• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.7
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• pp.299-304
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• 2016

In recent years, heat source systems which have a principal effect on the performance of buildings are difficult to design optimally as a great number of design factors and constraints in large and complicated buildings need to be considered. On the other hand, it is necessary to design an optimum system combination and operation planning for energy efficiency considering Life Cycle Cost (LCC). This study suggests a multi-level and multi-objective optimization method to minimize both LCC and investment cost using a genetic algorithm targeting an office building which requires a large cooling load. The optimum method uses a two stage process to derive the system combination and the operation schedule by utilizing the input data of cooling and heating load profile and system performance characteristics calculated by dynamic energy simulation. The results were assessed by Pareto analysis and a number of Pareto optimal solutions were determined. Moreover, it was confirmed that the derived operation schedule was useful for operating the heat source systems efficiently against the building energy requirements. Consequently, the proposed optimization method is determined by a valid way if the design process is difficult to optimize.

• Proceedings of the KSME Conference
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• 2001.06d
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• pp.260-265
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• 2001

This paper describes total flow control of an ice slurry system for pump energy saving. Similar turbo machinery has a characteristic that input power ratio is proportional to the three time of revolution speed ratio. To reduce the energy cost of brine pump in ice slurry storage systems, inverter is adapted instead of 3-way valve to control the speed of brine pump motor. One type of cooling load profile was used as driving load of the system, generated by a boiler and warm water storage tank. As results of the laboratory test, energy consumption and cost of the pump were reduced by 11.4%.

• Tribology and Lubricants
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• v.23 no.3
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• pp.109-116
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• 2007

A scroll compressor is on the increase in the use for the cooling and ambition machinery because of the advantages about high efficiency, low vibration and low noise. The design of thrust bearing for scroll compressor has depended on the experience. The lubrication considering the squeeze flow was applied for high side shell and low side shell of scroll thrust bearing. This work was based on governing fluid lubrication equation at the general coordinate. It shows the behavior for an orbiting scroll with direct numerical analysis using FDM. This study obtained the theoretical design value by finding load capacity and tilting angle of an orbiting scroll for thrust bearing in a scroll compressor. Especially this work performed the analysis about the design parameter. The program was written using Visual C++ to enhance user to change the design parameter easily. In particular the result value and the pressure profile were displayed as windows in every step for user to understand without difficulty.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.11
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• pp.1649-1657
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• 2010

We have investigated the unexpected phenomena on the surface of molded GFRP composites. The major cause of the unevenness, as a result of which the surface becomes rough, is a shrinking of the matrix in the process of holding pressure and cooling temperature. The higher holding pressure load in a molding process and the lower demolding temperature in an annealing experiment, the better GFRP composites moldings improved its appearance. In addition, by taking the holding pressure and demolding temperature into consideration, we evaluate the process that causes the surface unevenness and the variation in the fiber projection height.

• 한국태양에너지학회:학술대회논문집
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• 2009.04a
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• pp.184-189
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• 2009

In order to improve the operation of energy systems, it is necessary for the urban communities to have reliable optimization routines, both computerized and manual, implemented in their organizations. However, before a production plan for the energy system units can be constructed, a prediction of the energy systems first needs to be determined. So, several methodologies have been proposed for energy demand prediction, but due to uncertainties in urban community, many of them will fail in practice. The main topic of this paper has been the development of a method for energy demand prediction at urban community. Energy demand prediction is important input parameters to plan for the energy planing. This paper presents a energy demand prediction method which estimates heat and electricity for various building categories. The method has been based on artificial neural networks(ANN). The advantage of ANN with respect to the other method is their ability of modeling a multivariable problem given by the complex relationships between the variables. Also, the ANN can extract the relationships among these variables by means of learning with training data. In this paper, the ANN have been applied in oder to correlate weather conditions, calendar data, schedules, etc. Space heating, cooling, hot water and HVAC electricity can be predicted using this method. This method can produce 10% of errors hourly load profile from individual building to urban community.