• Journal of computational fluids engineering
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• v.10 no.4 s.31
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• pp.12-17
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• 2005

A computational study of evaluation of current turbulence models is performed for a better prediction of thermal stratification in an upper plenum of a liquid metal reactor. The turbulence models tested in the present study are the two-layer model, the shear stress transport (SST) model, the v2-f model and the elliptic blending mode(EBM). The performances of the turbulence models are evaluated by applying them to the thermal stratification experiment conducted at JNC (Japan Nuclear Corporation). The algebraic flux model is used for treating the turbulent heat flux for the two-layer model and the SST model, and there exist little differences between the two turbulence models in predicting the temporal variation of temperature. The v2-f model and the elliptic blending model better predict the steep gradient of temperature at the interface of thermal stratification, and the v2-f model and elliptic blending model predict properly the oscillation of the ensemble-averaged temperature. In general the overall performance of the elliptic blending model is better than the v2-f model in the prediction of the amplitude and frequency of the temperature oscillation.

• KIEE International Transactions on Electrophysics and Applications
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• v.3C no.1
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• pp.1-4
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• 2003

This paper presents an attempt to develop probabilistic multistress life models to evaluate the lifetime characteristics of epoxy-encapsulated magnet wire with heavy build polyurethane enamel. A set of accelerated life tests were conducted over a wide range of pulsating voltages, temperatures, and frequencies. Samples of fine gauge twisted pairs of the encapsulated magnet wire were tested us-ing a pulse endurance dielectric test system. An electrical-thermal lifetime function was combined with the Weibull distribution of lifetimes. The parameters of the combined Weibull-electrical-thermal model were estimated using maximum likelihood estimation. Likewise, a generalized electrical-thermal-frequency life model was also developed. The parameters of this new model were estimated using multiple linear regression technique. It was found in this paper that lifetime estimates of the two proposed probabilistic multistress life models are good enough. This suggests the suitability of using the general electrical-thermal-frequency model to estimate the lifetime of the encapsulated magnet wire over a wide range of voltages, temperatures and pulsating frequencies.

• Journal of The Korean Astronomical Society
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• v.36 no.1
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• pp.21-31
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• 2003

ASTRO-F /FIS will carry out all sky survey in the wavelength from 50 to 200 ${\mu}m$. At far infrared, stars and galaxies may not be good calibration sources because the IR fluxes could be sensitive to the dust shell of stars and star formation activities of galaxies. On the other hand, asteroids could be good calibration sources at far infrared because of rather simple spectral energy distribution. Recent progresses in thermal models for asteroids enable us to calculate the far infrared flux fairly accurately. We have derived the Bond albedos and diameters for 559 asteroids based on the IRAS and ground based optical data. Using these thermal parameters and standard thermal model, we have calculated the spectral energy distributions of asteroids from 10 to 200 ${\mu}m$. We have found that more than $70\%$ of our sample asteroids have flux errors less than $10\%$ within the context of the best fitting thermal models. In order to assess flux uncertainties due to model parameters, we have computed SEDs by varing external parameters such as emissivity, beaming parameter and phase integral. We have found that about 100 asteroids can be modeled to be better than $5.8\%$ of flux uncertainties. The systematic effects due to uncertainties in phase integral are not so important.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.2
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• pp.173-182
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• 2005

The Performance of U-tube ground heat exchanger for geothermal heat Pump systems depends on the thermal properties of the soil, as well as grout or backfill materials in the borehole. In-situ tests provide a means of estimating some of these properties. In this study, in-situ thermal response tests were completed on two vertical boreholes, 130 m deep with 62 mm diameter high density polyethylene U-tubes. The tests were conducted by adding a monitored amount of heat to water over a $17\~18$ hour period for each vertical boreholes. By monitoring the water temperatures entering and exiting the loop and heat load, overall thermal conductivity values of grout/soil formation were determined. Two parameter estimation models for evaluation of thermal response test data were compared when applied on the same temperature response data. One model is based on line-source theory and the other is a numerical one-dimensional finite difference model. The average thermal conductivity deviation between measured data and these models is of the magnitude $1\%$ to $5\%$.

• Structural Engineering and Mechanics
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• v.39 no.3
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• pp.317-338
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• 2011

Three-dimensional thermal and mechanical coupled finite element models are proposed to study the structural behaviours of shear connectors under fire. Concrete slabs, steel beams and shear connectors are modelled with eight-noded solid elements, and profiled steel deckings are modelled with eight-noded shell elements. Thermal, mechanical and geometrical nonlinearities are incorporated into the models. With the proper incorporation of thermal and mechanical contacts among steel beams, shear connectors, steel deckings and concrete slabs, both of the models are verified to be accurate after the validation against a series of push-out tests in the room temperature or under the standard fire. Various thermal and mechanical responses are also extracted and observed in details from the results of the numerical analyses, which gives a better understanding of the structural behavior of shear connectors under elevated temperatures.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1201-1204
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• 2004

This paper suggests a DCS (Distributed Control System) model for steam temperature system of the thermal power plant. The model calculated within sectional range is linear. In order to calculate mathematical models, the system is partitioned into two or three sectors according to its thermal conditions, that is, saturated water/steam and superheating state. It is divided into three sections; water supply, steam generation and steam heating loop. The steam heating loop is called 'superheater' or steam temperature system. Water spray supply is the control input. A first order linear model is extracted. For linear approach, sectional linearization is achieved. Modeling methodology is a decomposition-synthetic technique. Superheater is composed of several tube-blocks. For this block, linear input-output model is to be calculated. Each tiny model has its transfer function. By expanding these block models to total system, synthetic DCS linear models are derived. Control instrument include/exclude models are also considered. The resultant models include thermal combustion conditions, and applicable to practical plant engineering field.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.975-983
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• 2013

This study proposes a low order dynamic model of a building system in order to predict thermal behavior within a building and its energy consumption. The building system includes a thermally well-insulated room and an electric heater. It is modeled by a second order lumped RC thermal network based on the thermal-electrical analogy. In order to identify unknown parameters of the model, an experimental procedure is firstly detailed. Then, the different linear parametric models (ARMA, ARX, ARMAX, BJ, and OE models) are recalled. The parameters of the parametric models are obtained by the least square approach. The obtained parameters are interpreted to the parameters of the physically based model in accordance with their relationship. Afterwards, the obtained models are implemented in Matlab/Simulink(R) and are evaluated by the mean of the sum of absolute error (MAE) and the mean of the sum of square error (MSE) with the variable of indoor temperature of the room. Quantities of electrical energy and converted thermal energy are also compared. This study will permit a further study on Model Predictive Control adapting to the proposed model in order to reduce energy consumption of the building.

• Nuclear Engineering and Technology
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• v.48 no.3
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• pp.660-672
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• 2016

In Part I of this paper, the two-temperature homogenized model for the fully ceramic microencapsulated fuel, in which tristructural isotropic particles are randomly dispersed in a fine lattice stochastic structure, was discussed. In this model, the fuel-kernel and silicon carbide matrix temperatures are distinguished. Moreover, the obtained temperature profiles are more realistic than those obtained using other models. Using the temperature-dependent thermal conductivities of uranium nitride and the silicon carbide matrix, temperature-dependent homogenized parameters were obtained. In Part II of the paper, coupled with the COREDAX code, a reactor core loaded by fully ceramic microencapsulated fuel in which tristructural isotropic particles are randomly dispersed in the fine lattice stochastic structure is analyzed via a two-temperature homogenized model at steady and transient states. The results are compared with those from harmonic- and volumetric-average thermal conductivity models; i.e., we compare $k_{eff}$ eigenvalues, power distributions, and temperature profiles in the hottest single channel at a steady state. At transient states, we compare total power, average energy deposition, and maximum temperatures in the hottest single channel obtained by the different thermal analysis models. The different thermal analysis models and the availability of fuel-kernel temperatures in the two-temperature homogenized model for Doppler temperature feedback lead to significant differences.

• Journal of Mechanical Science and Technology
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• v.16 no.9
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• pp.1054-1064
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• 2002

Numerical prediction of welding-induced residual stresses using the finite element method has been a common practice in the development or refinement of welded product designs. Various researchers have studied several thermal models associated with the welding process. Among these thermal models, ramp heat input and double-ellipsoid moving source have been investigated. These heat-source models predict the temperature fields and history with or without accuracy. However, these models can predict the thermal characteristics of the welding process that influence the formation of the inherent plastic strains, which ultimately determines the final state of residual stresses in the weldment. The magnitude and distribution of residual stresses are compared. Although the two models predict similar magnitude of the longitudinal stress, the double-ellipsoid moving source model predicts wider tensile stress zones than the other one. And, both the ramp heating and moving source models predict the stress results in reasonable agreement with the experimental data.

• Journal of Aerospace System Engineering
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• v.10 no.4
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• pp.26-34
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• 2016

In a number of industries, porous insulations have been frequently used, reducing thermal insulation space through excellent performance of the thermal insulation's characteristics. This paper suggests an effective thermal conductivity prediction model. Firstly, we perform a literature review of traditional effective thermal conductivity prediction models and compare each model with experimental heat transfer results. Furthermore, this research defines the effectiveness of thermal conductivity prediction models using experimental heat transfer results and the Zehner-Schlunder model. The newly defined effective thermal conductivity prediction model has been verified to better predict performance than other models. Finally, this research performs a transient heat transfer analysis of a thermal protection system with a porous insulation in a high speed vehicle using the finite element method and confirms the validity of the effective thermal conductivity prediction model.