• Environmental and Resource Economics Review
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• v.30 no.4
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• pp.581-605
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• 2021

The purpose of this study is to provide basic data for improving energy efficiency by estimating the regional energy efficiency in Korea using the stochastic frontier approach beyond the energy intensity that has been traditionally used as an indicator of energy efficiency. In this paper, energy efficiency and energy intensity efficiency were estimated as a stochastic distance function from 1998 to 2018 for 16 cities and provinces in Korea. In addition, the robustness of energy efficiency according to the capital stock estimation methods which had been mixed in previous studies was reviewed. As a result of the analysis, there is a significant change in regional rankings according to the three energy efficiency indicators, so they should be used complementary to each other. Second, while the energy efficiency improved little by little over time, the energy intensity efficiency decreased slightly though. Lastly, energy efficiency by region according to the capital stock estimation method was not robust. Care must be taken in estimating capital stock, which is important in economic analysis.

• Journal of the Korean Solar Energy Society
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• v.39 no.5
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• pp.29-40
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• 2019

In response to the rapid climate change, in order to save energy in the field of buildings, the country is planning not only zero energy buildings but also zero energy cities. In the Urban Development Project, the Energy Use Plan Report is prepared and submitted by predicting the amount of energy demand at the planning stage. However, due to the activation of zero-energy buildings and the increase in the supply of new and renewable energy facilities, the energy consumption behavior of buildings in the city is changing from the previous ones. In this study, to estimate urban energy demand of Zero Energy City, building energy demand forecasts based on "Passive plans for use of energy based primary energy consumption", "Actual building energy usage data from Korea Appraisal Board" and "data from Certification of Building Energy Efficiency Rating" as well as demand forecast according to existing "Consultation about Energy Use Plan Code" were calculated and then applied to Multifunctional Administrative City 5-1 zone to compare urban total energy demand forecasts.

• KIEAE Journal
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• v.14 no.4
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• pp.35-45
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• 2014

The main objective of this study is to provide an effective algorithm of the transmitted solar radiation calculation through window glazing on a clear day. This algorithm would be used in developing a computer program for fenestration system analysis and shading device design. Various simulation methods have been evaluated to figure out the most accurate and effective procedure in estimation of transmitted solar radiation on a tilted surface on a clear day. Characteristics of simulated results of each step have been scrutinized by comparing them with measured results of the site as well as results from other simulation programs. Generally, the Duffie & Beckman's solar calculation method introducing the HDKR anisotropic model provided the most reliable simulation results. The DOE-2 program usually provided over-estimated simulation results. The estimation of extraterrestrial solar radiation and beam normal radiation were conducted pretty accurately. However, the solar radiation either on horizontal surface or on tilted surface involves complicated factors in estimation. Even though the estimation results were close to the real measured data during summer when solar intensity is getting higher, the estimation provided more error when solar intensities were getting weaker. The convex polygon clipping algorithm with homogeneous coordinates was fastest model in calculation of sunlight to shaded area ratio. It could not be applied because of its shape limitation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.25-32
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• 2004

We propose a hierarchical disparity estimation algorithm with edge-preserving energy-based regularization. Initial disparity vectors are obtained from downsampled stereo images using a feature-based region-dividing disparity estimation technique. Dense disparities are estimated from these initial vectors with shape-adaptive windows in full resolution images. Finally, the vector fields are regularized with the minimization of the energy functional which considers both fidelity and smoothness of the fields. The first two steps provide highly reliable disparity vectors, so that local minimum problem can be avoided in regularization step. The proposed algorithm generates accurate disparity map which is smooth inside objects while preserving its discontinuities in boundaries. Experimental results are presented to illustrate the capabilities of the proposed disparity estimation technique.

• Structural Engineering and Mechanics
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• v.47 no.6
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• pp.757-771
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• 2013

We present a semi-rigid connection estimation method by using cross modal strain energy method. While rigid or pinned assumptions are adopted for steel frames in traditional modeling via finite element method, the actual behavior of the connections is usually neither. Semi-rigid joints enable connections to be modeled as partially restrained, which improves the quality of the model. To identify the connection stiffness and update the FE model, a newly-developed cross modal strain energy (CMSE) method is extended to incorporate the connection stiffness estimation. Meanwhile, the relations between the correction coefficients for the CMSE method are derived, which enables less modal information to be used in the estimation procedure. To illustrate the capability of the proposed parameter estimation algorithm, a four-story frame structure is demonstrated in the numerical studies. Several cases, including Semi-rigid joint(s) on single connection and on multi-connections, without and with measurement noise, are investigated. Numerical results indicate that an excellent updating is achievable and the connection stiffness can be estimated by CMSE method.

• Journal of the Korean Solar Energy Society
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• v.37 no.2
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• pp.23-33
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• 2017

Accurate prediction of stochastic behavior of occupants is a well known problem for improving prediction performance of building energy use. Many researchers have been tried various sensors that have information on the status of occupant such as $CO_2$ sensor, infrared motion detector, RFID etc. to predict occupants, while others have been developed some algorithm to find occupancy probability with those sensors or some indirect monitoring data such as energy consumption in spaces. In this research, various sensor data and energy consumption data are utilized for decision tree algorithms (C4.5 & CART) for estimation of sub-hourly occupancy status. Although the experiment is limited by space (private room) and period (cooling season), the prediction result shows good agreement of above 95% accuracy when energy consumption data are used instead of measured $CO_2$ value. This result indicates potential of IoT data for awareness of indoor environmental status.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.29-35
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• 1996

For the Reactor Coolant System(RCS) flow rate measurement by the secondary calorimetric heat balance method, the coolant temperature of the hot leg is needed. Several Resistance Temperature Detectors(RTD) are installed in the hot leg to measure the temperature, but the average value of RTDs does not correctly represent the energy-averaged(bulk) temperature because of the thermal stratification phenomenon. Therefore some correction is introduced to predict the bulk temperature, but the correction inevitably contains uncertainty because the stratification is not defined well quantitatively yet. Therefore a large uncertainty for the correction has been used for the conservative estimation. But unrealistically large uncertainty causes degradation of the measurement method and yields difficulty to meet the acceptance criterion in start-up flow measurement test. In this paper, an analytical estimation is made on the correction and the related uncertainty using the measured hot leg velocity profile of System 80 reactor flow model test and the measured temperatures of YGN 3&4 and PVNGS 1&2 start-up tests. The results reveal that the magnitude of the correction uncertainty is much smaller than that used in the previous design. Therefore, the confidence on the flow rate measurement method can be improved and the difficulty in start-up flow measurement test can be lessened if the smaller correction uncertainty obtained through this estimation is applied.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.2
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• pp.106-111
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• 2018

In this work, we propose techniques for estimating the SOC of Li-air battery. First, we describe and explain the operation principle of the Li-air battery. Energy density of the Li-air battery was compared with that of the Li-ion battery. The capacity and impedance value of the fully discharged voltage is analyzed, and the OCV value for SOC estimation is measured through the electrochemical characterization of the Li-air battery. Estimation value is obtained by SOC modeling through extended Kaman filter and is compared with the measurement value from the Coulomb counting method. Moreover, the performance of SOC estimation circuit is evaluated.

• 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.

• Nuclear Engineering and Technology
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• v.52 no.4
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• pp.846-855
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• 2020

A loose part monitoring system is used to detect unexpected loose parts in a reactor coolant system in a nuclear power plant. It is still necessary to develop a new methodology for the localization and mass estimation of loose parts owing to the high estimation error of conventional methods. In addition, model-based diagnostics recently emphasized the importance of a model describing the behavior of a mechanical system or component. The purpose of this study is to propose a new localization and mass-estimation method based on finite element analysis (FEA) and optimization technique. First, an FEA model to simulate the propagation behavior of the bending wave generated by a metal sphere impact is validated by performing an impact test and a corresponding FEA and optimization for a downsized steam-generator structure. Second, a novel methodology based on FEA and optimization technique was proposed to estimate the impact location and mass of a loose part at the same time. The usefulness of the methodology was then validated through a series of FEAs and some blind tests. A new feature vector, the cross-correlation function, was also proposed to predict the impact location and mass of a loose part, and its usefulness was then validated. It is expected that the proposed methodology can be utilized in model-based diagnostics for the estimation of impact parameters such as the mass, velocity, and impact location of a loose part. In addition, the FEA-based model can be used to optimize the sensor position to improve the collected data quality in the site of nuclear power plants.