In this study, a long-term unsteady simulation model has been developed using rigid water column theory which is more accurate than Extended-period model and more efficient comparing with water-hammer simulation model. The developed model is applied to 24-hours unsteady simulation considering daily water-demand and water-hammer analysis caused by closing a valve. For the case of 24-hours daily simulation, the pressure of each node decreases as the water demand increase, and when the water demand decrease, the pressure increases. During the simulation, the amplitudes of flow and pressure variation are different in each node and the pattern of flow variation as well as water demand is quite different than that of KYPIPE2. Such discrepancy necessitates the development of unsteady flow analysis model in water distribution network system. When the model is applied to water-hammer analysis, the pressure and flow variation occurred simultaneously through the entire network system by neglecting the compressibility of water. Although water-hammer model shows the lag of travel time due to fluid elasticity, in the aspect of pressure and flow fluctuation, the trend of overall variation and quantity of the result are similar to that of water-hammer model. This model is expected for the analysis of gradual long-term unsteady flow variations providing computational accuracy and efficiency as well as identifying pollutant dispersion, pressure control, leakage reduction corresponding to flow-demand pattern, and management of long-term pipeline net work systems related with flowrate and pressure variation in pipeline network systems
Park, Gwang-Je;Lee, Ju-Hee;Kim, Hyung-Seok;Jeong, Sun-Beom;Oh, Taeg-Yun;Bae, Jae-Hyun
Journal of the Korean Society of Fisheries and Ocean Technology
/
v.42
no.3
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pp.134-147
/
2006
A model experiment using circulation water channel was carried out to investigate the dynamic characteristics of bottom trawl net which can be used in sea mount of North Pacific. Hydrodynamic resistance and shape variation according to the flow velocity and angle of hand rope transformation for net were measured, and experimental value was analyzed as the value of full-scale bottom trawl net. The results summarized are as follows; At the $30^{\circ}$ of angle of hand rope to net, hydrodynamic resistance varied from 0.5kgf to 2.68kgf as the flow velocity increased between 0.31m/s and 0.92m/s, and formula of hydrodynamic resistance for the model net was $F_m=3.04\;{\cdot}\;{\upsilon}^{1.53}$. At the fixed angle of hand rope, Net height was low and Net width was high according to the increase of flow velocity, and in addition, vertical opening was low and Net width was high by the increase of angle of hand rope at the fixed flow velocity. At the $30^{\circ}$ of angle of hand rope to net, net opening area was $0.214m^2$ as flow velocity was 0.61m/s, and formula of net opening area for the model net was $S_m=-0.22{\upsilon}+0.35$. At the $30^{\circ}$ of angle of hand rope to net, catch efficiency seemed to be highest as $0.319m^3/s$ of filtering volume at the 0.76m/s(51kt's) of flow velocity. Shape variation of net showed the gradual laminar transform for the variation of flow velocity but there needed some improvements due to the occurrence of shortening at the ahead of wing net.
The Transactions of The Korean Institute of Electrical Engineers
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v.67
no.11
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pp.1423-1433
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2018
Recently, a permanent magnet synchronous motor of middle and small-capacity has high torque, high precision control and acceleration / deceleration characteristics. But existing control has several problems that include unpredictable disturbances and parameter changes in the high accuracy and rigidity control industry or nonlinear dynamic characteristics not considered in the driving part. In addition, in the drive method for the control of low-vibration and high-precision, the process of connecting the permanent magnet synchronous motor and the load may cause the response characteristic of the system to become very unstable, to cause vibration, and to overload the system. In order to solve these problems, various studies such as adaptive control, optimal control, robust control and artificial neural network have been actively conducted. In this paper, an incremental encoder of the permanent magnet synchronous motor is used to detect the position of the rotor. And the position of the detected rotor is used for low vibration and high precision position control. As the controller, we propose augmented state feedback control with a speed observer and first order deadbeat disturbance observer. The augmented state feedback controller performs control that the position of the rotor reaches the reference position quickly and precisely. The addition of the speed observer to this augmented state feedback controller compensates for the drop in speed response characteristics by using the previously calculated speed value for the control. The first order deadbeat disturbance observer performs control to reduce the vibration of the motor by compensating for the vibrating component or disturbance that the mechanism has. Since the deadbeat disturbance observer has a characteristic of being vulnerable to noise, it is supplemented by moving average filter method to reduce the influence of the noise. Thus, the new controller with the first order deadbeat disturbance observer can perform more robustness and precise the position control for the influence of large inertial load and natural frequency. The simulation stability and efficiency has been obtained through C language and Matlab Simulink. In addition, the experiment of actual 2.5[kW] permanent magnet synchronous motor was verified.
This paper proposes a novel approach to model updating for a large-scale cable-stayed bridge based on ambient vibration tests coupled with a hybrid metaheuristic search algorithm. Vibration measurements are carried out under excitation sources of passing vehicles and wind. Based on the measured structural dynamic characteristics, a finite element (FE) model is updated. For long-span bridges, ambient vibration test (AVT) is the most effective vibration testing technique because ambient excitation is freely available, whereas a forced vibration test (FVT) requires considerable efforts to install actuators such as shakers to produce measurable responses. Particle swarm optimization (PSO) is a famous metaheuristic algorithm applied successfully in numerous fields over the last decades. However, PSO has big drawbacks that may decrease its efficiency in tackling the optimization problems. A possible drawback of PSO is premature convergence leading to low convergence level, particularly in complicated multi-peak search issues. On the other hand, PSO not only depends crucially on the quality of initial populations, but also it is impossible to improve the quality of new generations. If the positions of initial particles are far from the global best, it may be difficult to seek the best solution. To overcome the drawbacks of PSO, we propose a hybrid algorithm combining GA with an improved PSO (HGAIPSO). Two striking characteristics of HGAIPSO are briefly described as follows: (1) because of possessing crossover and mutation operators, GA is applied to generate the initial elite populations and (2) those populations are then employed to seek the best solution based on the global search capacity of IPSO that can tackle the problem of premature convergence of PSO. The results show that HGAIPSO not only identifies uncertain parameters of the considered bridge accurately, but also outperforms than PSO, improved PSO (IPSO), and a combination of GA and PSO (HGAPSO) in terms of convergence level and accuracy.
Journal of the Korea Academia-Industrial cooperation Society
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v.18
no.1
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pp.688-695
/
2017
This paper deals with characteristics analysis of a permanent magnet (PM) linear generator using analytical methods for wave energy harvesting. The wave energy is carried out from the movement of a yo-yo system. A linear generator using permanent magnets to generate a magnetic force itself does not require a separate power supply and has the advantage of simple maintenance. In addition to the use of a rare earth, a permanent magnet having a high-energy density can be miniaturized and lightweight, and can obtain high energy-conversion efficiency. We derived magnetic field solutions produced by the permanent magnet and armature reaction based on 2D polar coordinates and magnetic vector potential. Induced voltage is obtained via arbitrary sinusoidal input. In addition, electrical parameters are obtained, such as back-EMF constant, resistance, and self- and mutual-winding inductances. The space harmonic method used in this paper is confirmed by comparing it with finite element method (FEM) results. These facilitate the characterization of the PM-type linear generator and provide a basis for comparative studies, design optimization, and machine dynamic modeling.
An important issue in multiagent reinforcement learning is how an agent should team its optimal policy through trial-and-error interactions in a dynamic environment where there exist other agents able to influence its own performance. Most previous works for multiagent reinforcement teaming tend to apply single-agent reinforcement learning techniques without any extensions or are based upon some unrealistic assumptions even though they build and use explicit models of other agents. In this paper, basic concepts that constitute the common foundation of multiagent reinforcement learning techniques are first formulated, and then, based on these concepts, previous works are compared in terms of characteristics and limitations. After that, a policy model of the opponent agent and a new multiagent reinforcement learning method using this model are introduced. Unlike previous works, the proposed multiagent reinforcement learning method utilize a policy model instead of the Q function model of the opponent agent. Moreover, this learning method can improve learning efficiency by using a simpler one than other richer but time-consuming policy models such as Finite State Machines(FSM) and Markov chains. In this paper. the Cat and Mouse game is introduced as an adversarial multiagent environment. And effectiveness of the proposed multiagent reinforcement learning method is analyzed through experiments using this game as testbed.
We need various methods to develop MMORPG that is game genre which many users use among various game genre using Internet. Specially, to heighten efficiency of distributing work, Object-oriented language such as C++ is used and we need design techniques that can take advantage of enough object-oriented concept when making large-scale game. There is various pattern that can apply in software breakup design in GoF's design pattern for these design techniques. If you apply Observer pattern to Party System Design for forming community between game users, you can easily add new class and maintain system later. Party Play is one of the important system that is used to form game users' community in MMORPG games. The main point that must be considered in Party-Play-System is to divide evenly experience value and acquisition that is got by Party-Play among users according to each user's level. To implement Party Play System that consider maintenance of system, in this paper, we propose a method using GoF's Observer-Pattern, showing you that proposed method which has advantage to dynamic memory allocation and to virtual method call can be used usefully to change object to real time at program run and to add new class and to maintain system new.
Service-Oriented Computing (SOC) is a reuse paradigm for developing business processes by dynamic service composition. Service consumers subscribe services deployed by service providers only through service interfaces. Therefore, services on server-side are perceived as black box to service consumers. Due to this nature of services, service consumers have limited knowledge on the quality of services. This limits utilizing of services in critical domains hard. Therefore, there is an increasing demand for effective methods for monitoring services. Current monitoring techniques generally depend on specific vendor's middleware without direct access to services due to the technical hardship of monitoring. However, these approaches have limitations including low data comprehensibility and data accuracy. And, this results in a demand for effective service monitoring framework. In this paper, we propose a framework for efficiently monitoring services. We first define requirements for designing monitoring framework. Based on the requirements, we propose architecture for monitoring framework and define generic patterns for efficiently acquiring monitored data from services. We present the detailed design of monitoring framework and its implementation. We finally implement a prototype of the monitor, and present the functionality of the framework as well as the results of experiments to verify efficiency of patterns for transmitting monitoring data.
Park, Ji-Hoon;Won, Hyun-Kyu;Kim, Young-Hwan;Kim, Man-Pil
Journal of the Korea Society of Computer and Information
/
v.15
no.10
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pp.229-237
/
2010
Recently, forest management objectives become more complex and complicated, and spatial constraints were necessarily considered for ecological stability. Now forest planning is required to provide an optimized solution that is able to achieve a number of management objectives and constraints. In this study, we developed a decision supporting system based on the one of dynamic planning techniques, Tabu Search (TS) heuristic algorithm, which enable one to generate an optimized solution for given objectives and constraints. For this purpose, we analyzed the logical flow of the algorithm and designed the subsequence of processes. To develop a high-performance computing system, we examined a number of strategy to minimize execution time and workloads in each process and to maximize efficiency of using system resources. We examined two model based on the original TS algorithm and revised version of TS algorithm and compared their performance in optimization process. The results showed high performance of the developed system in providing feasible solutions for several management objectives and constraints. Moreover, the revised version of TS algorithm was appeared to be more stable for providing results with minimum variation. The developed system is expected to use for developing forest management plans in Korea.
Despite the growing numbers of regional problems (e.g. conflicts between the state and localities, inter-local conflicts, etc.) associated with the state-led developmental projects, the Korean social sciences have been unable to offer satisfying explanations and solutions to the regional problems. This is mainly because the existing works, which have been taken captured by the assumptions of "methodological nationalism", significantly lack the socio-spatial understandings of the state actions and the relations between the state and localities, thereby seeing the issues of regional development mainly in terms of either the economic efficiency defined at the national scale, or the plan rationality of the national bureaucrats. With this problem orientation in mind, this paper aims to explore the ways in which the state and localities are interacting, conflicting and negotiating with one another through the mediation of the state-led developmental projects. Focusing on the developmental processes of Masan Export Processing Zone from the mid-1960s to the early 1970s, it examines the multi-scalar processes through which the state-led industrial complex developmental processes have been influenced by the complex and dynamic interactions among social forces and actors acting at diverse geographical scales (e.g. the global, national, local, urban, etc.). This analysis shows that the regional policies of the Korean developmental state were more heavily influenced by the interactions, contestations, and collaborations among social forces and actors, acting in and through the state, at various geographical scales, rather than by the economic and techno-bureaucratic rationality.
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