• Environmental and Resource Economics Review
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• v.24 no.1
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• pp.109-139
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• 2015

Referring to many previous research on the statistical differences in the figures of energy balance table between that of KEEI and IEA, a study is conducted to provide with a framework for proper comparison, followed by the actual calculation of the differences. Major differences are found for energy oil with its size of over 32% differences in primary energy supply and in energy transformation sectors. In final energy consumption sector, naptha consumption for petro-chemical industry shows 14.58% differences. Overall final energy consumption figure of KEEI after its adjustment to net calorific value as is the case of that of IEA is 3.58% larger than that of IEA. Considering the fact that energy balance table provides the basic information for the understanding of energy sector, further studies seem to be necessary for proper adjustment of current status.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.390-393
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• 1991

This paper describes nonlinear 4th order models for a natural circulation drum-boiler. The models lire derived from energy balance and mass balance principles. They can be characterized by a few physical parameters that are easily obtained from construction data. The models also require steam tables for a limited operating range, which can be approximated by polynomials. The models have been validated against real plant operating data.

• Journal of the Korea Institute of Building Construction
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• v.11 no.3
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• pp.247-255
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• 2011

Currently, there is database for per unit requirements of major construction materials in terms of energy consumption and $CO_2$ emission based on the input-output table published by the Bank of Korea in 2000, but no database for per unit requirements based on input-output tables was published in 2005 and 2007. The purpose of this study was to calculate the unit requirement values of major construction materials in terms of energy consumption and $CO_2$ emission generated by using the input-output tables published in 2005 and 2007. To estimate the unit requirement values, a database building method with the input-output tables was adopted by selecting 16 types of construction materials in wide use on construction sites. When the study results were compared with existing unit requirement values based on the input-output table of 2000, there were small discrepancies, from which it can be interpreted that the method used in the study is reasonable. Unit requirement values estimated based on input-output tables of 2005 and 2007 tended to decrease, and the highest value of energy consumption and $CO_2$ emission were found in the materials using cement and rebar.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.10
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• pp.1474-1483
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• 2013

The objective was to evaluate the use of prediction equations based on the chemical composition of feedstuffs to estimate the values of apparent metabolisable energy corrected for nitrogen balance (AMEn) of corn and soybean meal for broilers. For performance and carcass characteristics, 1,200 one-d-old birds (male and female) were allotted to a completely randomised factorial $2{\times}8$ (two genders and eight experimental diets) with three replicates of each sex with 25 birds. In the metabolism trial, 240 eight-d-old birds were distributed in the same design, but with a split plot in time (age of evaluation) with five, four and three birds per plot, respectively, in stages 8 to 21, 22 to 35, and 36 to 42 d of age. The treatments consisted of the use of six equations systems to predict the AMEn content of feedstuffs, tables of food composition and AMEn values obtained by in vivo assay, totalling eight treatments. Means were compared by Scott-Knott test at 5% probability and a confidence interval of 95% was used to check the fit of the energy values of the diets to the requirements of the birds. As a result of this study, the use of prediction equations resulted in better adjustment to the broiler requirements, resulting in better performance and carcass characteristics compared to the use of tables, however, the use of energy values of feedstuffs obtained by in vivo assay is still the most effective. The best equations were: AMEn = 4,021.8-227.55 Ash (for corn) combined with AMEn = -822.33+69.54 CP-45.26 ADF+90.81 EE (for soybean meal); AMEn = 36.21 CP+85.44 EE+37.26 NFE (nitrogen-free extract) (for corn) combined with AMEn = 37.5 CP+46.39 EE+14.9 NFE (for soybean); and AMEn = 4,164.187+51.006 EE-197.663 Ash-35.689 CF-20.593 NDF (for corn and soybean meal).