• 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 Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1211-1217
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• 2001

This paper presnts a controller for the heat capacity of thermal storage systems using off-peak electricity which is composed of an identifier using neural networks and a storage time adjuster in order to store exactly the required thermal energy without loss. Since thermal storage systems have nonlinear characteristics and large time constant, even if we predict the heating load accurately, it is very difficult to store exactly the required thermal energy. Thus, in the neural network for the identifier, the adaptive learning rate for high learning speed and bit inputs based on state changes of thermal storage power source are used. Also a hardware for the controller using a microprocessor is developed. The performance of the proposed controller is shown by experiment.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.70-75
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• 2001

In metal cutting, the machining accuracy is more affected by thermal errors than by geometric errors. This paper models of the thermal errors for error analysis and develops on-the-machine measurement system by which the volumetric error are measured and compensated. The thermal error is modeled by means of angularity errors of a column and thermal drift error of the spindel unit which are measured by the touch probe unit with a star type styluses, a designed spherical ball arti-fact, and five gap sensors. In order to analyze the thermal characteristics under several operating conditions, experiments performed with the touch probe unit and five gap sensors on the vertical and horizontal machining centers.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.417-422
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• 2002

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric errors, thermally-induced errors, and the deterioration of the machine tools. Geometric and thermal errors of machine tools should be measured and compensated to manufacture high quality products. In metal cutting, the machining accuracy is more affected by thermal errors than by geometric errors. In this study, the compensation device and temperature-based algorithm have been implemented on the machining center in order to compensate thermal error of machine tools under the real-time. The thermal errors are predicted using the neural network and multi-regression modeling methods. In order to compensate thermal characteristics under several operating conditions, experiments performed with five gap sensors and manufactured compensation device on the horizontal machining center.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.1
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• pp.21-28
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• 2016

A typical heat exchanger, found in many industrial sites, is made up of a large number of unitary cells, which causes difficulties when carrying out full-scale three-dimensional numerical simulations of the heat exchanger to analyze the aero-thermal performance. In the present study, a three-dimensional numerical study using a porous media model was carried out to evaluate the performance of the heat exchanger modelled in two different ways : full-scale and simplified. The pressure drop in the air side and gas side along with the overall heat transfer rate were calculated using a porous media model and the results were then compared to results obtained with a one-dimensional flow network model. The comparison between the results for two different geometries obtained using a porous media model and a one-dimensional flow network model shows good agreement between the simplified geometry and the one-dimensional flow network model. The full-scale geometry shows reasonable differences caused by the geometry such as sudden expansion and contraction.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.2
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• pp.109-116
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• 1999

ZnO Varistor is an electronic ceramic device to absorb the surge voltage from low voltage to high. To investigate the puncture mechanism occurring in NnO varistor, the Voronoi simulation for formulating the relation between the applied voltage and the increase of the temperature inside grain is applied. The Voronoi network can realize the structure of the practical varistor better than the established simple network. Using the current through each grain and the voltage applied to the grain, Joule heating energy is calculated and the phenomenon that the puncture occurs can be analyzed quantitatively by simulating the electric and thermal characteristics according to the externally applied pulsed voltage.

• Macromolecular Research
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• v.15 no.3
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• pp.225-233
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• 2007

To improve the poor mechanical and low-temperature properties of glycidyl azide polymer (GAP)-based propellants, the addition of binders was investigated using GAP and flexible polymer backbone-structural polycaprolactone (PCP) at various weight(wt) ratios, and varying the ratio of Desmodur N-100 pluriisocyanate (N-100) to isophorone diisocyanate (IPDI). Using Gee's theory, the solubility parameter of the PCP network was determined, in order to elucidate the physical and chemical interaction between GAP and PCP. The structure of the binder networks was characterized by measuring the cross-link densities and molecular weights between cross-links ($M_c$) obtained by a swelling experiment using Flory-Rhener theory. The thermal and mechanical properties of the segmented block copolyurethane (GAP-b-PCP) binders prepared by the incorporation of PCP into the binder recipes were investigated, along with the effect of the different curatives ratios.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.5
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• pp.19-24
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• 2002

• Journal of the Microelectronics and Packaging Society
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• v.24 no.4
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• pp.91-95
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• 2017

Package-On-Package (PoP) technology is developing toward smaller form factors with high-speed data transfer capabilities to cope with high DDR4x memory capacity. The common application processor (AP) used for PoP devices in smartphones has the bottom package as logic and the top package as memory, which requires both thermally and electrically enhanced functions. Therefore, it is imperative that PoP designs consider both thermal and power distribution network (PDN) issues. Stacked packages have poorer thermal dissipation than single packages. Since the bottom package usually has higher power consumption than the top package, the bottom package impacts the thermal budget of the top package (memory). This paper investigates the thermal and electrical characteristics of PoP designs, particularly the bottom package. Findings include that via and dense via-cluster volume have an important role to lower thermal resistance to the motherboard, which can be an effective way to manage chip hot spots and reduce the thermal impact on the memory package. A Cu block and dense via-cluster layout with an optimal location are proposed to drain the heat from the chip hot spots to motherboard which will enhance thermal and electrical performance at the design stage. The analytical thermal results can be used for design guidelines in 3D packaging.

• Journal of Korean Society of Steel Construction
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• v.19 no.6
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• pp.695-702
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• 2007

The Thermal Prestressing Method for continuous composite girder bridges is a new design and construction method developed to induce initial composite stresses in the concrete slab at negative bending regions. Due to the induced initial stresses, prevention of tensile cracks at the concrete slab, reduction of steel girder section, and reduction of reinforcing bars are possible. Thus, the construction efficiency can be improved and the construction can be made more economical. The method for determining the optimum heating region of the thermal prestressing method has not been established although such method is essential for improving the efficiency of the design process. The trial-and-error method used in previous studies is far from efficient, and a more rational method for computing optimal heating region is required. In this study, an efficient method for determining the optimum heating region in using the thermal prestressing method was developed based on the neural network algorithm, which is widely adopted to pattern recognition, optimization, diagnosis, and estimation problems in various fields. Back-propagation algorithm, commonly used as a learning algorithm in neural network problems, was used for the training of the neural network. Through case studies of two-span and three-span continuous composite girder bridges using the developed procedure, the optimal heating regions were obtained.