• Title/Summary/Keyword: Mean energy

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A Study on Energy Expenditure in Korean Adolescent Women (한국 청소년 여성의 에너지 소비량에 관한 연구)

  • 김유섭;오승호
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.22 no.4
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    • pp.367-373
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    • 1993
  • A 4-week energy balance study was conducted to estimate the energy expenditure (EE) of 7 high school age girl, 15 to 16 year age, by measurement of energy intakes and changes in body energy (BE) content (intake/balance technique), keeping their normal living pattern and eating behavior. Gross energy intake (GE) and fecal energy (FE) loss was measured by bomb calorimetry. Urinary energy (UE) loss was calculated from nitrogen excreted. Fat mass (FM) was determined from body density estimated from skinfold thickness. Mean constitutional ratio of carbohydrate, protein and fat for the total energy intake was 70.1$\pm$1.8%, 12.2$\pm$0.7% and 17.7$\pm$2.0%, respectively, Fecal energy loss was 2.8% proportion of the gross energy intake. Mean daily metabolizable energy estimated by subtract fecal and urinary energy loss was 2022 $\pm$ 50㎉. Total body energy change estimated from body composition change over 28days was increased 2400 $\pm$ 950㎉ . Mean daily energy expenditure was 1958$\pm$87㎉ (39$\pm$2㎉ /kg of body weight).

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Intermittent Heating and Cooling Load Calculation Method -Comparing with ISO 13790

  • Lee, Sang-Hoon
    • Architectural research
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    • v.14 no.1
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    • pp.11-18
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    • 2012
  • College of Architecture, Georgia Institute of Technology, Atlanta, GA, US Abstract The intermittent heating and cooling energy need calculation of the ISO 13790 monthly method was examined. The current ISO 13790 method applies a reduction factor to the continuous heating and cooling need calculation result to derive the intermittent heating and cooling for each month. This paper proposes a method for the intermittent energy need calculation based on the internal mean temperature calculation. The internal temperature calculation procedure was introduced considering the heat-balance taking into account of heat gain, heat loss, and thermal inertia for reduced heating and cooling period. Then, the calculated internal mean temperature was used for the intermittent heating and cooling energy need calculation. The calculation results from the proposed method were compared to the current ISO 13790 method and validated with a dynamic simulation using EnergyPlus. The study indicates that the intermittent heating and cooling energy need calculation method using the proposed model improves transparency of the current ISO 13790 method and draws more rational outcomes in the monthly heating and cooling energy need calculation.

Analysis of Energy Performance and PMV Improvement by Application of Passive Factor for Office Building Renewal (오피스건물 리뉴얼시 패시브 요소적용에 따른 에너지성능 및 PMV 개선에 관한 연구)

  • Hong, Won-Pyo
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.28 no.12
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    • pp.55-64
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    • 2014
  • This paper presents a case study to investigate the monthly calculation method of ISO 13790 applied for a office building. The energy performance analysis according to improvement of insulation and air permeability of windows in K office buildings is investigated by means of building energy efficiency rating tool ($ECO_2-OD$). The K building energy system is tested experimently by the measurement of PMV(predicted mean vote) for the control of indoor thermal environment and heat transmission coefficient of windows and interior walls respectively, before and after the example K office building is remodeled passively. Therefore, Internet based energy assessment program of energy efficiency rating of office building can be applied as a program for the annual energy requirement and for evaluation of energy savings from the experimental and simulation results.

Solar Energy Prediction Based on Artificial neural network Using Weather Data (태양광 에너지 예측을 위한 기상 데이터 기반의 인공 신경망 모델 구현)

  • Jung, Wonseok;Jeong, Young-Hwa;Park, Moon-Ghu;Seo, Jeongwook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.457-459
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    • 2018
  • Solar power generation system is a energy generation technology that produces electricity from solar power, and it is growing fastest among renewable energy technologies. It is of utmost importance that the solar power system supply energy to the load stably. However, due to unstable energy production due to weather and weather conditions, accurate prediction of energy production is needed. In this paper, an Artificial Neural Network(ANN) that predicts solar energy using 15 kinds of meteorological data such as precipitation, long and short wave radiation averages and temperature is implemented and its performance is evaluated. The ANN is constructed by adjusting hidden parameters and parameters such as penalty for preventing overfitting. In order to verify the accuracy and validity of the prediction model, we use Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE) as performance indices. The experimental results show that MAPE = 19.54 and MAE = 2155345.10776 when Hidden Layer $Sizes=^{\prime}16{\times}10^{\prime}$.

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Decomposition of Energy - Induced CO2 Emissions in Korea Using Log Mean Divisia Index Approach (로그 평균 디비지아 지수 기법을 이용한 이산화탄소 배출량 변화의 요인분해)

  • Chung, Hae-Shik;Lee, Kihoon
    • Environmental and Resource Economics Review
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    • v.10 no.4
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    • pp.569-589
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    • 2001
  • We examine historical contributions of inter fuel substitution, changes in carbon efficiency and energy intensity, growth of economy and population to Korea's $CO_2$ emissions from 1970 to 1998 using the log mean weight Divisia index method. The study reveals that economic growth is the most significant factor to $CO_2$ emissions growth among the five factors. Changes in the fuel substitution and carbon coefficient are found negative contributors to $CO_2$ emissions growth. Energy intensity, which played dominant role in halting $CO_2$ emissions growth in the 1980s, began to play reversed role in the 1990s. When evaluated with the log mean Divisia index technique, deterioration of energy intensity in the 1990s is found worse and expected to contribute $CO_2$ emissions growth further.

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A STUDY ON THE ENGINE PERFORMANCE OF A SPARK IGNITION ENGINE ACCORDING TO THE IGNITION ENERGY

  • Han, Sung Bin
    • Journal of Energy Engineering
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    • v.23 no.3
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    • pp.1-6
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    • 2014
  • The more or less homogeneous fuel-air mixture that exists at the end of the compression process is ignited by an electric ignition spark from a spark plug shortly before top dead center. The actual moment of ignition is an optimization parameter; it is adapted to the engine operation so that an optimum combustion process is obtained. Brake mean effective pressure (BMEP) of the spark ignition energy control device (IECD) than conventional spark system at the stoichiometric mixture is increased about 9%. For lean burn engine, the lean limit is extended about 25% by using the IECD. It was considered the stability of combustion by the increase of flame kernel according to the high ignition energy supplies in initial period and discharge energy period lengthen by using the IECD.

A Study on Energy expenditure in Korean Adult (한국인의 에너지 소비량에 관한 연구)

  • 오승호
    • Journal of Nutrition and Health
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    • v.22 no.6
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    • pp.423-437
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    • 1989
  • A 4-week energy balance study was conducted to estimate the energy expenditure (EE) of 16 college age men and women, 20 to 26 year of age, by measurement of energy intakes and changes in body energy(BE) content(intake/balance technique), keeping their normal living pattern and maintenance body weight. Energy intake was measured by bomb calorimetry and estimated by food table. Fecal energy loss was calculated from nitrogen excreted. Fat mass was determined from body density estimated from skinfold tickness. 1) Gross energy (GE) intakes calculated from food table was not only 13.4% lower than those of bomb calorimetry but also lower 4 and 5% than metabolizable energy(ME) intakes for the male and female subjects, respectively. 2) Fecal energy loss was 7.2% and 6.9% proportion of the gross energy intake for the male and female subjects, respectively. 3) Mean daily metabolizable energy intakes estimated by subtract fecal and urinary energy loss was 2467kcal for the male subjects and 1897kcal for the female subjects. 4) Total body energy change estimated from body composition change over 31 days was decreased 7672kcal for the male subjects and 2689kcal for the female subjects. 5) Mean daily energy expenditure was 2714kcal (45kcal/kg of body weight) for the male subjects and 1984kcal(40kcal/kg of body weight) for the female subjects. 6) The estimated energy expenditure of college-age subjects in this study provide evidence to support the Recommended Dietary Allowances for energy of Korean normal adult.

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The Meteorological Themes Selection for the Site Selection of Protected Horticulture Complex in Saemanguem (새만금 시설원예단지 적지선정을 위한 기상환경 주제선정)

  • Kang, Dong Hyeon;Lee, Si Young;Kim, Jong Koo;Choi, Hong Ki;Park, Min Jung;Yeon, Je Sung;Son, Jin Kwan
    • Journal of Bio-Environment Control
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    • v.24 no.4
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    • pp.287-295
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    • 2015
  • This study was conducted to find the suitability site selection for the construction of Saemangeum horticulture complex taking into account cost-effective environmental management by analyzing and comparing meteorological conditions. The study sites were regions around the Saemangeum area in which the development of an industrial complex extending 28,300 ha is planned. We collected meteorological data in 12 candidate sites and established a rating scheme and thematic maps. We selected ten themes by consulting experts using a questionnaire. Selected ten themes is Summer, 20 days max. temp. mean, Winter, 20 days min. temp. mean, Summer, 90 days temp. mean, Winter, 90 days temp. mean, Year-round, max. wind velocity, Year-round, wind velocity mean, Winter, 90 days solar radiation mean, Year-round, number of foggy days, Year-round, 1 day max. rainfall and Spring. 90 days humidity mean. And we set ratio-based weights for the evaluation parameters.

Hourly Steel Industry Energy Consumption Prediction Using Machine Learning Algorithms

  • Sathishkumar, VE;Lee, Myeong-Bae;Lim, Jong-Hyun;Shin, Chang-Sun;Park, Chang-Woo;Cho, Yong Yun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.10a
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    • pp.585-588
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    • 2019
  • Predictions of Energy Consumption for Industries gain an important place in energy management and control system, as there are dynamic and seasonal changes in the demand and supply of energy. This paper presents and discusses the predictive models for energy consumption of the steel industry. Data used includes lagging and leading current reactive power, lagging and leading current power factor, carbon dioxide (tCO2) emission and load type. In the test set, four statistical models are trained and evaluated: (a) Linear regression (LR), (b) Support Vector Machine with radial kernel (SVM RBF), (c) Gradient Boosting Machine (GBM), (d) random forest (RF). Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used to measure the prediction efficiency of regression designs. When using all the predictors, the best model RF can provide RMSE value 7.33 in the test set.

Using physical activity levels to estimate energy requirements of female athletes

  • Park, Jonghoon
    • Korean Journal of Exercise Nutrition
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    • v.23 no.4
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    • pp.1-5
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    • 2019
  • [Purpose] The goal of this study was to review data on physical activity level (PAL), a crucial index for determining estimated energy requirement (EER), calculated as total energy expenditure (TEE, assessed with doubly labeled water [DLW]) divided by resting metabolic rate (RMR, PAL = TEE/RMR) in female athletes and to understand the methods of assessing athletes' EERs in the field. [Methods] For the PAL data review among female athletes, we conducted a PubMed search of the available literature related to the DLW method. DLW studies measuring TEE and RMR were included for the present review. [Results] Briefly, the mean PAL was 1.71 for collegiate swimmers with moderate training, which was relatively low, but the mean PAL was 3.0 for elite swimmers during summer training camp. This shows that PAL can largely vary even within the same sport depending on the amount of training, and the differences in PAL were remarkable depending on the sport. Aside from the DLW method, there is currently no research tool related to athletes' EERs that can be used in the field. [Conclusion] Briefly, the mean PAL was 1.71 for collegiate swimmers with moderate training, which was relatively low, but the mean PAL was 3.0 for elite swimmers during summer training camp. This shows that PAL can largely vary even within the same sport depending on the amount of training, and the differences in PAL were remarkable depending on the sport. Aside from the DLW method, there is currently no research tool related to athletes' EERs that can be used in the field.