• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.7
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• pp.27-34
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• 2018

The energy consumption of apartment houses is affected by various factors. The criteria for assessing current energy usage are area, region and purpose. The purpose of this study is to obtain the reliability of the method of evaluating the existing energy consumption certificate and to derive usable evaluation factors according to the correlation of factors affecting energy consumption. The research process collects energy usage data for apartment houses in Daegu and calculates statistical results through correlation analysis and multiple regression analysis. As a result, it was found that the power energy is influenced by the yearly factor of physical characteristics, and the heat energy and total energy usage are influenced by the energy source which is energy characteristic factor.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.112-121
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• 2024

The pipping system is widely used in many industries as equipment for transporting fluids over long distances. In high-pressure pipe, as the speed of the fluid increases, a loud noise is generated. Therefore, various studies have been conducted to reduce pipe noise. In this paper, a pipe noise analysis was developed to predict and quantitatively assess the flow-induced vibration and acoustic-induced vibration due to valve flow in high-temperature and high-pressure. To do this, a high-fidelity fluid analysis technique was developed for predicting internal flow in the pipe with valve. In additional, the contribution of compressible/incompressible pressure by frequency band was evaluated using the wavenumber-frequency analysis. To predict a low/middle frequency pipe noise, the vibroacoustic analysis method was developed based on Finite Element Method (FEM). And the pipe noise prediction method for the middle/high frequency was developed based on Statistical Energy Analysis (SEA).

• Structural Engineering and Mechanics
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• v.46 no.4
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• pp.459-486
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• 2013

A novel damage classification method based on wavelet packet transform and statistical analysis is developed in this study for structural health monitoring. The response signal of a structure under an impact load is normalized and then decomposed into wavelet packet components. Energies of these wavelet packet components are then calculated to obtain the energy distribution. Statistical similarity comparison based on an F-test is used to classify the structure from changes in the wavelet packet energy distribution. A statistical indicator is developed to describe the damage extent of the structure. This approach is applied to the test results from simply supported reinforced concrete beams in the laboratory. Cases with single and two damages are created from static loading, and accelerations of the structure from under impact loads are analyzed. Results show that the method can be used with no reference baseline measurement and model for the damage monitoring and assessment of the structure with alarms at a specified significance level.

• KIEAE Journal
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• v.14 no.5
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• pp.59-65
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• 2014

Nowadays, reduction of energy use in buildings is a big issue, especially in public buildings like schools. The building structure is very simple in that, the room size, schedule and user number is similar across different schools. There are many policies which are suitable for this kind of buildings. Investigation of energy consumption pattern in primary school, middle school and high school in different cities of Korea has been done in this paper using statistical data from national organization and the data from IBM and Gyeonggi Provincial Office of Education, aimed at providing the basic data for the development of energy efficiency improvement policies of educational facilities. The study was divided according to climate, energy source type and public or private school, as different cities have different climates and accordingly different amount of energy sources are used. It was observed that, the average energy consumption in primary school is $36.9kWh/m^2$, in middle school is $20.5kWh/m^2$ and in high school $27.4kWh/m^2$. As further analysis, monthly energy consumption pattern has been analyzed for one city.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.197-202
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• 2006

The low-altitude earth observation satellite is generally equipped with high performance camera as a main payload which is vulnerable to vibration environment. During the launch process of a satellite, the combustion and jet noise of launch vehicle produce severe acoustic environment and the acoustic loads induced may damage the critical equipments of the satellite including the camera. Therefore to predict and simulate the effect of the acoustic environment which the satellite has to sustain at the lift-off event is very important process to support the load-resistive design and test-qualification of components. Statistical Energy Analysis(SEA) has been widely used to estimate the vibro-acoustic responses of the structures and gives statistical but reliable results in the higher frequency region with less modeling efforts and calculation time than the standard FEA. In this study, SEA technique has been applied to a 3-Dimensional model of a low-altitude earth observation satellite to predict the acceleration responses on the structural components induced by the high level acoustic field in the launch vehicle fairing. In addition, the expected response on each critical component panel was calculated by the classical method in consideration of the mass loading and imposed sound pressure level, and then compared with SEA results.

• Transactions of the Korean hydrogen and new energy society
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• v.31 no.6
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• pp.546-552
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• 2020

In this study, optimization research was conducted through statistical analysis with the aim of maximizing the efficiency of organic matter reduction and hydrogen production by applying electrolysis process at sewage treatment plant. Statistical analysis and optimal operating conditions of organic matter removal efficiency and H2 generation, which varied with various conditions in the electrolysis process, were derived using response surface methodology. As a result, 1,268 μS/cm of conductivity, 350 A current, and pH 3.2 was found to be the optimum condition to reach the desired value as 38% of organic matter reduction and 2.58 L/min of H2 production. The experiment also determined that the optimization study was reliable. Base on this study, it was confirmed that the removal of organic matter and hydrogen production could be stably by applying the electrolysis process in the sewage treatment plant.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.824-828
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• 2007

In this paper Statistical Energy Analysis has been considered to predict middle, high frequency air borne interior noise. PIM method is used for verification. Damping loss factor and coupling loss factor have been derived from the response(SPL) of sub systems when the power is applied. The airborne SEA model of vehicle is modeled through AutoSea2. Insulation material's absorption coefficient and transmission loss are acquired from closed form solution and experiment.

• Journal of the Korean Solar Energy Society
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• v.31 no.5
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• pp.99-104
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• 2011

It has to take quantitative energy usage of high school education facilities in nations to set goals of their energy reduction. Therefore, The purpose of this study is to present various analysis result of energy consumption that is a statistic alanalysis of high school education facilities in Korea to set the goal of energy saving. This study has enforced analysis and has provided used energy for the year 2008 and general information from 2022 high school education facilities in 16 cities in South Korea by the relevant agency. Used energy sources in high school education facilities are electricity, gas for heating, oil, coal, water, and this study has changed the various used energy sources as unit 'kWh' only for comparison and analysis them.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.4
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• pp.87-92
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• 2019

This paper describes the pattern analysis for data of the factory energy consumption by using machine learning method. While usual statistical methods or approaches require specific equations to represent the physical characteristics of the plant, machine learning based approach uses historical data and calculate the result effectively. Although rule-based approach calculates energy usage with the physical equations, it is hard to identify the exact equations that represent the factory's characteristics and hidden variables affecting the results. Whereas the machine learning approach is relatively useful to find the relations quickly between the data. The factory has several components directly affecting to the electricity consumption which are machines, light, computers and indoor systems like HVAC (heating, ventilation and air conditioning). The energy loads from those components are generated in real-time and these data can be shown in time-series. The various sensors were installed in the factory to construct the database by collecting the energy usage data from the components. After preliminary statistical analysis for data mining, time-series clustering techniques are applied to extract the energy load pattern. This research can attributes to develop Factory Energy Management System (FEMS).

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1996.04a
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• pp.144-150
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• 1996

The Energy Efficiency Standards and Labelling Act, as amended by the Rational Energy Utilization Act, provides energy efficiency standards and labellings for six equipment categories(viz, refrigerators, air-conditioners, fluorescent lamps and ballasts, incandescent lamps, cars) authorizes the Ministry of Trade. Industry and Energy (MOTIE) to prescribe amended or new energy efficiency standards and labelling standards. This study was initiated by the KIER(Korea Institute of Energy Research) in 1992. KIER's assessment of the appliance energy efficiency standards is designed to evaluate their statistical and engineering analysis according to Korean Industrial Standards(KS). And to make didtinction between the poor efficiency and good efficiency models. 5 grades are classified depending on their tested energy efficiency. This year, based on our analysis, MOTIE mandated updated standards for refrigerators, air-conditioners, Incandescent lamps, and fluorescent lamps.