminum properties, respectively. There are three shapes of cluster-seeds, cube, rod, and sphere, and three classes of masses and the simulation took place under nine supersaturation ratios, making a total of 81 calculations. Results show that the dimension of the cluster-seed highly affects the rates of cluster development. In order to analyze heterogeneous nucleation above and below the critical supersaturation ratio, growth rate and liquefaction rate were separately defined to supplement the investigation. Design of experiments (DOE) was used for analysis which displayed that the shape and mass of the cluster-seed are prominent for the growth rate, while the supersaturation ratio is most significant followed by the mass for liquefaction rate. The significance of the supersaturation ratio for overall liquefaction suggests that thermal diffusion is more dominant than mass interactions for this system.

• 한국신재생에너지학회:학술대회논문집
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• 2006.11a
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• pp.105-108
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• 2006

The fuel cell is one of the promising environment-friendly energy sources for the next generation. The fuel cell provides good energy efficiency above 40% without pollution or noise. Different fuel cell types are usually distinguished by the kind of electrolyte. Among these, the proton exchange membrane fuel cell (PEMFC) has advantages of high power density. low operating temperature, relatively quick start-up, and rapid response to varying loads. The bipolar plate is a major component of the PEM fuel cell stack, and it takes a large portion of stack volume, weight and cost. In this study, as alternative materials for bipolar plate of PEM fuel cells, graphite composites were fabricated by compression molding and by machining. Graphite particles mixed with epoxy resin were used as the main substance to provide electric conductivity. Flow channels were fabricated by compression molding with design of experiments (DOE) to evaluate moldability. The cost for compression molding of graphite-composite bipolar plate was compared with machining cost to make the same bipolar plate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.787-794
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• 2010

This paper aims to evaluate the effect of each material ingredient on mechanical and dynamic performance and to determine an optimal mixing condition of a rubber granule layer. To minimize the required number of tests, the test matrix was established by using the design of experiments (DOE). The tensile tests were then performed to identify the mechanical properties. Also, to evaluate the dynamic performance that the IAAF has required for athletics tracks for athletes' safety and balance, a series of impact tests were performed by using the so-called the "artificial athlete" machine. Finally, the response surface methodology was used to decide the optimal mixing conditions needed to achieve a high level of mechanical properties and dynamic performance.

• Transactions on Electrical and Electronic Materials
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• v.15 no.2
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• pp.81-86
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• 2014

The process parameter in optimized KOH alkali activation of soft carbon series coke material in high purity was set with DOE experiments design. The activated carbon was produced by performing the activation process based on the set process parameters. The specific surface area was measured and pore size was analyzed by $N_2$ absorption method for the produced activated carbon. The surface functional group was analyzed by Boehm method and metal impurities were analyzed by XRF method. The specific surface area was increased over 2,000 $m^2/g$ as the mixing ratio of activation agent increased. The micro pores in $5{\sim}15{\AA}$ and surface functional group under 0.4 meq/g were obtained. The contents of the metal impurity in activated carbon which is the factor for reducing the electrochemical characteristics was reduced less than 100 ppm through the cleansing process optimization. The electrochemical characteristics of activated carbon in 38.5 F/g and 26.6 F/cc were checked through the impedance measuring with cyclic voltammetry scan rate in 50~300 mV/s and frequency in 10 mHz ~100 kHz. The activated carbon was made in the optimized activation process conditions of activation time in 40 minutes, mixing ratio of activation agent in 4.5 : 1.0 and heat treatment temperature over $650^{\circ}C$.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.4
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• pp.165-171
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• 2018

In this study, the shape of the flow control structure within a DVR was designed for heat dissipation of the CPU. The proposed design consists of three thin metal plates, which directly controls the air flow inside the DVR box and forces the air to pass through the CPU, thereby efficiently dissipating heat from the CPU. The shape of the structure was determined using parametric studies. To verify the design result, we carried out a three-dimensional time dependent numerical analysis using a commercial fluid dynamics analysis package FlowVision. As a result of experiments with a real DVR equipment, it is confirmed that the temperature of the CPU is significantly reduced compared to the initial model.

• Analytical Science and Technology
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• v.20 no.5
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• pp.370-382
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• 2007

In this study, solid-phase microextraction (SPME) technique using GC/FID was studied as a possible alternative to liquid-liquid extraction for the analysis of EGBE, DGBE, DBM and TGME in water, and an optimization condition of trace analysis of EGBE, DGBE, DBM and TGME using the factorial design was described. Experiments used a fractional factorial design method followed by central composite design allowing optimization of a number of factors as well as statical analysis of results. The response surface analysis showed that the extraction efficiency can be described by a second-order polynomial equation in which the salts concentration, extraction temperature, extraction time and sonication time are the major influences. Using DOE, a new data-dependent method was developed that improved the quantity of confidently analyzed EGBE, DGBE, DBM and TGME in water samples.