• Journal of Soil and Groundwater Environment
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• v.17 no.6
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• pp.69-81
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• 2012

Diverse geostatistical tools such as kriging have been used to estimate the volume and spatial coverage of contaminated soil needed for remediation. However, many approaches frequently yield estimation errors, due to inherent geostatistical uncertainties. Such errors may yield over- or under-estimation of the amounts of polluted soils, which cause an over-estimation of remediation cost as well as an incomplete clean-up of a contaminated land. Therefore, it is very important to use a better estimation tool considering uncertainties arising from incomplete field investigation (i.e., contamination survey) and mathematical spatial estimation. In the current work, as better estimation tools we propose stochastic simulation approaches which allow the remediation volume to be assessed more accurately along with uncertainty estimation. To test the efficiency of proposed methods, heavy metals (esp., Pb) contaminated soil of a shooting range area was selected. In addition, we suggest a quantitative method to delineate the confident interval of estimated volume (and spatial extent) of polluted soil based on the spatial aspect of uncertainty. The methods proposed in this work can improve a better decision making on soil remediation.

• KIEAE Journal
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• v.8 no.4
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• pp.19-27
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• 2008

The carbon dioxide is brought from the energy consumption and regarded as a criteria material to estimate the Global Warming Potential. Building shares about 30% in national energy consumption and affects to environment as much as the energy consumption. But there is not enough data to forecast the amount of the carbon dioxide during the maintenance stage. Various factors are related with the energy consumption and carbon dioxide emission such as the physical area, the building exterior area, the maintenance type and location. Among these factors, the building carbon-dioxide emission can be estimated by the overall building characteristics such as the maintenance area, the number of household, the heating type, etc., The physical amount such as the thickness of the insulation and window infiltration could explained the limited scope and might not be use to estimate the total carbon-dioxide emission energy because the each value could not include or represent the overall building. In this paper, it provided the estimation model of the carbon-dioxide emission, explained by the overall building characteristics. These factors are shown as the maintenance area, no. of household, the heating type, the volume of the building, the ratio of the window to wall area etc., For providing the estimation model of th carbon-dioxide emission, it conducted the corelation analysis to filter the variables and suggested the estimation model with the power model and multiple regression model. Most of the model have a good statistics and fitted in the curve line.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.263-263
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• 2007

In the future, self-contained sensors and processing units will need on-board, renewable power supplies to be truly autonomous. One way of supplying such power is through energy harvesting, processes by which ambient forms of energy are converted into electricity. One energy harvesting technique involves converting kinetic energy, in the form of vibrations, into electrical energy through the use of piezoelectric materials. Researchers are currently investigating how piezoelectric materials can be used to harvest power. This study examines the use of auxiliary structures, consisting of a mechanical fixture and a lead zirconate/lead titanate (PZT) piezoelectric element, which can be attached to any boundary conditions vibrating beam of the any boundary conditions. Adjusting various boundary conditions of these structures can maximize the strain induced in the attached PZT element and improve power output.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.554-556
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• 2009

Wind classification for exact estimation of wind energy resources was carried out using numerically simulated wind data for three years. The MM5(a fifth-generation Mesoscale Model), developed at Penn State University and the National Center for Atmospheric Research (NCAR), was used to estimate the wind fields in this study. We also use a variant of the K-mean clustering to classify the wind district and define the relation between districts. Wind estimated at surface and 100 m high at Busan area is classified into the 10 and 7 classes, respectively. These discrepancies of wind districts pattern at surface and upper air meteorological data indicates the quantity of wind resources can be changed according to the level of wind data used in estimation. Therefore, the estimation of wind district classification by reasonable wind data is utilized to build the effective policy for wind energy dissemination.

• Journal of Power Electronics
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• v.10 no.6
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• pp.769-776
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• 2010

The ultracapacitor module has recently been recast for use in hybrid energy storage systems (HESSs). As a result, accurate state-of-charge (SOC) estimation for an ultracapacitor module is as important as that of primary sources in order to be utilized efficiently in an energy storage system (ESS). However, while SOC estimation via the open-circuit voltage (OCV) method is generally used due to its linear characteristics compared with other ESSs, this method results in many errors in cases of highcurrent charging/discharging within a short time period. Accordingly, this paper introduces a dynamic SOC estimation algorithm that is capable of SOC compensation of an ultracapacitor module even when there is a current input and output. A cycle profile that simulates the operating conditions of a mild-HEV was applied to a vehicle simulator to verify the effectiveness of the proposed algorithm.

• Advances in nano research
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• v.14 no.6
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• pp.527-539
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• 2023

Measuring energy burn during intensive combat sport has been a challenging concerns for a long time. In the present article, the energy consumption during combat sports is measured by use of wearable GoBe2 equipped with nanotechnology measuring devices. In this regard, 12 professional combat athletes were asked to wear GoBe2 devices during different sessions of intensive combat exercises. The curves provided by GoBe2 nano-sensor devices are further collected and analyzed for different combat durations. On the other hand, energy consumption in these athlete is calculated using other validated methods to evaluate reliability of GoBe2 wearable devices. Based on the results obtained from these experiments a multi-parameter mathematical model is presented for estimation of combat calorie consumptions. The results show that nanotechnology in these type of sensors could help in estimation of calorie consumption during combat. Moreover, the reliability of using wearable GoBe2 sensors are satisfactory except for some specific conditions. The mathematical model provides a satisfactory results based on athlete physical condition and also duration of the combat with about 8% error margin in the results.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.1-12
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• 2018

This paper presents a material estimation method using dual-energy X-ray images generated as a result of cargo inspection system in MeV region. We use new discrimination curve using logarithmic function rather than four discrimination curves commonly used in existing estimation algorithms. We also propose an atomic number estimation using the probability distribution of the logarithmic curve rather than linear interpolation. When the probability distribution is used as a weight, we used two methods of using the weight for the two nearest reference materials and the weight for all the reference materials. Experimental results showed that the atomic number estimation of materials using the probability distribution as a weight is more accurate than the existing methods. In order to visualize the estimated atomic number, the HSI model was used for color the resulting image.

• New & Renewable Energy
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• v.17 no.2
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• pp.1-8
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• 2021

We estimated the price range of electricity transactions under the prosumer system, considering the spread of renewable energy and the prospect of introducing a surplus power trading system between power consumers in Korea. The range (min/max) of power transaction prices was estimated by prosumers and consumers who could purchase electricity from utilities if needed. It is assumed that utilities purchased electricity from prosumers and consumers under a Time-of-Use (TOU) rate, trading at a monthly price. The range of available transaction prices according to the amount of power purchased from utilities and the amount of transaction power was also estimated. The price range that can be traded is expected to vary depending on variables such as the TOU rate, purchased and surplus power, levelized cost of electricity, etc.

• Journal of Energy Engineering
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• v.11 no.1
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• pp.34-46
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• 2002

Carbon accounting is a key issue in the discussions on global warming/CO$_2$mitigation. This paper applies both the IPCC Approach and the NEAT (Non-Energy use Emission Accounting Tables) model, a bottom-up approach, to estimate the potential CO$_2$ emissions (carbon storage) originating from the non-energy use as to assess the actual CO$_2$ emissions (carbon release) from the use of fossil fuels in Korea. The current Korean carbon accounting seems to overestimate the potential CO$_2$ emissions and with it to underestimate the actual CO$_2$ emissions. The estimation shows that the potential CO$_2$ emissions calculated according to the IPCC Approach are lower than those calculated using the NEAT model. This is because the IPCC default storage fraction for naphtha seems to be low for the Korean petrochemical production structure, on the one hand and because the IPCC Approach does not consider the trade with short life petrochemical products, on the other hand. This paper shows that a bottom-up approach like the NEAT model can contribute to overcome some of limitations of the IPCC guidelines, especially by considering the international trade with short life petrochemical products and by estimating the storage fractions of fossil fuels used as feedstocks for the country in consideration. This paper emphasizes the importance of accurate energy statistics for carbon accounting.

• Journal of the Korean Solar Energy Society
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• v.23 no.1
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• pp.57-67
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• 2003

This study aims to presents Evaluation Method of Green Remodeling that analyze the value of environment through expense, using the method of life cycle cost and life cycle assessment simultaneously. The results of this study are summarized as follows. Evaluation Model developed in this study can convert economical value of environment into cost by integrating. In addition, the model can apply as a useful tool to estimation of economical design alternative as well as quantification of environmental loads and costs. Evaluation Model presented In this study observe energy consumption and the environmental load emission with qualification, it can forecast effect of environmental cost that cost estimation is expected to be added to energy cost rate by being possible. Synthetically, when Estimation Model and computer program that developed in this study is applies to the construction industry; reasonable management of environmental load is convenient at each step of Green Remodeling. In addition, at preliminary design phase, practical use may be possible by reasonable yardstick about various alternatives and improvement of design alternatives likewise by grasping environmental effect.