• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.420-428
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• 2019

This study is the heating energy saving test of the high-bed strawberry crown heating system. The system consists of electric hot water boiler, thermal storage tank, circulation pump, crown heating pipe(white low density polyethylene, diameter 16mm) and a temperature control panel. For crown heating, the hot water pipe was installed as close as possible to the crown part after planting the seedlings and the pipe position was fixed with a horticultural fixing pin. In the local heating type, hot water at $20{\sim}23^{\circ}C$ is stored in the themal tank by using an electric hot water boiler, and crown spot is partially heated at the setting temperature of $13{\sim}15^{\circ}C$ by turning on/off the circulation pump using a temperature sensor for controlling the hot water circulation pump which was installed at the very close to crown of strawberry. The treatment of test zone consisted of space heating $4^{\circ}C$ + crown heating(treatment 1), space heating $8^{\circ}C$(control), space heating $6^{\circ}C$ + crown heating(treatment 2). And strawberries were planted in the number of 980 for each treatment. The heating energy consumption was compared between November 8, 2017 and March 30, 2018. Accumulated power consumption is converted to integrated kerosene consumption. The converted kerosene consumption is 1,320L(100%) for space $8^{\circ}C$ heating, 928L(70.3%) for space $4^{\circ}C$ + crown heating, 1,161L($88^{\circ}C$) for space $6^{\circ}C$ + crown heating). It was analyzed that space $4^{\circ}C$ + pipe heating and space $6^{\circ}C$ + crown heating save heating energy of 29.7% and 12% respectively compared to $8^{\circ}C$ space heating(control).

• Journal of Korean Society of Environmental Engineers
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• v.27 no.8
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• pp.870-876
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• 2005

The multiple regression models which have two factors(population and commercial area) have been used to forecast the water demand in the future. But, the coefficient of population had a negative value because proper regional classification wasn't performed, and it is not reasonable because the population must be a positive factor. So, the regional classification was performed by principal component and cluster analysis to solve the problem. 6 regional characters were transformed into 4 principal components, and the areas were divided into two groups according to cluster analysis which had 4 principal components. The new regression models were made by each group, and the problem was solved. And, the future water demands were estimated by three scenarios(Active, moderate, and passive one). The increase of water demand ore $89.034\;m^3/day$ in active plat $49,077\;m^3/day$ in moderate plan, and $19,996\;m^3/day$ in passive plan. The water supply ability as scenarios is enough in water treatment plant, however, 2 reservoirs among 4 reservoirs don't have enough retention time in all scenarios.