• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.419-428
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• 2021

In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.731-741
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• 2008

Previous studies on the numerical simulation at the tidal reach of Han River tend to restrict downstream boundary as Jeon-ryu station due to difficulties in gaining cross section data and tidal elevation values at Yu-do. But, in this study, geometries beyond the confluence of Gok-reung stream and Im-jin River are constructed based on the numerical sea map; tidal elevation at the downstream boundary, Yu-do is estimated by harmonic analysis of In-cheon tide gage station so that hydrodynamic and diffusion behavior have been analyzed. The domain ranging from Shin-gok submerged weir to Yu-do is selected (which is 36.8 km in length). RMA-2 and RAM4 developed by Il Won Seo (2008) are applied to simulate flow and diffusion behavior, respectively. Numerical results of flow characteristic are compared with the measured data at Jeon-ryu station. Simulation is carried out from June 23 to 25 in 2006 on the ground that hydrologic data is satisfactory and tidal difference is huge during that period. The result shows that reverse flow occurs 5 times according to the tidal elevation at Yu-do and the maximum reverse flow is observed up to Jang-hang IC, which is 32.9 km in length. Also analysis is focused on the process of generation and disappearance of reverse flow, the distribution of water surface elevation and velocity along the maximum velocity line, and the transport of nonconservative pollutant. Pollutant injected from Gul-po stream spreads widely across the river; however, the size of BOD cloud entering from Gok-reung stream is relatively small because water depth at the mid and left side becomes deeper and maximum velocity occurs along the right bank so that transverse mixing is completed quickly. Finally, mixing characteristic of horizontal salinity distribution is obtained by estimating the salinity input with analytical solution of 1D advection-dispersion equation.

• Journal of Korean Society of Forest Science
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• v.75 no.1
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• pp.1-18
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• 1986

This study was initiated to estimate productivity of Quercus variabilis stand. However the practical objective of this study was to provide some information to establish the basis of selecting the suitable site for Quercus variabilis. The productivity measured in terms of DBH, height, basal area and stem volume was hypothesized, respectively, to be a function of a group of factors. This study considered 32 factors, 20 of which were related to the forest environmental factors such as tree age, latitude, percent slope, etc. and the rest of which were related to soil factors such as soil moisture, total nitrogen, available $P_2O_5$, etc. The data on 4 productivity measurements of Quercus variabilis growth and related factors cited were collected from 99 sample plots in Kyeongbook and chungbook provinces. Some factors considered were, in nature, discrete variables and the others continuous variables. Each kind of factor was classified into 3 or 4 categories and total numbers of such categories were eventually amounted to 110. Then each category was treated as an independent variable. This is amounted to saying that individual variable was treated a dummy variable and assigned a value 1 or 0. However the first category of each factor was deleted from the normal equation for statistical consideration. First of all, each of 4 productivity measurements of Quercus variabilis growth was regressed and, at the same time, those 110 categories. Secondly, the partial correlation coefficients were measured between each pair of 4 productivity measurements and 32 individual foctors. Finally, the relative scores were estimated in order to derive the category ranges. The result of these statistical analyses could be summarized as follows: 1) Growth measurement in terms of height seems to be a more significant criterion for estimation of productivity of Quercus variabilis. 2) Productivity of forest on stocked land may better be estimated in terms of forest environmental factors, on the other hand, that of unstocked land may be estimated in terms of physio-chemical factors of soil. 3) The factors that a strongly positive relation to all growth factors of tree are age group, effective soil, soil moisture, etc. This implies that these factors might effectively be used for criteria for selecting the suitable site for Quercus variabilis. 4) Parent rock, latitude, total nitrogen, age group, effective soil depth, soil moisture, organic matter, etc., had more significant category range for tree growth. Therefore, the suitable site for Quercus variabilis may be selected, based on this information. In conclusion, the above results obtained by the multivariable analysis can be not only the important criteria for estimating the growth of Quercus variabilis but also the useful guidance for selecting the suitable sites and performing the rational of Quercus variabilis forest.