• Journal of Korea Water Resources Association
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• v.43 no.9
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• pp.769-780
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• 2010

Topological and hydraulic assessments to examine whether required demand and pressure are satisfied and using these assessed results as a criteria have been general methodology for reliability assessment of water distribution systems. However, many of existing studies that used nodal pressure calculated by hydraulic assessment for reliability assessment have two major issues to be solved. The one is that demand-driven analysis was used for hydraulic assessment and the other is that serviceability was not considered for reliability assessment. In addition, all of the studies used pressure-demand analysis which is suitable to hydraulic analysis for water distribution systems under abnormal operating condition considered only available nodal demand for reliability assessment. This means that advantages which can be obtained by pressure-driven analysis are not used properly and efficiently. In this study, new methodology for reliability assessment of water distribution systems using HSPDA model and distance measure method is suggested. This methodology considers both nodal pressure and nodal available demand for reliability assessment. Suggested methodology is applied to two water distribution systems to show its applicability and application results are compared with existing study.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.11a
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• pp.65-70
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• 2005

Recently, Grid is embossed as a new issue according to the need of cooperation related to distributed resources, data sharing, Interaction and so on. It focuses on sharing of large scale resources, high-performance, applications of new paradigms, which improved more than established distributed computing. Because of the environmental specificity distributed geographically and dynamic, the most important problem in grid environment is to share and to allocate distributed grid resources. This paper proposes supply-driven strategies model that is applicable for resource management in grid environment and presents a optimal resource allocation algorithm based on resource demands. Supply-driven strategies model can offer efficient resource management by transaction allocation based on user demand and provider strategy. This paper implements the supply-driven strategies model on the DEVS modeling and simulation environment and shows the efficiency and excellency of this model by comparing with established models.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.4
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• pp.105-121
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• 2015

PDA model is new collection development method not only corresponding user's demand, but also expensing acquisition budget effectively. In the PDA model, when the trigger that indicates user's demand reaches up to treshold, e-book is automatically purchased without librarian's interrogation. This study examines concept, basic principles, and current condition of operation about PDA and finds a way that could applicate to Korean university library foreign E-book consortium. Current model of university library e-book acquisition pursuit reduction of budget and utility value, but the selected collection is not based on user's demand. Therefore, it could be considerable to apply PDA or evidence based purchase model to foreign e-book acquisition consortium.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.142-149
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• 2022

This study attempts to analyze the economic impact of the service robot industry using Input-Output analysis, which is conducted based on Demand-driven model, the Leontief price model, the Backward and Forward Linkage Effects, and the Exogenous Methods. In a Demand-driven model analysis, we can conclude that the service robot industry contains characteristics of both the manufacturing industry and the service industry, which causes a positive impact on the overall industry by compensating for the weaknesses of the two industries. The Leontief price analysis indicates when wages in the service robot industry increase, prices related to robot manufacturing also increase. Also, when profits in the service robot industry increase, prices related to service provision increase, too. The Backward and Forward Linkage Effects analysis shows that the service robot industry is highly sensitive to the current economic condition and has a great influence on the service industry. The service robot industry can highlight the aspect of service characteristics when the manufacturing industry is in recession and vice versa. In addition, the service robot industry can be regarded as a value-adding and domestic economy promoting industry which utilizes knowledge of information and communication technologies. It is important to foster the service robot industry in South Korea, which is in economic recession to provide an opportunity to stimulate the growth of both service and robot industries.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.1
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• pp.70-77
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• 2021

This paper was reclassified industries related to the 4th industrial revolution into manufacturing, information and communication services, finance and insurance services, and science and technology services by comparing the industry association table with the Korean standard industry classification. And the economic ripple effect was analyzed by exogenizing the four sectors of the industry using a demand-driven model. The wholesale and retail and product brokerage services were measured to be large in the manufacturing, information communication services, and science technology service sector according as a result of analysis of the production inducement effect, added value inducement effect, and employment inducement effect. And the financial and insurance services were analyzed to be large in the financial and insurance services sector. The import inducement effect was analyzed to be the largest in all sectors of the fourth industry. As a result of the forward and backward linkage effect, it was confirmed that the manufacturing and the information communication services sector were the intermediate primary production type sensitive to economic fluctuations. Also it was confirmed that the financial and insurance services and the science technology services sector were the final primary production type.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.93-106
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• 2020

This research explores how imported automobile companies can develop their strategies to improve the outcome of their recalls. For this, the researchers analyzed patterns of recall demand, classified recall types based on the demand patterns and examined response strategies, considering plans on how to procure parts and induce customers to visit workshops, recall execution capacity and costs. As a result, recalls are classified into four types: U-type, reverse U-type, L- type and reverse L-type. Also, as determinants of the types, the following factors are further categorized into four types and 12 sub-types of recalls: the height of maximum demand, which indicates the volatility of recall demand; the number of peaks, which are the patterns of demand variations; and the tail length of the demand curve, which indicates the speed of recalls. The classification resulted in the following: L-type, or customer-driven recall, is the most common type of recalls, taking up 25 out of the total 36 cases, followed by five U-type, four reverse L-type, and two reverse U-type cases. Prior studies show that the types of recalls are determined by factors influencing recall execution rates: severity, the number of cars to be recalled, recall execution rate, government policies, time since model launch, and recall costs, etc. As a component demand forecast model for automobile recalls, this study estimated the ARIMA model. ARIMA models were shown in three models: ARIMA (1,0,0), ARIMA (0,0,1) and ARIMA (0,0,0). These all three ARIMA models appear to be significant for all recall patterns, indicating that the ARIMA model is very valid as a predictive model for car recall patterns. Based on the classification of recall types, we drew some strategic implications for recall response according to types of recalls. The conclusion section of this research suggests the implications for several aspects: how to improve the recall outcome (execution rate), customer satisfaction, brand image, recall costs, and response to the regulatory authority.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.6
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• pp.421-428
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• 2014

For the analysis of water supply network, demand-driven and pressure-driven analysis methods have been proposed. Of the two methods, demand-driven analysis (DDA) can only be used in a normal operation condition to evaluate hydraulic status of a pipe network. Under abnormal conditions, i.e., unexpected pipe destruction, or abnormal low pressure conditions, pressure-driven analysis (PDA) method should be used to estimate the suppliable flowrate at each node in a network. In order to carry out the pressure-driven analysis, head-outflow relationship (HOR), which estimates flowrate at a certain pressure at each node, should be first determined. Most previous studies empirically suggested that each node possesses its own characteristic head-outflow relationship, which, therefore, requires verification by using actual field data for proper application in PDA modeling. In this study, a model pipe network was constructed, and various operation scenarios of normal and abnormal conditions, which cannot be realized in real pipe networks, were established. Using the model network, data on pressure and flowrate at each node were obtained at each operation condition. Using the data obtained, previously proposed HOR equations were evaluated. In addition, head-outflow relationship at each node was analyzed especially under multiple pipe destruction events. By analyzing the experimental data obtained from the model network, it was found that flowrate reduction corresponding to a certain pressure drop (by pipe destruction at one or multiple points on the network) followed intrinsic head-outflow relationship of each node. By comparing the experimentally obtained head-outflow relationship with various HOR equations proposed by previous studies, the one proposed by Wagner et al. showed the best agreement with the exponential parameter, m of 3.0.

• Transactions of the Korean hydrogen and new energy society
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• v.34 no.5
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• pp.398-412
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• 2023

The Korean government is actively promoting the hydrogen industry as a key driver of economic growth. This commitment is evident in the 2019 hydrogen economy activation roadmap and the 2021 basic plan for hydrogen economy implementation. This study quantitatively analyzes the economic impact of the hydrogen economy using input-output analysis based on the Bank of Korea's 2019 input-output table, projecting its size by 2050. Four parts dealt with production-inducing, value-added creation, employment-inducing, and wage-inducing based on a demand-driven model. The results reveal that transportation had the most remarkable economic effect throughout the hydrogen economy, and production was the least. The hydrogen economy is projected to reach 71.2 trillion won by 2050.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.89-100
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• 2011

The MAGLEV (Magnetically Levitated Vehicle) system, which is under commercialization as a new transportation system in Korea, is operated by means of unmanned automatic control system. Therefore the plan of train operation should be carefully established and validated in advance. In general, when making the train operation plan, the statistically predicted traffic data is used. However, traffic wave can occur when real train service is operated, and the demand-driven simulation technology is required to review train operation plans and service qualities considering traffic wave. This paper presents a method and model to simulate the MAGLEV's operation considering continuous demand changes. For this purpose, we employed the discrete event model which is suitable for modeling the behavior of railway passenger transportation, and modeled the system hierarchically using DEVS (Discrete Event System Specification) formalism. In addition, through the implementation and experiment using DEVSim++ simulation environment, we tested the feasibility of the proposed model and it is also verified that our demand-driven simulation technology could be used for the prior review of the train operation plans and strategies.

• Journal of Energy Engineering
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• v.25 no.4
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• pp.37-52
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• 2016

This study attempts to compare the role of the oil refinery industry in the Korean and Japanese national economy using an inter-industry analysis. First of all, the study conducts a comparative analysis on production-inducing effects and value-added creation effects of the oil refinery industry based on demand-driven model. Moreover, we investigate the supply shortage effects and sectoral pervasive effects of price change by using supply-driven model and Leontief price model, respectively. These analyses have been done by specifying the oil refinery industry as not endogenous but exogenous. The results show that1 won of production or investment in the oil refinery industry induces 0.2620 won and 0.6537 won of production in other industries of Korea and Japan, respectively. The former is less than the latter. It also creates 0.0946 won and 0.0536 won of value-added in other industries of Korea and Japan, respectively. The first is larger than the second. The effects of 1 won of supply shortage in oil refinery industry on other industries are computed to be 0.9657 won and 1.4476 won for Korea and Japan, respectively, and thus the former is smaller than the latter. Finally, the pervasive effects of 10% price change in oil refinery industry are estimated to be 0.3819% and 0.3409% in Korea and Japan, respectively, and thus the first is larger than the second.