• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.1
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• pp.26-32
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• 2000

Design load calculations which depend on the thermal characteristics of the building structure such as the wall, roof, and fenestration provide the basic data for selecting an HVAC system and its equipment. Most of domestic multi-family houses include a high thermal storage layer like massive concrete structure and a floor heating structure. This study is to compare the results of the design heating load between steady state and unsteady state calculation in order to comprehend the thermal storage effect in multi-family houses. The design heating load under the steady state calculation is estimated from 5.4% to 7.8% larger than that under the unsteady state in the typical floor of a multi-family house model. The design heating load considered the safety factors like a orientation and location factor also is 21.4% to 26.5% larger than that by the unsteady state calculation. So, the safety factors for use of the practicing engineer are analyzed as the main factor of a heating plant oversizing.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.37-42
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• 2015

In order to provide fundamental data for the creation of environmental design criteria for horticultural facilities, we developed a method to easily calculate the seasonal heating load applying heating degree-hour while taking into account heating load reductions due to solar radiation in the daytime, and reviewed through greenhouse heating experiments. Heating experiments and measuring meteorological environments were carried out in three greenhouses located at Buyeo, Cheonan, and Buan, and we derived reduction factors of seasonal heating load according to hours of sunshine. Daily mean hours of sunshine during the experiment period in each of the greenhouse was 4.0 to 8.3 hours, and the reduction factor of seasonal heating load was 0.64 to 0.85, has been shown to decrease linearly with the increase in hours of sunshine. A method to estimate the seasonal heating load for greenhouses was developed using the reduction factor of seasonal heating load derived from the greenhouse heating experiment, including the adjustment factor of seasonal heating load according to hours of sunshine. The developed method was validated through heating experiments in a greenhouse located at Cheonan. Greenhouse seasonal heating loads calculated by the method developed in this study were analyzed to show the estimate error of 1.2 to 5.0%. It showed that the accuracy increased 2.3 times more than when using the heating load reduction factor of 0.75 applied uniformly in previous studies. Thus, the calculation method of seasonal heating load for greenhouses considering hours of sunshine developed in this study could be utilized for energy estimation, management planning, and economic evaluation in greenhouse design.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.4
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• pp.153-153
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• 1985

A method of computer aided design (C.A.D.) is proposed to analize a load circuit of a high frequency induction heating. Various formulas are derived from the properity of the heating load, which is useful for the design of heating materials. A load circuit which is designed by the proposed C.A.D. is realized and tested. The experimental results show in good agreement with the theoritical analysies. Especially the result reveal that the power transfer efficiency increases as the Q and coupling coefficient of the work coil increase.

• The Journal of Sustainable Design and Educational Environment Research
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• v.11 no.2
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• pp.19-27
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• 2012

This study was carried out in order to establish the estimation equation for school power consumption using regression analysis based on collected power consumption for two years of weather data and schools are located in Central Changwon and Masan district in Changwon city. (1) The power consumption estimation equation for Heating and cooling is calculated using power consumption per unit volume, the difference between actual power consumption and results of estimation equations is 4.1%. (2) The power consumption estimation equation for heating load is showed 2.6% difference compared to actual power consumption in Central Changwon and is expressed 2.9% difference compared to that in Masan district. Therefore, the power consumption prediction for each school using the power consumption estimation equation is possible. (3) The power consumption estimation equation for cooling load is showed 8.0% difference compared to actual power consumption in Central Changwon and is expressed 2.9% compared to that in Masan district. As the power consumption estimation equation for cooling load is expressed difference compared to heating load, it needs to investigate influence for cooling load.

• Journal of Bio-Environment Control
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• v.23 no.3
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• pp.192-198
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• 2014

To establish the design criteria for seasonal heating load calculation in greenhouses, standard weather data are required. However, they are being provided only at seven regions in Korea. So, instead of using standard weather data, in order to find the method to build design weather data for seasonal heating load calculation, heating degree-hour and heating degree-day were analyzed and compared by methods of fundamental equation, Mihara's equation and modified Mihara's equation using normal and thirty years from 1981 to 2010 hourly weather data provided by KMA and standard weather data provided by KSES. Average heating degree-hours calculated by fundamental equation using thirty years hourly weather data showed a good agreement with them using standard weather data. The 24 times of heating degree-day showed relatively big differences with heating degree-hour at the low setting temperature. Therefore, the heating degree-hour was considered more appropriate method to estimate the seasonal heating load. And to conclude, in regions which are not available standard weather data, we suggest that design weather data should be analyzed using thirty years hourly weather data. Average of heating degree-hours derived from every year hourly weather data during the whole period can be established as environmental design standards, and also minimum and maximum of them can be used as reference data for energy estimation.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.5 no.4
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• pp.278-284
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• 1993

A simplified TAC method was developed for the selection of design temperature and absolute humidity for peak cooling and heating load calculation with ETD method. And the design data of the 11 major cities in Korea were obtained. Based on the simplified TAC method, the design data for summer and autumn cooling season were selected by the TAC 5.0% of July through August and TAC 5.0% of October, respectively. But the design data for winter heating season were selected by the conventional TAC 2.5% of the full winter season.

• Journal of the Korean Solar Energy Society
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• v.34 no.3
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• pp.89-97
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• 2014

Recently design standard for energy-saving in apartment buildings has been consolidated gradually on the basis of evaluation and certification standards of energy efficiency of buildings, the energy-saving policy of building at home and abroad. Performance criteria for thennal insulation as well as fenestration has been progressively enhanced, and performance criteria for ventilation and airtightness of the building have also been re-developed. Therefore, heating and cooling load characteristics of the apartment building can be changed. For the design of the upcoming heating and cooling equipment in apartment buildings, it is necessary to evaluate the heating and cooling load characteristics according to the design strategies for energy saving in apartment buildings. As a result, in this study, it is intended to use as a resource for analyzing the impact that the adoption of energy-saving design variables for each of the apartment buildings, to predict the heating and cooling load characteristics in the apartment building.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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• pp.1-8
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• 2017

The purpose of this study was to provide basic data for development of environmental design technology for greenhouses constructed in reclaimed lands. We analyzed the climatic conditions around seven major reclaimed land areas in Korea, which have a plan to install advanced horticultural complexes. The characteristics of heating load through the thermal environment measurement of the greenhouse in Saemangeum were analyzed. The part to be applied to the environmental design of the greenhouses in reclaimed lands were reviewed. The overall heat transfer coefficient of the experimental greenhouse with the aluminum screen and multi-layer thermal curtain averaged $3.79W/m^2^{\circ}C$. It represents a 44 % heat savings rate compared with plastic greenhouses with a single covering, which was significantly lower than that of the common greenhouses with 2-layer thermal curtains. This is because the experimental greenhouse was installed on reclaimed land and wind was stronger than the inland area. Among the total heating load, the transmission heat loss accounted for 96.4~99.9 %, and the infiltration loss and the ground heat exchange were low. Therefore, it is necessary to take countermeasures to minimize the transmission heat loss for greenhouses constructed in reclaimed lands. As the reclaimed land is located on the seaside, the wind is stronger than the inland area, and the fog is frequent. Especially, Saemangeum area has 2.6 times stronger wind speed and 3.4 times longer fog duration than the inland area. In designing the heating systems for greenhouses in reclaimed lands, it is considered that the maximum heating load should be calculated by applying the wind coefficient larger than the inland area. It is reasonable to estimate the operation cost of the heating system by applying the adjustment factor 10 % larger than the average in calculating the seasonal heating load.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.6
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• pp.441-446
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• 2000

This paper presents an approach for the prediction of optimal heating load using a diagonal recurrent neural networks(DRNN) and data base system of outdoor temperature. In the DRNN, a dynamic backpropagation(DBP) with delta-bar-delta teaming method is used to train an optimal heating load identifier. And the data base system is utilized for outdoor temperature prediction. Compared to other kinds of methods, the proposed method gives better prediction performance of heating load. Also a hardware for the controller is developed using a microprocessor. The experimental results show that prediction enhancement for heating load can be achieved with the proposed method regardless of the its inherent nonlinearity and large time constant.

• Journal of Biosystems Engineering
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• v.15 no.4
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• pp.346-354
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• 1990

In order to provide basic references for the design of heating on simple silkworm rearing house, the actual change of heating load coefficient by progress of adult silkworm rearing day from the reared in silkworm rearing house, the heating load coefficient by types of silkworm rearing houses and the heating requirement and the maximum heating load by types of silkworm rearing houses were determined. The results obtained from the study were as follows : 1. The average heating load coefficients of NS, OS and CC type simple silkworm rearing houses were $24.1KJ/m^2-hr-^{\circ}C$, $19.8KJ/m^2-hr-^{\circ}C$, and $10.8KJ/m^2-hr-^{\circ}C$, respectively. 2. The change of heating load coefficient by progress of silkworm rearing day after reared into simple silkworm rearing house could be expressed as Fig. 4. 3. Heating degree-hour for adult silkworm rearing in Suweon district was calculated as $951.6^{\circ}C-hr$ for spring season and $610.5^{\circ}C-hr$ for autumn season. 4. Yearly heating requirement of the NS type was estimated twice more than that of the CC type. Thus, some kinds of reinforced thermal adiabatic facilities is desirable for NS type. 5. The time for maximum heating load was turned out at the 4th instar during the spring season and after the mounting during the autumn season. 6. This study was performed in Suweon district. However, the estimated and analyzed data could be adapted to the major silkworm rearing district if their meteorology data were adjusted.