• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.396-401
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• 2002

The purpose of this 3-D numerical simulation is evaluate the application of a commercial CFD code to predict 3-D flow characteristics of wind turbine. The experimental approach, which has been main method of investigation, appears to be its limits, the cost increasing disproportionally with the size of the wind turbines, and is hence mostly limited to observing the phenomena. Hence, the use of Computational Fluid Dynamics (CFD) techniques and Wavier-Stokes solvers are considered a very serious contender. The flow solver CFX-TASCflow is employed in all computations presented in this paper. The 3-D flow separation and the wake distribution of 2 bladed Horizontal Axis Wind Turbines (HAWTs) are compared to Heuristic model and visualized result by NREL(National Renewable Energy Laboratory). Simulated 3-D flow separation structure on the rotor blade is very similar to Heuristic model and the wake structure of the wind turbine is good agree with visualized results.

• New & Renewable Energy
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• v.16 no.1
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• pp.15-24
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• 2020

For mechanical load testing of wind turbines, capture matrix is constructed for various range of wind speeds according to the international standard IEC 61400-13. The conventional method wastes considerable amount of data by its invalid data policy -segment data into 10 minutes then remove invalid ones. Previously, we have suggested an alternative way to save the total amount of data to build a capture matrix, but the efficient selection of data has been still under question. The paper introduces optimization algorithms to construct capture matrix with less data. Heuristic algorithm (simple stacking and lowest frequency first), population method (particle swarm optimization) and Q-Learning accompanied with epsilon-greedy exploration are compared. All algorithms show better performance than the conventional way, where the distribution of enhancement was quite diverse. Among the algorithms, the best performance was achieved by heuristic method (lowest frequency first), and similarly by particle swarm optimization: Approximately 28% of data reduction in average and more than 40% in maximum. On the other hand, unexpectedly, the worst performance was achieved by Q-Learning, which was a promising candidate at the beginning. This study is helpful for not only wind turbine evaluation particularly the viewpoint of cost, but also understanding nature of wind speed data.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.52-59
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• 2008

This paper describes the secant method for solving the economic dispatch (ED) problem with generator constraints and transmission losses. The ED problem is an important optimization problem in the economic operation of a power system. The proposed algorithm involves selection of minimum and maximum incremental costs (lambda values) and then the evaluation of optimal lambda at required power demand is done by secant method. The proposed algorithm has been tested on a power system having 6, 15, and 40 generating units. Studies have been made on the proposed method to solve the ED problem by taking 120 and 200 units with generator constraints. Simulation results of the proposed approach were compared in terms of solution quality, convergence characteristics, and computation efficiency with conventional methods such as lambda iterative method, heuristic methods such as genetic algorithm, and meta-heuristic methods like particle swarm optimization. It is observed from different case studies that the proposed method provides qualitative solutions with less computational time compared to various methods available in the literature.

• Korean Management Science Review
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• v.27 no.3
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• pp.15-31
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• 2010

We consider a reverse logistics network design problem for recycling. The problem consists of three stages of transportation. In the first stage products are transported from retrieval centers to disassembly centers. In the second stage disassembled modules are transported from disassembly centers to processing centers. Finally, in the third stage modules are transported from either processing centers or a supplier to a manufacturer, a recycling site, or a disposal site. The objective is to design a network which minimizes the total transportation cost. We design a cooperative coevolutionary algorithm to solve the problem. First, the problem is decomposed into three subproblems each of which corresponds to a stage of transportation. For subproblems 1 and 2, a population of chromosomes is constructed. Each chromosome in the population is coded as a permutation of integers and an algorithm which decodes a chromosome is suggested. For subproblem 3, an heuristic algorithm is utilized. Then, a performance evaluation procedure is suggested which combines the chromosomes from each of two populations and the heuristic algorithm for subproblem 3. An experiment was carried out using test problems. The experiments showed that the cooperative coevolutionary algorithm generally tends to show better performances than the previous genetic algorithm as the problem size gets larger.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.2192-2197
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• 2003

The purpose of this 3-D numerical simulation is evaluate the application of a commercial CFD code to predict 3-D flow and power characteristics of wind turbines. The experimental approach, which has been main method of investigation, appears to be its limits, the cost increasing with the size of the wind turbines, hence mostly limited to observing the phenomena on rotor blades. Therefore, the use of Computational Fluid Dynamics (CFD) techniques and Navier-Stokes solvers are considered a very serious contender. The flow solver CFX-TASCflow is employed in all computations in this paper. The 3-D flow separation and the wake distribution of 2 and 3 bladed Horizontal Axis Wind Turbines (HAWTs) are compared to Heuristic model and smoke-visualized experimental result by NREL(National Renewable Energy Laboratory). Simulated 3-D flow separation structure on the rotor blade is very similar to Heuristic model and the wake structure of the wind turbine is good consistent with smoke-visualized result. The calculated power of the 3 bladed rotor by CFD is compared with BEM results by TV-Delft. The CFD results of which is somewhat consist with BEM results, under an error less than 10%.

• Journal of Ocean Engineering and Technology
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• v.18 no.4 s.59
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• pp.65-70
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• 2004

Many port states, such as New Zealand, U.S.A., Australia, and Canada, have strict regulations to prevent arriving ships from discharging polluted ballast water that contains harmful aquatic organisms and pathogens. They are notified that transfer of polluted ballast water can cause serious injury to public health and damage to property and environment. For this reason, ballast exchange in deep sea is perceived as the most effective method of emptying ballast water. The ballast management plan contains the effective exchange method, ballast system, and safety considerations. In this study, we pursued both nautical engineering analysis and optimization of the algorithm, in order to generate the sequence of stability and rapidity. A heuristic algorithm was chosen on the basis of optimality and applicability to a sequential exchange problem. We have built an optimized algorithm for the automatic exchange of ballast water, by redefining core elements of the A$\ast$ algorithm, such as node, operator, and evaluation function. The final version of the optimized algorithm has been applied to existing bulk carrier, and the performance of the algorithm has been successfully verified.

• The Journal of Korean Association of Computer Education
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• v.5 no.3
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• pp.37-44
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• 2002

Automatic text classification is a task of assigning predefined categories to free text documents. Its importance is increased to organize and manage a huge amount of text data. There have been some researches on automatic text classification based on machine learning techniques. While most of them was focused on proposal of a new machine learning methods and cross evaluation between other systems, a through evaluation or optimization of a method has been rarely been done. In this paper, we propose an improving method of kNN-based Korean text classification system using heuristic informations about decision function, the number of nearest neighbor, and feature selection method. Experimental results showed that the system with similarity-weighted decision function, global method in considering neighbors, and DF/ICF feature selection was more accurate than simple kNN-based classifier. Also, we found out that the performance of the local method with well chosen k value was as high as that of the global method with much computational costs.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1550-1556
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• 1997

In this paper, we apply the evolutionary algorithm to the combinatorial optimization problem. Evolutionary algorithm useful for the optimization of the large space problem. This paper propose a method for the reuse of wastes of light water in atomic reactor system. These wastes contain several reusable elements, and they should be carefully selected and blended to satisfy requirements as an input material to the heavy water atomic reactor system. This problem belongs to an NP-hard like the 0/1 knapsack problem. Two evolutionary strategies are used as approximation algorithms in the highly constrained combinatorial optimization problem. One is the traditional strategy, using random operator with evaluation function, and the other is heuristic based search that uses the vector operator reducing between goal and current status. We also show the method which perform the feasible test and solution evaluation by using the vectored knowledge in problem domain. Finally, We compare the simulation results of using random operator and vector operator for such combinatorial optimization problems.

• The Journal of Korean Institute for Practical Engineering Education
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• v.3 no.1
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• pp.62-68
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• 2011

Usability heuristics("heuristics") are general principles for usability evaluation during user interface design. This method is commonly used by Human Computer Interaction(HCI) professionals; however, the most widely used set of heuristics which were originally created by Nielsen has not yet been found practical in the current state of Korean technologies. In our prior research, we found that some of Nielsen's heuristics are difficult for some evaluators to understand and insufficient to fully evaluate Korean applications, due to the broad-applicability of these heuristics and differences in cultural context. Therefore, in this study, professionals in computer science and related fields evaluated Nielsen's ten usability heuristics in order to gather logical bases for finding areas for improvement. The results of this study will help creating a new set of heuristics that will better valuate more recently developed applications.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1317-1322
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• 2018

In order to complete the AR UI design simply and quickly, the usable factors were studied in this thesis. The primary aim of interface design is to increase the usability. The various factors should be considered together when we evaluate the usability. The idealized usable working model is based on user-centered with the aim of perceiving the interests of users, operating easily and completing targets. In order to ensure the types of usable factors, literature survey method had been used and a total of 85 usable factors had been collected by this survey. To make the usable factors can adapt the augmented reality, the concept of factors should be redefined. We extract the items which is adaptable and user-centered, combine or delete the items that have the same meanings and finally select 25 usable evaluative factors. Then we take HCI professional as the object and collect the data by Heuristic Evaluation. We systematize the usable factors by Principal Component Analysis, and observe the correlation between the usable factors and classify those which have high correlation.