• ETRI Journal
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• v.26 no.4
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• pp.371-374
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• 2004

We propose and demonstrate a fabrication method of chirped fiber gratings by a thermal diffusion process. The method could suggest a direction for a simple and cost-effective implementation of chirped fiber grating-based devices.

• International Journal of Concrete Structures and Materials
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• v.6 no.3
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• pp.177-186
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• 2012

The temperature distributions of concrete structures strongly depend on the value of thermal conductivity of concrete. However, the thermal conductivity of concrete varies according to the composition of the constituents and the temperature and moisture conditions of concrete, which cause difficulty in accurately predicting the thermal conductivity value in concrete. For this reason, in this study, back-propagation neural network models on the basis of experimental values carried out by previous researchers have been utilized to effectively account for the influence of these variables. The neural networks were trained by 124 data sets with eleven parameters: nine concrete composition parameters (the ratio of water-cement, the percentage of fine and coarse aggregate, and the unit weight of water, cement, fine aggregate, coarse aggregate, fly ash and silica fume) and two concrete state parameters (the temperature and water content of concrete). Finally, the trained neural network models were evaluated by applying to other 28 measured values not included in the training of the neural networks. The result indicated that the proposed method using a back-propagation neural algorithm was effective at predicting the thermal conductivity of concrete.

• Journal of computational fluids engineering
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• v.19 no.1
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• pp.47-56
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• 2014

Since a typical plate heat exchanger is made up of a huge number of unitary cells, it may be impossible to predict the aero-thermal performance of the full scale heat exchanger through three-dimensional numerical simulation due to the enormous amount of computing resources and time required. In the present study, a simple flow-network model using the friction factor correlation and a thermal-network model based on the effectiveness-number of transfer units (${\varepsilon}$-NTU) method has been developed. The complicated flow pattern inside the cross-corrugated heat exchanger has been modeled into flow and thermal networks. Using this model, the heat transfer between neighboring streams can be considered, and the pressure drop and the heat transfer rate of full-scale heat exchanger matrix are calculated. In the calculation, the aero-thermal performance of each unitary cell of the heat exchanger matrix was evaluated using correlations of the Fanning friction factor f and the Nusselt number Nu, which were calculated by unitary-cell CFD model.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.5
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• pp.52-59
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• 2008

The accuracy of the machine tools is degraded because of thermal error of structure due to thermal variation. To improve the accuracy of a machine tools, measurement and prediction of thermal error is very important. The main part of thermal source is spindle due to high speed with friction. The thermal error of spindle is very important because it is over 10% in total thermals errors. In this paper, the suitable thermal error prediction technology for machine tools with open architecture controller is developed and implemented to machine tools. Two thermal error prediction technologies, neural network and multi-linear regression, are investigated in several methods. The multi-linear regression method is more effective for implementation to CNC. The developed thermal error prediction technology is implemented on the internal function of CNC.

• Journal of the Korean Geotechnical Society
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• v.29 no.1
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• pp.93-107
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• 2013

Thermal conduction of the particulate composites or granular materials can be widely used in porous materials and geotechnical engineering. And it has continued to develop "effective thermal conductivity" of medium by modeling energy relationship among particles in medium. This study focuses on the development of the effective thermal conductivity at the unsaturated conditions of soils using the modified network model approach assisted by synthetic 3D random packed systems (DEM method, Discrete Element Method) at the particle scale. To verify the network model, three kinds of glass beads and the Jumunjin sand are used to obtain experimental values at various unsaturated conditions. The PPE (Pressure Plate Extractor) test is then performed to obtain SWCC (Soil-Water Characteristic Curve) of soil samples. In the modified network model, SWCC is used to adjust the equivalent radius of thermal cylinder at contact area between particles. And cutoff range parameter to define the effective zone is also adjusted according to the SWCC at given conditions. From a series of laboratory tests and the proposed network model, the modified network model which adopts a SWCC shows a good agreement in modeling thermal conductivity of granular soils at given conditions. And an empirical correlation between the fraction of the mean radius (${\chi}$) and thermal conductivity at given saturated condition is provided, which can be used to expect thermal conductivity of the granular soils, to estimate thermal conductivity of granular soils.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.1038-1044
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• 2013

A research on thermal analysis method is conducted for the characterization of heat generation during operation of Interior Permanent Magnet Synchronous Motor(IPMSM) for Light Railway Transits(LRT) in this paper. Efficient cooling of the heat generated in the IPMSM is important because the excessive heat generated from the winding, core and permanent magnet makes it harder for a long time continuous operation of IPMSM. Therefore, in order to analyze the heat generation characteristics of the 110kW-class IPMSM as advanced research for application the IPMSM to the cooling device, the heat transfer coefficients for each component of the 110 kW-class IPMSM were derived and the thermal equivalent network was configured to perform the thermal analysis in this study. Finally, the 110kW-class IPMSM prototype is made and a comparative verification between the test data and the thermal analysis results through its various performance tests are carried out.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.05a
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• pp.81-84
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• 2002

An approach for predicting the effective thermal conductivities of fiber-reinforce composite has been developed based on a thermal-electrical analogy. The unit cell of the composite laminate is divided into regular volume elements and the material properties have been given to each element. By constructing the series-parallel thermal resistance network, the thermal conductivities of composite both in-plane and out-of-plane direction have been predicted. Graphite/Epoxy composite is used for a balanced plain-weave composite laminate. By comparing the predicted results and the previous works, good agreement has been found.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.52-55
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• 2002

This paper examines the effective thermal conductivity of 3-D braided glass/epoxy composites. 3-D braided composites have a number of advantage over conventional laminate composites, including through-thickness reinforcement, and high damage tolerance and processability. The thermal properties of composites depend primarily on the microstructure of the braided preform and properties of constituent materials. A thermal resistance network model based on structure of the braided preform is proposed by using thermal-electrical analogy. In order to affirm the applicability theses solutions, thermal conductivities of 3-D braided glass/epoxy composites are measured

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.213-216
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• 2006

During the last decade several different methods have been proposed for the estimation of thermal deformations in the line heating process. These are mainly based on the assumption of residual strains in the heat-affected zone or simulated relations between heating conditions and residual deformations. However these results were restricted in the application from the too simplified heating conditions or the shortage of the data. The purpose of this paper is to develop a simulator of thermal deformation in the line heating using the artificial neural network. Two neural network predicting the maximum temperature and deformations at the heating line are studied. Deformation data from the line heating experiments are used for learning data for the network. It was observed that thermal deformation predicted by the neural network correlate well with the experimental result.

• Progress in Superconductivity and Cryogenics
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• v.24 no.4
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• pp.78-83
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• 2022

REBCO coated conductors are widely used for HTS power application, high magnetic field magnet application, and etc. A thermal stability of the REBCO conductor is essential for the operation of HTS-based device, and thermal conductivities of the conductor are relevant parameters for modeling cryogenic heat transfer. REBCO conductors consist of a REBCO layer, copper layers for electrical stabilization and a hastelloy substrate. At cryogenic temperature, thermal conductivity of copper and silver strongly depend on the purity of the material and the intensity of the magnetic field. In this study, thermal conductivities of the laminated composite structure of REBCO conductor are evaluated by using the thermal network model and the multidimensional heat conduction analysis. As a result, the thermal network model is applicable to REBCO conductors configured in series or parallel alone and multidimensional heat conduction analysis is necessary for complex cases of series and parallel configuration.