• 통합자연과학논문집
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• 제12권1호
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• pp.20-23
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• 2019

Demand response is usually operated through using the power rates and incentives. Demand management based on power charges is the most rational and efficient demand management method, and such methods include rolling base charges with peak time, sliding scaling charges depending on time, sliding scaling charges depending on seasons, and nighttime power charges. Search for other methods to stimulate resources on demand by actively deriving the demand reaction of loads to increase the energy efficiency of loads. In this paper, ESS algorithm for saving energy based on predicting the amount of solar power generation that can be used for buildings with small loads not under electrical grid.

• Structural Engineering and Mechanics
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• 제60권6호
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• pp.1021-1038
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• 2016

Considerable part of reinforced concrete building has suffered from destructive earthquakes in Turkey. This situation makes necessary to determine nonlinear behavior and seismic performance of existing RC buildings. Inelastic response of buildings to static and dynamic actions should be determined by considering both flexural plastic hinges and brittle shear hinges. However, shear capacities of members are generally neglected due to time saving issues and convergence problems and only flexural response of buildings are considered in performance assessment studies. On the other hand, recent earthquakes showed that the performance of older buildings is mostly controlled by shear capacities of members rather than flexure. Demand estimation is as important as capacity estimation for the reliable performance prediction in existing RC buildings. Demand estimation methods based on strength reduction factor (R), ductility (${\mu}$), and period (T) parameters ($R-{\mu}-T$) and damping dependent demand formulations are widely discussed and studied by various researchers. Adopted form of $R-{\mu}-T$ based demand estimation method presented in Eurocode 8 and Turkish Earthquake Code-2007 and damping based Capacity Spectrum Method presented in ATC-40 document are the typical examples of these two different approaches. In this study, eight different existing RC buildings, constructed before and after Turkish Earthquake Code-1998, are selected. Capacity curves of selected buildings are obtained with and without considering the brittle shear capacities of members. Seismic drift demands occurred in buildings are determined by using both $R-{\mu}-T$ and damping based estimation methods. Results have shown that not only capacity estimation methods but also demand estimation approaches affect the performance of buildings notably. It is concluded that including or excluding the shear capacity of members in nonlinear modeling of existing buildings significantly affects the strength and deformation capacities and hence the performance of buildings.

• 한국임상보건과학회지
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• 제4권4호
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• pp.769-781
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• 2016

Purpose. The purpose of this paper was to analyze the educational needs of industry which will hire learner and to develop curriculum to meet the demand. Methods. This study was a descriptive research based on survey results. In each questionnaire, the number of responses and ratios were measured to determine the priorities of the questionnaire items and the education demand was evaluated based on these priorities. Results. The core competency keywords for nurses in industry are knowledge, technology, and communication. In the industry needs for curriculum development, the importance of education to be strengthened for nurse training was found to be core basic nursing skills, nursing process application ability, communication ability, creative nursing problem solving ability, personality and foreign language ability. Conclusion. This study has laid the groundwork for the development of competency based curriculum based on environmental factors and reducing the problems of mis - matching between industry and education.

• 한국지진공학회논문집
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• 제26권1호
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• pp.31-38
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• 2022

Based on the nonlinear static analysis and the approximate seismic evaluation method adopted in "Guidelines for seismic performance evaluation for existing buildings, two methods to calculate strength demand for retrofitting individual structural walls in unreinforced masonry buildings are proposed." The displacement coefficient method to determine displacement demand from nonlinear static analysis results is used for the inverse calculation of overall strength demand required to reduce the displacement demand to a target value meeting the performance objective of the unreinforced masonry building to retrofit. A preliminary seismic evaluation method to screen out vulnerable buildings, of which detailed evaluation is necessary, is utilized to calculate overall strength demand without structural analysis based on the difference between the seismic demand and capacity. A system modification factor is introduced to the preliminary seismic evaluation method to reduce the strength demand considering inelastic deformation. The overall strength demand is distributed to the structural walls to retrofit based on the wall stiffness, including the remaining walls or otherwise. Four detached residential houses are modeled and analyzed using the nonlinear static and preliminary evaluation procedures to examine the proposed method.

• 경영과학
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• 제29권3호
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• pp.121-134
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• 2012

In this study, we consider a component procurement planning problem where the procurement amounts of components are determined under assemble-to-order systems with demand uncertainty. In the problem, procurement amount of each component is decided before the demands of finished products are known and after the demands are identified the assembly amounts of the finished products are decided. In this study, the objective function of the problem is minimizing the total costs which are composed of purchase and inventory costs of the components and the backorder costs of the finished products. We assume that the uncertain demand information is given as multiple scenarios of the demands, and we propose procurement planning methods based on stochastic models which considering the multiple demand scenarios. To evaluate the performances of the proposed methods, computational experiments were carried out on the proposed methods as well as benchmarks including a method based on deterministic mathematical model and a heuristic. From the results of the computational tests, the superiorities of the proposed methods were shown.

• Journal of Electrical Engineering and Technology
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• 제4권2호
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• pp.159-167
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• 2009

This paper presents the Improved Pre-prepared Power Demand (IPPD) table and Muller's method as a means of solving the Profit Based Unit Commitment (PBUC) problem. In a deregulated environment, generation companies (GENCOs) schedule their generators to maximize profits rather than to satisfy power demand. The PBUC problem is solved by the proposed approach in two stages. Initially, information concerning committed units is obtained by the IPPD table and then the subprob-lem of Economic Dispatch (ED) is solved using Muller's method. The proposed approach has been tested on a power system with 3 and 10 generating units. Simulation results of the proposed approach have been compared with existing methods and also with traditional unit commitment. It is observed from the simulation results that the proposed algorithm provides maximum profit with less computational time compared to existing methods.

• 산업경영시스템학회지
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• 제40권4호
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• pp.29-37
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• 2017

This papers focuses on remanufacturing processes in a closed loop supply chain. The remanufacturing processes is considered as one of the effective strategies for enterprises' sustainability. For this reason, a lot of companies have attempted to apply remanufacturing related methods to their manufacturing processes. While many research studies focused on the return rate for remanufacturing parts as a control parameter, the relationship with demand certainties has been studied less comparatively. This paper considers a closed loop supply chain environment with remanufacturing processes, where highly fluctuating demands are embedded. While other research studies capture uncertainties using probability theories, highly fluctuating demands are modeled using a fuzzy logic based ambiguity based modeling framework. The previous studies on the remanufacturing have been limited in solving the actual supply chain management situation and issues by analyzing the various situations and variables constituting the supply chain model in a linear relationship. In order to overcome these limitations, this papers considers that the relationship between price and demand is nonlinear. In order to interpret the relationship between demand and price, a new price elasticity of demand is modeled using a fuzzy based nonlinear function and analyzed. This papers contributes to setup and to provide an effective price strategy reflecting highly demand uncertainties in the closed loop supply chain management with remanufacturing processes. Also, this papers present various procedures and analytical methods for constructing accurate parameter and membership functions that deal with extended uncertainty through fuzzy logic system based modeling rather than existing probability distribution based uncertainty modeling.

• 전기학회논문지P
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• 제63권4호
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• pp.307-311
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• 2014

Due to the increasing of power consumption, it is difficult to construct accurate prediction model for daily peak power demand. It is very important work to know power demand in next day for manager and control power system. In this research, we develop a daily peak power demand prediction method considering of characteristics of day of week. The proposed method is composed of liner model based on AR model and nonlinear model based on ELM to resolve the limitation of a single model. Using data sets between 2006 and 2010 in Korea, the proposed method has been intensively tested. As the prediction results, we confirm that the proposed method makes it possible to effective estimate daily peak power demand than conventional methods.

• Structural Engineering and Mechanics
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• 제10권4호
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• pp.405-426
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• 2000

Two approximate methods based on mechanism analysis suitable for seismic assessment/design of structural concrete are reviewed. The methods involve use of equal energy concept or equal displacement concept along with appropriate patterns of inelastic deformations to relate structure's maximum lateral displacement to member and plastic deformations. One of these methods (Clough's method), defined here as a ductility-based approach, is examined in detail and a modification for its improvement is suggested. The modification is based on estimation of maximum inelastic displacement using inelastic design response spectra (IDRS) as an alternative to using equal energy concept. The IDRS for demand displacement ductilities are developed for a single degree of freedom model subjected to several accelerograms as functions of response modification factor (R), damping ratios, and strain hardening. The suggested revised methodology involves estimation of R as the ratio of elastic strength demand to code level demand, and determination of design base shear using $R_{design}{\leq}R$ and maximum displacement, determination of plastic displacement using IDRS and subsequent local plastic deformations. The methodology is demonstrated for the case of a 10-story precast wall panel building.

• Journal of Biosystems Engineering
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• 제38권1호
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• pp.9-17
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• 2013

Purpose: The goal of this study was to develop a methodology for the demand forecast of tractor, riding type rice transplanter and combine harvester using an ARIMA (autoregressive integrated moving average) model, one of time series analysis methods, and to forecast their demands from 2012 to 2021 in South Korea. Methods: To forecast the demands of three kinds of machines, ARIMA models were constructed by following three stages; identification, estimation and diagnose. Time series used were supply and stock of each machine and the analysis tool was SAS 9.2 for Windows XP. Results: Six final models, supply based ones and stock based ones for each machine, were constructed from 32 tentative models identified by examining the ACF (autocorrelation function) plots and the PACF (partial autocorrelation function) plots. All demand series forecasted by the final models showed increasing trends and fluctuations with two-year period. Conclusions: Some forecast results of this study are not applicable immediately due to periodic fluctuation and large variation. However, it can be advanced by incorporating treatment of outliers or combining with another forecast methods.