• Journal of the Korea Concrete Institute
• /
• v.17 no.4 s.88
• /
• pp.551-558
• /
• 2005

The setting and hardening of concrete is accompanied with nonlinear temperature distribution caused by development of hydration heat of cement. Especially at early ages, this nonlinear distribution has a large influence on the crack evolution. As a result, in order to predict the exact temperature history in concrete structures it is required to examine thermal properties of concrete. In this study, the convection heat transfer coefficient which presents thermal transfer between surface of concrete and air, was experimentally investigated with variables such as velocity of wind, curing condition and ambient temperature. At initial stage, the convection heat transfer coefficient is overestimated by the evaporation quantity. So it is essential to modify the thermal equilibrium considered with the boiling effect. From experimental results, the convection heat transfer coefficient was calculated using equations of thermal equilibrium. Finally, the prediction model for equivalent convection heat transfer coefficient including effects of velocity of wind, curing condition, ambient temperature and boiling effects was theoretically proposed. The convection heat transfer coefficient in the proposed model increases with velocity of wind, and its dependance on wind velocity is varied with curing condition. This tendency is due to a combined heat transfer system of conduction through form and convection to air. From comparison with experimental results, the convection heat transfer coefficient by this model was well agreed with those by experimental results.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.37 no.11
• /
• pp.1023-1029
• /
• 2013

The integration between a gas turbine and an air separation unit (ASU) is important in IGCC plants. The portion of ASU air extracted from the gas turbine and the degree of nitrogen supply from the ASU to the gas turbine side are important operating parameters. Their effect on the gas turbine performance and operability should be considered in a wide ambient temperature range. In this study, appropriate nitrogen dilution rate and turbine inlet temperature that satisfy the two limitations of turbine blade temperature and maximum allowable power output were predicted. The air integration was set at zero. The simulation showed that the power output increases and turbine blade temperature decreases as the nitrogen dilution increases. The maximum allowable power output can be obtained under medium and low ambient temperature ranges. Under a high ambient temperature range, the achievable power is less than the maximum power.

• Journal of Environmental Policy
• /
• v.10 no.1
• /
• pp.27-47
• /
• 2011

Used as foundation resources for environment improvement and preservation of single-housing residential area by practicing classification of biotope with the concept of ecological area rate applied and performing urban thermal environment prediction simulation. Biotope is classified as seven types according to classification of biotope which is carried out with the concept of ecological area rate applied. The classification is listed below in descending order: building biotope(48.16%), impervious pavement biotope(39.75%), greenspace biotope(6.23%), crack permeable pavement biotope(3.26%), whole surface permeable pavement biotope(2.51%), parts permeable pavement biotope(0.04%). As a result of analysing prediction of variation and characteristics of thermal environment of single-housing residential area, land surface temperature per types of biotope are evaluated as listed below in descending temperature order: impervious pavement biotope > building biotope > greenspace biotope > permeable pavement biotope. In case 2 where vegetated roof hypothetically covers 100% of the roof area, temperature is predicted to be $33.58^{\circ}C$ Max, $23.85^{\circ}C$ Min, and $27.74^{\circ}C$ Avg. which is Approximately $5.19^{\circ}C$ lower than a non-vegetated roof. Average outdoor temperature for case 2 is studied to be $0.18^{\circ}C$ lower than case 1.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.37 no.11
• /
• pp.1015-1022
• /
• 2013

This study simulates the operation of a 200 kW class micro gas turbine that is currently under development. The performance and operating characteristics depending on the load control scheme (constant turbine inlet temperature versus constant turbine exit temperature) and ambient condition were investigated using detailed component performance data. The sensitivities of operating parameters, such as the compressor surge margin and flow path temperatures, according to unit fuel flow change were predicted for a wide load range. The sensitivity analysis showed that the steady state calculation provided useful information about the maximum surge margin reduction during load change.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.12 no.6
• /
• pp.609-615
• /
• 2000

The energy conservation is one of the most important issues in recent years. Especially, the energy conservation through improved control strategies is one of the most highly possible area to be implemented in the near future. The energy conservation of the ice storage system can be accomplished through the improved control strategies. A real time building load prediction algorithm was developed. The expected highest and the lowest outdoor temperature of the next day were used to estimate the next day outdoor temperature profile. The measured dry bulb temperature and the measured building load were used to estimate system parameters by using the on-line weighted recursive least square method. The estimated hourly outdoor temperatures and the estimated hourly system parameters were used to predict the next day hourly building loads. In order to see the effectiveness of the building load prediction algorithm, two different types of building models were selected and analysed. The simulation results show less than 1% in error for the prediction of the next day building loads. Therefore, this algorithm may successfully be used for the development of improved control algorithms of the ice storage system.

• Journal of the Korean Institute of Gas
• /
• v.23 no.5
• /
• pp.52-58
• /
• 2019

In this study, we have developed a forecasting model for city- gas acceptance. City-gas corporations have to report about city-gas sale volume next year to KOGAS. So it is a important thing to them. Factors influenced city-gas have differences corresponding to usage classification, however, in city-gas acceptence, it is hard to classificate. So we have considered tha outside temperature as factor that influence regardless of usage classification and the model development was carried out. ARIMA, one of the traditional time series analysis, and LSTM, a deep running technique, were used to construct forecasting models, and various Ensemble techniques were used to minimize the disadvantages of these two methods.Experiments and validation were conducted using data from JB Corp. from 2008 to 2018 for 11 years.The average of the error rate of the daily forecast was 0.48% for Ensemble LSTM, the average of the error rate of the monthly forecast was 2.46% for Ensemble LSTM, And the absolute value of the error rate is 5.24% for Ensemble LSTM.

• Proceedings of the SAREK Conference
• /
• 2009.06a
• /
• pp.1300-1305
• /
• 2009

The energy conservation in buildings affects environmental preservation as well as economic benefits, and creates the comfortable indoor environment set for the inhabitants. Especially, apartment buildings show ever-increasing energy consumption with large-sized and high-class tendency, thus energy saving counterplans are needed. The present study is to develop an optical control algorithm by using heating load curve according to the outdoor temperature change. Heating load analysis should be performed before the present method can be applied. Dynamic heating load simulations are performed by resistance-capacitance method. Results show that heating load decrease linearly according to the increase of outdoor temperature.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.2
• /
• pp.87-95
• /
• 2016

This study examined the characteristics of the hourly demand of city gas in Korea and proposed multiple regression models to obtain precise estimates of the hourly demand of city gas. Forecasting the hourly demand of city gas with accuracy is essential in terms of safety and cost. If underestimated, the pipeline pressure needs to be increased sharply to meet the demand, when safety matters. In the opposite case, unnecessary inventory and operation costs are incurred. Data analysis showed that the hourly demand of city gas has a very high autocorrelation and that the 24-hour demand pattern of a day follows the previous 24-hour demand pattern of the same day. That is, there is a weekly cycle pattern. In addition, some conditions that temperature affects the hourly demand level were found. That is, the absolute value of the correlation coefficient between the hourly demand and temperature is about 0.853 on average, while the absolute value of the correlation coefficient on a specific day improves to 0.861 at worst and 0.965 at best. Based on this analysis, this paper proposes a multiple regression model incorporating the hourly demand ahead of 24 hours and the hourly demand ahead of 168 hours, and another multiple regression model with temperature as an additional independent variable. To show the performance of the proposed models, computational experiments were carried out using real data of the domestic city gas demand from 2009 to 2013. The test results showed that the first regression model exhibits a forecasting accuracy of MAPE (Mean Absolute Percentage Error) around 4.5% over the past five years from 2009 to 2013, while the second regression model exhibits 5.13% of MAPE for the same period.

• Journal of the Microelectronics and Packaging Society
• /
• v.11 no.3 s.32
• /
• pp.71-76
• /
• 2004

The power consumption of TEC for Laser diode cooling was predicted by 3-D FEM simulation and verified by experiment. The operating conditions such as power consumption of Laser diode, set temperature, ambient temperature, resistance of thermal path was considered to estimate the TEC power consumption. Using 3-D FEM simulation, the relation between TEC configuration defined by the pellet dimension and the number and power consumption was investigated for low power consumption scheme. As a result, as the thermal resistance of the pellet increased, the power consumption decreased.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.8
• /
• pp.2793-2800
• /
• 2010

In this paper, we propose a quadratic (nonlinear) regression model that forecasts daily demands of electric power in summer. For cost-effective production (and/or procurement) of electric power, forecasting demands of electric power with accuracy is important, especially in summer when temperature is high. In the literature, temperature and daily demands of preceding days are typically employed to construct forecasting models. While, we consider another factor, day of the week, together with temperature and daily demands of preceding days. For validating the proposed model, we demonstrate the forecasting accuracy in terms of MAPE(Mean Absolute Percentage Error) and MPE(Maximum Percentage Error) using field data from KEPCO(Korea Electric Power Corporation) in comparison with two forecasting models in the literature. When compared with the two benchmarks, the proposed forecasting model performs far better providing MAPE and MPE not exceeding 3.08% and 8.99%, respectively, in summer from 2005 to 2009.