• Journal of Energy Engineering
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• v.24 no.2
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• pp.9-16
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• 2015

As electricity is an indispensable input to human's existence and industrial production, economic benefits arise from consumption. The economic benefits of the electricity consumption are useful information in various fields of electricity-related policy. Therefore, this study attempts to value the economic benefits from electricity use. The economic benefit of electricity consumed is the area under the demand curve which made of the sum of the actual consumer expenditure and the consumer surplus. Consumer expenditure can be easily observed but the information on price elasticity of demand is necessarily required to compute consumer surplus. This study derives the estimates for price elasticities through literature review. The price elasticities of the electricity demand for residence, industry, and commercial are estimated to be -0.332, -0.351, and -0.263, respectively. Because the consumer surplus of the electricity consumption for residence, industry, and commercial are computed to be 191.54, 143.44, and 231.91 won per kWh, respectively. Given that average prices of electricity use were 127.02, 100.70, and 121.98 won per kWh for the year 2013, the economic benefit are calculated to be 318.56, 244.14, and 353.89 won per kWh, respectively. We can convert the values to 321.96, 246.75, and 357.67 won per kWh in 2014 constant price, respectively, using consumer price index. They can be used in the economic feasibility analysis of a new electricity supply project.

• Journal of Korean Society of Transportation
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• v.29 no.6
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• pp.97-106
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• 2011

Mode choice model is an essential element for estimating- the demand of new means of transportation in the planning stage as well as in the establishment phase. In general, current demand analysis model developed for the mode choice analysis applies common parameters of utility function in each region which causes inaccuracy in forecasting mode choice behavior. Several critical problems from using common parameters are: a common parameter set can not reflect different distribution of coefficient for travel time and travel cost by different population. Consequently, the resulting model fails to accurately explain policy variables such as travel time and travel cost. In particular, the nonlinear logit model applied to aggregation data is vulnerable to the aggregation error. The purpose of this paper is to consider the regional characteristics by adopting the parameters fitted to each area, so as to reduce prediction errors and enhance accuracy of the resulting mode choice model. In order to estimate parameter of each area, this study used Household Travel Survey Data of Metropolitan Transportation Authority. For the verification of the model, the value of time by marginal rate of substitution is evaluated and statistical test for resulting coefficients is also carried out. In order to crosscheck the applicability and reliability of the model, changes in mode choice are analyzed when Seoul subway line 9 is newly opened and the results are compared with those from the existing model developed without considering the regional characteristics.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.8
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• pp.692-700
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• 2014

In this work, satellite FE (finite element) model updating for the prediction of the effect of micro-vibration is described. In the case of satellites launched in low earth orbit, high agility and more mission accomplishments are required by the customer in order to procure many images from satellites. To achieve the goal, many mechanisms, including high capacity wheels and antennas with multi-axis gimbals have been widely adopted, but they become a source of micro-vibration which could significantly deteriorate the quality of images. To investigate the effect due to the micro-vibration in orbit on the ground, a prediction is conducted through an integrated model coupling the measured jitter sources with FE (finite element) model. Before prediction, the FE model is updated to match simulation results with the modal survey test. Subsequently, the quality of FE model is evaluated in terms of frequency deviation error, the resemblance of mode shapes and FRFs (frequency response functions) between test and analysis.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.4
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• pp.611-634
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• 2017

In rapid urbanization, demand for utility tunnel increases more, and tunnel boring machine (TBM) has been used widely. Prediction of TBM penetration rate is important for proper estimation of construction period and cost. Although there are several methods, such as NTNU model and CSM model that require many input parameters, fundamental understanding on correlations between rock properties and TBM penetration rate is critical. In this study, we explored the brittleness indices of hard rocks according to various definitions, and the correlations between the brittleness indices and the TBM penentration rates.

• The Journal of Society for e-Business Studies
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• v.15 no.1
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• pp.89-101
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• 2010

In some industries, manufacturing firms' distinctive competences include not only product superiority but also service excellence. For example, in a highly volatile and dynamic market, flexibility and responsiveness are more valued than just the product cost. And sales order processing, in that respect is a very important process. However, previous studies on sale order processing have considered only due-date assignments or dealt with production scheduling to minimize production cost or delivery lead time. Due to recent advances in information technology, a new approach is possible in dealing with sales order processing. For example, RFID(Radio Frequency IDentification) and ubiquitous computing technology adds real time visibility and traceability to supply chain. In this study, we develop a new due-date re-negotiation process for sales order management and propose a new business integration model to support the re-negotiation process based on RFID, ubiquitous computing technology and RosettaNet's PIPs.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.149-159
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• 2012

The evaluation of public transit service quality is more complicated than evaluating other aspects of transportation service. Although various measures of effectiveness [MOEs] for transit service have been studied and applied, a more comprehensive and accurate MOE is still required. In the past, either data from user surveys or the experience of bus agency administrators and/or engineers used to measure the quality of service. However, recently, with reliable and accurate real time data from BMS(Bus Management System) and BIS(Bus Information System), more reliable and accurate MOEs are available. This study develops a service evaluation model from users' perspectives, which is based on user' cost models that consider passenger access time, riding time, waiting time, and discomfort due to in-vehicle overcrowding, violation of traffic laws, and accident rate. For validating proposed model, data from the BMS and transit-fare cards (T-Money Card) for Seoul's No. 472 main bus line were used. Models developed in this study provided reliable results.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.49-62
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• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.8
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• pp.881-887
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• 2012

CFRP composite materials have been widely used in various fields of engineering because of their excellent properties. They show high specific stiffness and specific strength compared with metallic materiasl. Woven CFRP composite materials are fabricated from carbon fibers with two orientation angles ($0^{\circ}/90^{\circ}$), which influences the mechanical properties. Therefore, woven CFRP composite materials show different types of fracture behavior according to the load direction. Therefore, the fracture behavior of these materials needs to be evaluated according to the load direction when designing structures using these materials. In this study, we evaluate the fracture strength of plain-woven CFRP composite materials according to the load direction. We performed tests for six different angles (load direction: $0^{\circ}/90^{\circ}$, $30^{\circ}/-60^{\circ}$, $+45^{\circ}/-45^{\circ}$) and estimated the fracture strength for an arbitrary fiber angle by using the modified Tan's theory and harmonic function.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4D
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• pp.345-356
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• 2012

Road pavement requires repetitive maintenance works to maintain satisfactory service level to the public. However, the repetitive maintenance works upon deteriorated pavement structure make negative effects to deterioration speed. It often leads to inefficient use of limited budget. For that reason, the pavements require reconstruction work to recover their original performance. Recently, construction demands in the Korean national highway have already been reached to maximum level, and the aged pavements start to demand much more reconstruction works. However, in the real world, road agencies have often been confused when they determine maintenance design for such aged road sections due to budget constraint. It is because there is no reliable long-term maintenance strategy that supports their decision making. To support their decision making, this paper aimed to suggest the best maintenance strategy considering changing process of pavement performance by repetitive maintenance works. As an analysis method, probability distribution and hazard function to estimate the life expectancy were adopted, and then the results were used for long-term life cycle cost analysis with deterministic or Monte-Carlo method under various scenarios. As an empirical study, the Korean national highway data that has long-maintenance history data since 1986 has been applied. Last, this paper considered quality assurance of maintenance work to improve maintenance quality. These could be important information as a part of long-term maintenance strategy of pavement.

• Korean Journal of Construction Engineering and Management
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• v.16 no.1
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• pp.74-81
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• 2015

As one of urban infrastructure system, the electricity substation is critical for urban life and industrial activity as the electricity demands get higher than ever. However the substation is generally regarded as unpleasant or dangerous facility, which finally results in the continuous opposition movement by resident due to the belief of unidentified negative effect in apartment prices. Accordingly, as the scientifically objective and quantitative analysis is required to solve the social conflict, this study intends to examine the variation affected by urban infrastructure system, expecially for substation. After the independent variable defining the price of apartment and the dependent variable, which is apartment price, are identified and their spatial data has been filed, the forecasting model has been developed through the hedonic price function as well as artificial neural networks system. The research finding indicated that the spatial range affected by substation is not notable and the range of some case was applicable for less than 600m. It is expected that these research findings can be applied for establishing the one of solid cases for the analysis of economical effect to local housing market by the urban infrastructure system.