• KIEAE Journal
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• v.14 no.1
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• pp.75-81
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• 2014

This study aims at investigating the benefit of actively controlling humidity to improve thermal comfort and energy efficiency in climate zones other than hot-dry. For this research purpose, three thermal control strategies, which adopted different initiative degrees in humidity control, were developed - i) temperature controls, ii) temperature and humidity controls, and iii) thermal sensation controls. Performance of the developed strategies were experimentally tested in a full scale mock up of an office environment. The study revealed that air temperature was better controlled in the occupied zone under the first two strategies than the thermal sensation based strategy. On the other hand, the thermal sensation-based strategy maintained thermal sensation levels more comfortably. In addition, energy consumption was significantly reduced when humidity was actively controlled for thermal comfort. The thermal sensation-based control strategy consumed significantly less electricity than the first two strategies. From these findings, this study indicated that adoption of an active humidity control system based on thermal sensation can provide increased thermal comfort as well as energy savings for summer seasons in climatic zones other than hot-dry.

• Journal of Mechanical Science and Technology
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• v.15 no.11
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• pp.1482-1489
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• 2001

Thermally-induced errors originating from machine tool errors have received significant attention recently because high speed and precise machining is now the principal trend in manufacturing proce sses using CNC machine tools. Since the thermal error model is generally a function of temperature, the thermal error compensation system contains temperature sensors with the same number of temperature variables. The minimization of the number of variables in the thermal error model can affect the economical efficiency and the possibility of unexpected sensor fault in a error compensation system. This paper presents a thermal error model with minimum number of variables using a fuzzy logic strategy. The proposed method using a fuzzy logic strategy does not require any information about the characteristics of the plant contrary to numerical analysis techniques, but the developed thermal error model guarantees good prediction performance. The proposed modeling method can also be applied to any type of CNC machine tool if a combination of the possible input variables is determined because the error model parameters are only calculated mathematically-based on the number of temperature variables.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2589-2596
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• 2000

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model, etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcomes limitation of accuracy in the linear regression model or the engineering judgment model. It shows that the fuzzy model has more better performance than linear regression model, though it has less number of thermal variables than the other. The fuzzy model does not need to have complex procedure such like multi-regression and to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Also, the fuzzy model can be applied to any machine, but it delivers greater accuracy and robustness.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.75-80
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• 1999

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcome limitation of accuracy in the linear regression model or the engineering judgment model. And this model is compared with the engineering judgment model. It is not necessary complex process such like multi-regression analysis of the engineering judgment model. A fuzzy model does not need to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Like a regression model, this model can be applied to any machine, but it delivers greater accuracy and robustness.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.4
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• pp.526-534
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• 2016

A MEMS solid propellant thruster array shall be operated within an allowable range of operating temperatures to avoid ignition failure by incomplete combustion due to a time delay in ignition. The structural safety of the MEMS thruster array under severe on-orbit thermal conditions can also be guaranteed by a suitable thermal control. In this study, we propose a thermal control strategy to perform on-orbit verification of a MEMS thruster module, which is expected to be the primary payload of the STEP Cube Lab mission. The strategy involves, the use of micro-igniters as heaters and temperature sensors for active thermal control because an additional heater cannot be implemented in the current design. In addition, we made efforts to reduce the launch loads transmitted to the MEMS thruster module at the system level structural design. The effectiveness of the proposed thermo-mechanical design strategy has been demonstrated by numerical analysis.

• Journal of the Korean Physical Society
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• v.73 no.11
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• pp.1644-1649
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• 2018

Aiming at infrared thermal images with different buried depth defects, we study a variety of image segmentation algorithms based on the threshold to develop global search ability and the ability to find the defect area accurately. Firstly, the iterative thresholding method, the maximum entropy method, the minimum error method, the Ostu method and the minimum skewness method are applied to image segmentation of the same infrared thermal image. The study shows that the maximum entropy method and the minimum error method have strong global search capability and can simultaneously extract defects at different depths. However none of these five methods can accurately calculate the defect area at different depths. In order to solve this problem, we put forward a strategy of "divide and conquer". The infrared thermal image is divided into several local thermal maps, with each map containing only one defect, and the defect area is calculated after local image processing of the different buried defects one by one. The results show that, under the "divide and conquer" strategy, the iterative threshold method and the Ostu method have the advantage of high precision and can accurately extract the area of different defects at different depths, with an error of less than 5%.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.354-356
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• 2000

This paper describes the strategy of a daily optimal operational scheduling on cogeneration systems with each other generation mode. The cogeneration systems consists of three generators. auxiiiary devices which are three auxiliary boilers, two waste boilers and three sludge incinerators. One unit that using the back pressure turbin generates the electrical and the thermal energy. The other two units that using the extraction condensing turbine generate the energy. Auxiliary devices operate to supplement the thermal energy to the thermal load with three units. The cogeneration system has a large capacity which is able to supply enough the thermal energy to the thermal load, however the electric power generated is insufficient to satisfy the electrical load. Therefore the insufficient electric energy is supplemented by buying electrical energy from the utility. Simulation was carried out using optimization toolbox. The result reveals that the proposed modeling and strategy can be effectively applied to cogeneration systems with each other generation mode.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.1
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• pp.88-93
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• 2005

In this study, the operational characteristics on heating performance and energy consumption for intermittent hot water heating system in apartment buildings were research by simulation. The effects of apartment inlet hot water temperature and operation time per day on energy consumption and indoor thermal environment are investigated. The strategy of energy saving and thermal environment improvement is suggested in comparison with the existing ones.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.721-729
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• 1994

In this paper an optimization of the industrial congeneration system which have a thermal storage tank is proposed for the short-term operation strategy. Short-term operation costs of topping cycle and bottoming cycle are calculated by using the proosed model of a thermal storage tank. Simulation result of four cases are compared and analyzed each other.By these simulations which are similar to real operation circumstances. the validity of the proposed model is verified.

• Korean Journal of Computational Design and Engineering
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• v.4 no.4
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• pp.318-326
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• 1999

Recently, electronic systems including computers have been rapidly shrinking in size while at the same time the complexity and the capability of these systems continue to grow/sup [1]/. Thus, system volumes have decreased as system power has increased, resulting in dramatic increases in system heat density. The high temperature of the computer system is considered as the major reason for low performance and shortening life of the product. It is necessary to solve this problem due to the heat density increased and to develop the design skill of the computer cabinet according to miniaturization. M4500 desk-top computer was selected for analyzing the thermal management inside cabinet. The cabinet volume, the configuration of the heating devices, the size and location of air ventilation, and the fan selection have been investigated as the important parameters to find out an optimal cabinet design. The objectives of this project were to analyze which design parameters would affect cooling performance by thermal strategy, to design an optimal model, and to measure the temperatures of the main parts to confirm the effect of the thermal design. The temperatures of each part of the optimal model were compared with those of the existing model. As a result. the volume of this miniaturized model was about 16% smaller than that of M4500 without any change in operating performance.