• Nuclear Engineering and Technology
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• v.46 no.1
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• pp.55-62
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• 2014

A method for estimating software reliability for nuclear safety software is proposed in this paper. This method is based on the software reliability growth model (SRGM), where the behavior of software failure is assumed to follow a non-homogeneous Poisson process. Two types of modeling schemes based on a particular underlying method are proposed in order to more precisely estimate and predict the number of software defects based on very rare software failure data. The Bayesian statistical inference is employed to estimate the model parameters by incorporating software test cases as a covariate into the model. It was identified that these models are capable of reasonably estimating the remaining number of software defects which directly affects the reactor trip functions. The software reliability might be estimated from these modeling equations, and one approach of obtaining software reliability value is proposed in this paper.

• Current Photovoltaic Research
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• v.11 no.1
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• pp.27-33
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• 2023

In this paper, a machine learning model by using a regression algorithm is proposed to estimate the power generation performance of the BIPV system. The physical model formula for estimating the generation performance and the proposed model were compared and analyzed. For the physical model formula, simple efficiency model, temperature correction model, and regressive physics model for changing an irradiance were used. As a result, when comparing the regressive physics model for changing an irradiance and the proposed model with the actual generation measured data, the respective RMSE values are 0.1497 kW, 0.0451 kW and the accuracy values are 86.44%, and 96.56%. Therefore, the proposed model implemented in this experiment can be useful in estimating power generation.

• Proceedings of the Korean Society of Environment and Ecology Conference
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• 2008.04a
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• pp.137-139
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• 2008

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.16 no.2
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• pp.115-122
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• 1987

• Knowledge Management Research
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• v.9 no.4
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• pp.51-63
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• 2008

Effective energy consumption now becomes one of the area of knowledge management which potentially gives global impact. It is considerable for the energy management to optimize the usage of energy, rather than decreasing energy consumption at any cases. To resolve these challenges, an intelligent and personalized system which helps the individuals control their own behaviors in an optimal and timely manner is needed. So far, however, since the legacy energy management systems are nation-wide or organizational, individual-level energy management is nearly impossible. Moreover, most estimating methods of energy consumption are based on forecasting techniques which tend to risky or analysis models which may not be provided in a timely manner. Hence, the purpose of this paper is to propose a novel individual-level energy management system which aims to realize timely and personalized energy management based on context-aware computing approach. To do so, an index model for energy consumption is proposed with a corresponding service framework.

• Journal of Korea Multimedia Society
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• v.14 no.2
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• pp.288-294
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• 2011

In this paper we define the probability models for determining the disparity map given stereo images and derive the methods for solving the problem, which is proven to be equivalent to an energy-based stereo matching. Under the assumptions the difference between the pixel on the left image and the corresponding pixel on the right image and the difference between the disparities of the neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameter is proposed. The proposed method alternates between estimating the parameters with the intermediate disparity map and estimating the disparity map with the estimated parameters, after computing it with random initial parameters. Our algorithm is applied to the stereo matching algorithms based on the dynamic programming and belief propagation to verify its operation and measure its performance.

• International Journal of Highway Engineering
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• v.17 no.2
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• pp.143-150
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• 2015

PURPOSES : The authors set out to estimate the related carbon emissions, energy use, and costs of the national freeways and highways in Korea. To achieve this goal, a macro-level methodology for estimating those amounts by road type, road structure type, and road life cycle was developed. METHODS : The carbon emissions, energy use, and costs associated with roads vary according to the road type, road structure type, and road life cycle. Therefore, in this study, the road type, road structure type, and road life cycle were classified into two or three categories based on criteria determined by the authors. The unit amounts of carbon emissions and energy use per unit road length by classification were estimated using data gathered from actual road samples. The unit amounts of cost per unit road length by classification were acquired from the standard cost values provided in the 2013 road business manual. The total carbon emissions, energy use, and cost of the national freeways and highways were calculated by multiplying the road length by the corresponding unit amounts. RESULTS: The total carbon emissions, energy use, and costs associated with the national freeways and highways in Korea were estimated by applying the estimated unit amounts and the developed method. CONCLUSIONS: The developed method can be employed in the road planning and design stage when decision makers need to consider the impact of road construction from an environmental and economic point of view.

• Journal of electromagnetic engineering and science
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• v.18 no.2
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• pp.94-100
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• 2018

Partial discharges (PDs) are electrical sparks that occur inside insulation between two conducting electrodes and can lead to the disastrous failure of insulation systems. To determine the location of a PD, a distributed array of UHF PD sensors is used to detect the electromagnetic (EM) signals emitted from the PD source, and the localization of the PD source can be estimated using the time difference of arrival (TDOA) between EM signals captured by the UHF PD sensor array. There are four popular methods to estimate the TDOA-the first peak method, the cross-correlation method, the energy criterion method, and the average time window threshold method. In this work, we numerically investigate the influence of noise on estimating the TDOA for the four different methods. Numerical results show that the energy criterion method is more robust against noise than other methods.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.4
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• pp.252-259
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• 2009

When various kinds of outputs are produced from a single energy system, the methodology which allocates the common cost to each output cost is very important because it is directly related with the profit and loss of producers and purchasers. In the cost allocation methodology of the heat and the electricity on a cogeneration, there are energy method, work method, proportional method, benefit distribution method, various exergetic methods, and so on. On the other hand, we have proposed a worth evaluation method which can be applied to any system. The definition of this methodology is that the unit cost of a product is proportion to the worth. Where, worth is a certain evaluating basis that can equalize the worth of products. In this study, we applied this methodology to a gas-turbine cogeneration which produces 119.2 GJ/h of electricity and 134.7 GJ/h of steam, and then we allocated 3,150 $/h of fuel cost to electricity cost and steam cost. Also, we compared with various cost allocation methods. As the result, we conclude that reversible work of various kinds of worth basis evaluates the worth of heat and electricity most reasonably.

• New & Renewable Energy
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• v.20 no.1
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• pp.79-87
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• 2024

This study introduces a method for estimating Aerosol Optical Depth (AOD) using Broadband Aerosol Optical Depth (BAOD) derived from direct normal irradiance and meteorological factors observed between 2016 and 2017. Through correlation analyses between BAOD and atmospheric components such as Rayleigh scattering, water vapor, and tropospheric nitrogen dioxide, significant relationships were identified, enabling accurate AOD estimation. The methodology demonstrated high correlation coefficients and low Root Mean Square Errors (RMSE) compared to actual AOD₅₀₀ measurements, indicating that the attenuation effects of water vapor and the direct impact of tropospheric nitrogen dioxide concentration are crucial for precise aerosol optical depth estimation. The application of BAOD for estimating AOD₅₀₀ across various time scales-hourly, daily, and monthly-showed the approach's robustness in understanding aerosol distributions and their optical properties, with a high coefficient of determination (0.96) for monthly average AOD₅₀₀ estimates. This study simplifies the aerosol monitoring process and enhances the accuracy and reliability of AOD estimations, offering valuable insights into aerosol research and its implications for climate modeling and air quality assessment. The findings underscore the viability of using BAOD as a surrogate for direct AOD₅₀₀ measurements, presenting a promising avenue for more accessible and accurate aerosol monitoring practices, crucial for improving our understanding of aerosol dynamics and their environmental impacts.