• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.30 no.6
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• pp.393-400
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• 2017

For comparison to the Li-ion battery, evaluating a thermal battery must consider additional variables. The first one is the temperature difference between the battery and its unit cell. Thermal batteries and their unit cells have a temperature difference that is caused by the thermal battery activation mechanism and its shape. The second variable is the electrochemical reaction steps. Most Li-ion batteries have a constant electrochemical reaction at the electrode, and battery voltage is affected when the concentration of Li ions is changed. However, a thermal battery has several steps in its electrochemical reaction, and each step has a different potential. In this study, we used unit cell discharge tests based on interpolating a 4D lookup table to estimate the performance of a thermal battery. From the test results, we derived an estimation algorithm by interpolating the table, which is queried from specified profile groups. As a result, we found less than a 5 percent difference between estimation and experiment at the 1.3 V cut-off time.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.8
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• pp.695-703
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• 2005

The objective of this study is to determine the effective thermal conductivity and thermal resistance values in test boreholes with three different fill materials. To evaluate these heat transfer properties, in-situ tests on four vertical boreholes were conducted by adding a monitored amount of heat to water over various test lengths. Two parameter estimation models, line-source and numerical one-dimensional models, for evaluation of thermal response test data were compared when applied on the same four data sets. Results show that the average thermal conductivity deviation between measured data and these two models is in the range of $3.03\%$ to $4.45\%$. The effect of increasing grout thermal conductivity from 1.34 to 1.82 $W/m^{\circ}C$ resulted in overall increases in effective formation thermal conductivity by $11.1\%$ to $51.9\%$ and reductions in borehole thermal resistance by $11.6\%$ to $26.1\%$.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.314-321
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• 2022

Depth information used in SLAM and visual odometry is essential in robotics. Depth information often obtained from sensors or learned by networks. While learning-based methods have gained popularity, they are mostly limited to RGB images. However, the limitation of RGB images occurs in visually derailed environments. Thermal cameras are in the spotlight as a way to solve these problems. Unlike RGB images, thermal images reliably perceive the environment regardless of the illumination variance but show lacking contrast and texture. This low contrast in the thermal image prohibits an algorithm from effectively learning the underlying scene details. To tackle these challenges, we propose multi-channel remapping for contrast. Our method allows a learning-based depth prediction model to have an accurate depth prediction even in low light conditions. We validate the feasibility and show that our multi-channel remapping method outperforms the existing methods both visually and quantitatively over our dataset.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.6
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• pp.669-676
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• 2014

A three-way catalyst substrate for domestic passenger car satisfies the design criteria for exhaust gas exchange and pressure drop but does not have satisfactory thermal fatigue performance. Prefracture faults in this three-way catalyst substrate has often been discovered in vehicle repair or vehicle inspection facilities. This paper presents a thermal fatigue performance estimation method for a three-way catalyst substrate using a probabilistic strength reduction factor model. This method is superior to the thermal fatigue performance estimation method for a three-way catalyst substrate that uses a deterministic strength model.

• 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 $5\%$.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.10
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• pp.1065-1073
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• 2009

In this paper, the estimation method of C(t)-integral for combined mechanical and thermal loads is proposed for elastic-plastic-creep material via 3-dimensional FE analyses. Plasticity induced by initial loading makes relaxation rate different from those produced elastically. Moreover, the interactions between mechanical and thermal loads make the relaxation rate different from those produced under mechanical load alone. To quantify C(t)-integral for combined mechanical and thermal loads, the simplified formula are developed by modifying redistribution time in existing work done by Ainsworth et al..

• Proceedings of the Korea Concrete Institute Conference
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• 2000.04a
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• pp.497-500
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• 2000

This paper describes the procedures to estimate for the design thermal loads on prestressed concrete box girder bridges on th basis of the extreme analysis of the temperature data obtained from long-term thermal analyses. Long-term thermal analyses using the environmental data for three years were conducted, and the extreme distributions of th thermal loads are then determined by the tail-equivalence method, and the thermal loads corresponding to selected return period are calculated. Finally, the results are compared to the specifications suggested in a current design code for thermal loads.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.10
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• pp.1155-1162
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• 2004

This paper is the forth paper of several companion papers which compare the method of Air-Fuel ratio determination. In the previous work, various AFR calculations were performed for various fuels and the results were compared with each other. The comparison, however, were limited to numerical value and estimation of each equation or method was insufficient. In this paper, the overall estimation of the methods was attempted. Also, the method of trouble shooting of instrumentation was presented. Through the estimation of methods, it is concluded that the Eltinge method contains inherently the most perfect thermal dissociation model as far as the exhaust composition is concerned; therefore, this might be regarded as the most general equation of AFR determination among the existing ones. The others might be considered as approximate form. In addition, the mal-distribution factor in Eltinge method is qualitatively equivalent to thermal dissociation chemical equilibrium constant K. Lastly, it is illustrated that all instrumentation error, including the sampling line leakage, can be easily detected through the analyzing the exhaust component on the Eltinge chart.

• Nuclear Engineering and Technology
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• v.31 no.2
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• pp.192-201
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• 1999

This paper proposes an improved signal processing strategy for accurate feedwater flowrate estimation in nuclear power plants. It is generally known that ∼2% thermal power errors occur due to fouling Phenomena in feedwater flowmeters. In the strategy Proposed, the noises included in feedwater flowrate signal are classified into rapidly varying noises and gradually varying noises according to the characteristics in a frequency domain. The estimation precision is enhanced by introducing a low pass filter with the wavelet analysis against rapidly varying noises, and an autoassociative neural network which takes charge of the correction of only gradually varying noises. The modified multivariate stratification sampling using the concept of time stratification and MAXIMIN criteria is developed to overcome the shortcoming of a general random sampling. In addition the multi-stage robust training method is developed to increase the quality and reliability of training signals. Some validations using the simulated data from a micro-simulator were carried out. In the validation tests, the proposed methodology removed both rapidly varying noises and gradually varying noises respectively in each de-noising step, and 5.54% root mean square errors of initial noisy signals were decreased to 0.674% after de-noising. These results indicate that it is possible to estimate the reactor thermal power more elaborately by adopting this strategy.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.9
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• pp.1499-1507
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• 2003

Physical importance of cutting temperatures has long been recognized. Cutting temperatures have strongly influenced both the tool life and the metallurgical state of machined surfaces. Temperatures in drilling processes are particularly important, because chips remain in contact with the tool for a relatively long time in a hole. Tool temperatures tend to be higher in drilling processes than in other in machining processes. This paper concerns with modeling of thermal behaviors in drilling processes as well as estimation of the cutting temperature distribution based on remote temperature measurements. One- and two-dimensional estimation problems are proposed to analyze drilling temperatures. The proposed thermal models are compared with solutions of finite element methods. Observer algorithms are developed to solve inverse heat conduction problems. In order to apply the estimation of cutting temperatures, approximation methods are proposed by using the solution of the finite element method. In two-dimensional analysis, a moving heat source according to feedrate of the drilling process is regarded as a fixed heat source with respect to the drilling location. Simulation results confirm the application of the proposed methods.