• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1999.12a
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• pp.21-25
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• 1999

Planning support systems(PSS) add more advanced spatial analysis functions than Geographic information systems(GIS) and intertemporal functions to the functions of spatial decision support systems(SDSS). This paper reports the continuing development of a PSS providing a framework that facilitates urban planners and civil engineers in conducting coherent deliberations about planning, design and operation & maintenance(O&M) of water-distribution networks for urban growth management. The PSS using dynamic optimization model, modeling-to-generate-alternatives, value engineering(VE) and life-cycle cost(LCC) can generate network alternatives in consideration of initial cost and O&H cost. Users can define alternatives by the direct manipulation of networks or by the manipulation of parameters in the models. The water-distribution network analysis model evaluates the performance of the user-defined alternatives. The PSS can be extended to include the functions of generating sewer network alternatives, combining water-distribution and sewer networks, eventually the function of planning, design and O&H of housing sites. Capacity expansion by the dynamic water-distribution network optimization model using MINLP includes three advantages over capacity expansion using optimal control theory(Kim and Hopkins 1996): 1) finds expansion alternatives including future capacity expansion times, sizes, locations, and pipe types of a water-distribution network provided, 2) has the capabilities to do the capacity expansion of each link spatially and intertemporally, and 3) requires less interaction between models. The modeling using MINLP is limited in addressing the relationship between cost, price, and demand, which the optimal control approach can consider. Strictly speaking, the construction and O&M costs of water-distribution networks influence the price charged for the served water, which in turn influence the. This limitation can be justified in rather small area because price per unit water in the area must be same as that of neighboring area, i.e., the price is determined administratively. Planners and engineers can put emphasis on capacity expansion without consideration of the relationship between cost, price, and demand.

• Korea journal of population studies
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• v.25 no.1
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• pp.257-289
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• 2002

In this study we analyse how the tobacco prices have an effect on the national health. The level of tobacco price will fluctuate its consumers demand and eventually affect the national health status. We estimate tobacco consumption function as well as households'demand system in which tobacco and health expenditure functions are included. Demand elasticities are estimated and evaluated in order to find future policies to improve the national health by controlling the national tobacco consumption There are two econometric approaches app1ied in this study. The lent tobacco demand analysis method is mm tobacco consumption function model. Using national indices of tobacco price, tobacco consumption and other related variables, tobacco consumption function is estimated. The other is micro demand system analysis by using Korean urban households expenditure data during the period of 1991 to 1999. The own price elasticity which is estimated from national tobacco demand per capita is -0.19 for all people and -0.176 for the adults over 18, which means 100% price increase will cause decease of tobacco demand at 19% and 17.6% per each The cross vice elasticity which is estimated between tobacco and health expenditure of urban households demand system is -0.2328, which implies 100% of tobacco price increase will decrease 23.28% of health expenditure. The low price elasticities imply that tobacco price increase will increase total tobacco sales volume. 100% of tobacco price increase will bring about 79% increase of total tobacco sales volume according to our scenario. Korea's tobacco demand is negatively responsive to fluctuations in its price. The health expenditure is also negatively relatedto the tobacco price fluctuation. These empirical outputs could be utilized as the basis of government's tax policy to control national tobacco consumption in the future.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2490-2495
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• 2005

The scheduling of plant should be determined based on the product demands correctly forecasted by reasonable methods. However, because most existing forecasting packages need user's knowledge about forecasting, it has been hard for plant engineers without forecasting knowledge to apply forecasted demands to scheduling. Therefore, a forecasting module has been developed for plant engineers without forecasting knowledge. In this study, for the development of the forecasting module, an automatic method using the ARIMA model that is framed from the modified Box-Jenkins process is proposed. And a new method for safety inventory determination is proposed to reduce the penalty cost by forecasting errors. Finally, using the two proposed methods, the web-based automatic module has been developed.

• Wind and Structures
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• v.16 no.4
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• pp.323-340
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• 2013

An active mass damper system for flutter control of bridges is presented. Flutter stability of bridge structures is improved with the help of eccentric rotational actuators (ERA). By using a bridge girder model that moves in two degrees of freedom and is subjected to wind, the equations of motion of the controlled structure equipped with ERA are established. In order to take structural nonlinearities into consideration, flutter analysis is carried out by numerical simulation scheme based on a 4th-order Runge-Kutta algorithm. An example demonstrates the performance and efficiency of the proposed device. In comparison with known active mass dampers for flutter control, the movable eccentric mass damper and the rotational mass damper, the power demand is significantly reduced. This is of advantage for an implementation of the proposed device in real bridge girders. A preliminary design of a realization of ERA in a bridge girder is presented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1477-1485
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• 2018

There are two major issues for activated sludge process in sewage treatment plant. One is how to make sewage be more clean and the other is the energy saving in sewage treatment process. The major monitoring sewage qualities are chemical oxygen demand, phosphorus, nitrogen, suspended solid in effluent. These are transmitted to the national TMS(Telemetry Monitoring System) at every hour. If these exceed the environmental standard, the environmental charges imposed. So, these water qualities are to be controlled below the environmental standard in operation of sewage treatment plant. And recently, the energy saving is also important in process operation. Over 50% energy is consumed in blowers and motors for injection oxygen into aeration tank. So, with the water qualities to be controlled below the environmental standard, the energy saving also is to be accomplished for efficient plant management. Almost researches are aimed to control water quality without considering energy saving. AI techniques have been used for control water quality. AI modeling simulator provided the optimal control inputs(blower speed, waste sludge, return sludge) for control water quality. Blower speed is the main control input for activated sludge process. To make sewage be more clean, the excessive blower speed is supplied, but water quality is not better than the previous. In results, non necessary energy is consumed. In this paper we propose a new method that the energy saving also is to be accomplished with the water qualities to be controlled below the environmental standard for efficient plant management. Water qualities in only aeration tank are used the inputs of fuzzy models. Outputs of these models are chemical oxygen demand, phosphorus, nitrogen, suspended solid in effluent and have the environmental standards. In test, we found this method could save 10% energy than the previous methods.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.12
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• pp.154-161
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• 2009

A fuel cell power plant is a very complex system which has various control loops with some non-linearity. For control of a fuel cell power plant, dynamic models of fuel cell stacks have been developed and simplified process flow diagrams of a fuel cell power plant has been presented. Using such a model of a Molten Carbonate Fuel Cell (MCFC) power plant, this paper deals with development of an intelligent setpoint reference governor (I-SRG) to find the optimal setpoints and feed forward control inputs for the plant power demand. The I-SRG is implemented with neural network by using Particle Swarm Optimization (PSO) algorithm based on system constraints and performance objectives. The feasibility of the I-SRG is shown through simulation of an MCFC power plant for tracking control of its power demand.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.1
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• pp.32-41
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• 2008

This paper studies a joint EOQ and EPQ model in which a stationary demand can be satisfied by recycled products as well as newly purchased products. The model assumes that a fixed quantity of the used products are collected from customers and later recovered for reuse. The recovered products are regarded as perfectly new ones. We also assume that the number of orders for newly purchasing items and the number of recovery setups in a cycle can be mutually independent integers. Under these assumptions, we develop an optimization model obtaining the economic order quantity for newly procured products, the optimal lot size for the recovery process, and the sequence of the orders and the setups, simultaneously. And then a simple solution procedure to find a local optimal control parameter set is proposed. To validate the model and the solution procedure, finally, some computational experiments are presented.

• IE interfaces
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• v.18 no.1
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• pp.22-34
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• 2005

This paper introduces a simulation model which is based on the process analysis of a semiconductor company. The objective of the simulation modelis not only to estimate the overall performancesof the company but also to evaluate the performances of various operation rules for shop floor control. First, in order to develop the simulation model, a time study is performed for each process after analyzing the processes for the company. Second, by using ARENA, a simulation model is constructed based on the process analysis and the time study. After the simulation model is tested and run, its results are discussed.

• Environmental Engineering Research
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• v.19 no.1
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• pp.31-36
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• 2014

In this study, the influence of the control and operational parameters within a sewage treatment plant were reviewed by performing multiple regression analysis on the effluent quality of the sewage treatment. The data used for this review are based on the actual data from a sewage treatment plant using the media process within the year 2012. The prediction models of chemical oxygen demand ($COD_{Mn}$) and total nitrogen (T-N) within the effluent of the 2nd settling tank based on the multiple regression analysis yielded the prediction accuracy measurements of 0.93 and 0.84, respectively; and it was concluded that the model was accurately predicting the variances of the actual observed values. If the data on the energy spent on each operating condition can be collected, then the operating parameter that conserves energy without violating the effluent quality standards of COD and T-N can be determined using the regression model and the standardized regression coefficients. These results can provide appropriate operation guidelines to conserve energy to the operators at sewage treatment plants that consume a lot of energy.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.989-995
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• 2015

Due to the recent increase of the importance and demand of security services, the importance of a surveillance monitor system that makes an automatic security system possible is increasing. As the market for surveillance monitor systems is growing, price competitiveness is becoming important. As a result of this trend, surveillance monitor systems based on an embedded system are widely used. In this paper, an object detection algorithm based on an embedded system for a surveillance monitor system is introduced. To apply the object detection algorithm to the embedded system, the most important issue is the efficient use of resources, such as memory and processors. Therefore, designing an appropriate algorithm considering the limit of resources is required. The proposed algorithm uses two background models; therefore, the embedded system is designed to have two independent processors. One processor checks the sub-background models for if there are any changes with high update frequency, and another processor makes the main background model, which is used for object detection. In this way, a background model will be made with images that have no objects to detect and improve the object detection performance. The object detection algorithm utilizes one-dimensional histogram distribution, which makes the detection faster. The proposed object detection algorithm works fast and accurately even in a low-priced embedded system.