• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.303-308
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• 2022

Simulating the heat transfer in a composite material is an important topic in material science. Difficulties arise from the fact that adjacent materials cannot match perfectly, resulting in discontinuity in the temperature variables. Although there have been several numerical methods for solving the heat-transfer problem in imperfect contact conditions, the methods known so far are complicated to implement, and the computational times are non-negligible. In this study, we developed a ResNet-type deep neural network for simulating a heat transfer model in a composite material. To train the neural network, we generated datasets by numerically solving the heat-transfer equations with Kapitza thermal resistance conditions. Because datasets involve various configurations of composite materials, our neural networks are robust to the shapes of material-material interfaces. Our algorithm can predict the thermal behavior in real time once the networks are trained. The performance of the proposed neural networks is documented, where the root mean square error (RMSE) and mean absolute error (MAE) are below 2.47E-6, and 7.00E-4, respectively.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.284-287
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• 2017

This paper introduces liquid crystal (LC) alignment and its electro-optical properties in the LC cells with silver nanowire (AgNW) networks. The AgNW network was used as an electrode of LC cell as a substitute for an indium-tin-oxide (ITO) film. LC alignment characteristics in the LC cell using AgNW networks, which have two different sheet resistances of $60{\Omega}/m^2$ and $80{\Omega}/m^2$, were observed. The LC alignment characteristics including pretilt angle, LC alignment state, and thermal stability are similar irrespective of sheet resistance of AgNW network. However, twisted-nematic (TN)-LC cell normally operated when using AgNW network with sheet resistance of $80{\Omega}/m^2$. Electrooptical properties of TN-LC cell exhibited competitive performance compared to those of TN-LC cell based on conventional ITO electrode, which allow new approaches to replace conventional ITO electrode in display technology.

• Proceedings of the Membrane Society of Korea Conference
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• 1996.10a
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• pp.86-87
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• 1996

IPN (Interpenetrating Polymer Network) is a mixture of two or more crosslinked polymers with physically interlocked network structures between the component polymers. IPN can be classified as an alloy of thermosets and has the characteristics of thermosets such as the thermal resistance and chemical resistance and also has the characteristics of polymer alloys with enhanced impact resistance and amphoteric properties. The physical interlocking during the synthesis restricts the phase separation of the component polymer with chemical pinning process, thus the control of morphology is possible through variations of the reaction temperature and pressure, catalyst concentration and crosslinking agent concentration. Finely dispersed domain structure can be obtained through IPN synthesis of polymer components with gross immiscibility. In membrane applications, particularly for the separation of liquid mixtures, crosslinked polymer component with specific affinity to the permeate is needed. With the presence of the permeant-inert polymer component, the mechanical strength and the selectivity of the membranes are enhanced by restricting the swelling of the transporting polymer component networks.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.4
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• pp.222-230
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• 2023

In the present work, the scale effect on the Boil-Off Rate (BOR) was investigated based on an analytical method to systematically evaluate the thermal performance of a Liquefied Natural Gas (LNG) Cargo Containment System (CCS). A two-dimensional thermal resistance network model was developed to accurately estimate the heat ingress into the CCS from the outside. The analysis was performed for the KC-1 LNG membrane tank under the IGC and USCG design conditions. The ballast compartment of both the LNG tank and cofferdam was divided into six sections and a thermal resistance network model was made for each section. To check the validity of the developed model, the analysis results were compared with those from existing literature. It was shown that the BOR values under the IGC and USCG design conditions were agreed well with previous numerical results with a maximum error of 1.03% and 0.60%, respectively. A SDR, the scale factor of the LNG CCS was introduced and the BOR, air temperature of the ballast compartment, and the surface temperature of the inner hull were obtained to examine the influence of the SDR on the thermal performance. Finally, a correlation for the BOR was proposed, which could be expressed as a simple formula inversely proportional to the SDR. The proposed correlation could be utilized for predicting the BOR of a full-scale LNG tank based on the BOR measurement data of lab-scale model tanks.

• Geomechanics and Engineering
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• v.10 no.1
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• pp.49-57
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• 2016

The high permeability-high strength concrete belongs to the typical of porous materials. It is mainly used in underground engineering for cold area, it can act the role of heat preservation, also to be the bailing and buffer layer. In order to establish a suitable model to predict the thermal conductivity and directly applied for engineering, according to the structure characteristics, the thermal conductivity predicting model was built by resistance network model of parallel three-phase medium. For the selected geometric and physical cell model, the thermal conductivity forecast model can be set up with aggregate particle size and mixture ratio directly. Comparing with the experimental data and classic model, the prediction model could reflect the mixture ratio intuitively. When the experimental and calculating data are contrasted, the value of experiment is slightly higher than predicting, and the average relative error is about 6.6%. If the material can be used in underground engineering instead by the commonly insulation material, it can achieve the basic requirements to be the heat insulation material as well.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.479-482
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• 2003

We propose a real time gas monitoring system for classifying various gases with different concentrations. Using thermal modulation of operating temperature of two sensors, we extract patterns of gases from the voltage across the load resistance. We adopt the relative resistance as a pre-processing method and an ART2 neural network as a pattern recognition method. The proposed method has been implemented in a real time embedded system with tin oxide gas sensors, TGS 2611, 2602 and an MSP430 ultra-low power microcontroller in the test chamber.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2106-2109
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• 2008

Nanofluids have been studied as possible alternatives for heat transfer fluids to improve the efficiency of heat exchangers. There are deviations of measured effective thermal conductivities between research-groups, and the mechanisms of the effective thermal conductivity enhancement of nanofluids are not confirmed yet. In this study, the effects of particle shape on the effective thermal conductivity enhancement are discussed and presented as a possible explanation of the deviations. The particle motion effect is found to be negligible for nanofluids of high aspect ratio cylindrical particles, which is believed to be important for nanofluids of spherical particles, while the percolation network formation and contact resistance play dominant roles in determining the effective thermal conductivity.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.1-8
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• 2004

In this paper, we propose neural network-based fault diagnosis method to diagnose of sensor in the gas monitoring system. In the proposed method, using thermal modulation of operating temperature of sensor, the signal patterns are extracted from the voltage of load resistance. Also, ART2 neural network is used for fault isolation. The performance and effectiveness of the proposed ART2 neural network based fault diagnosis method are shown by simulation results using real data obtained from the gas monitoring system.

• Korean Journal of Optics and Photonics
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• v.24 no.6
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• pp.342-346
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• 2013

We present the thermal analysis result of die bonding for a high power LED package using a metal hybrid silicone adhesive structure. The simulation structure consists of an LED chip, silicone die adhesive, package substrate, silicone-phosphor encapsulation, Al PCB and a heat-sink. As a result, we demonstrate that the heat generated from the chip is easily dissipated through the metal structure. The thermal resistance of the metal hybrid structure was 1.662 K/W. And the thermal resistance of the total package was 5.91 K/W. This result is comparable to the thermal resistance of a eutectic bonded LED package.

• 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.