• Journal of Electrical Engineering and Technology
• /
• v.10 no.3
• /
• pp.895-904
• /
• 2015

This paper presents a probabilistic approach of reliability evaluation and economic assessment for solving transmission network expansion planning problems. Three methods are proposed for TNEP, which are reorganizing the existing power system focused on the buses of interest, selecting candidates using modified system operating state method with healthy, marginal and at-risk states, and finally choosing the optimal alternative using cost-optimization method. TNEP candidates can be selected based on the state reliability such as sufficient and insufficient indices, as proposed in this paper. The process of economic assessment involves the costs of construction, maintenance and operation, congestion, and outage. The case studies are carried out with modified IEEE-24 bus system and Jeju island power system expansion plan in Korea, to verify the proposed methodology.

• Journal of the Institute of Convergence Signal Processing
• /
• v.21 no.2
• /
• pp.55-60
• /
• 2020

In this paper, we propose a fast block matching algorithm of motion estimation using early detection of optimal candidate with high priority and a threshold. Even though so many fast algorithms for motion estimation have been published to reduce computational reduction full search algorithm, still so many works to improve performance of motion estimation are being reported. The proposed algorithm calculates block matching error for each candidate with high priority from previous partial matching error. The proposed algorithm can be applied additionally to most of conventional fast block matching algorithms for more speed up. By doing that, we can find the minimum error point early and get speed up by reducing unnecessary computations of impossible candidates. The proposed algorithm uses smaller computation than conventional fast full search algorithms with the same prediction quality as the full search algorithm. Experimental results shows that the proposed algorithm reduces 30~70% compared with the computation of the PDE and full search algorithms without any degradation of prediction quality and further reduces it with other fast lossy algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.567-571
• /
• 2008

In this paper, an overview on the ordering sphere decoder (SD) class for space-time codes (STC) will be presented. In SDs, the ordering techniques are considered as promising methods for reducing complexity by exploiting a sorted list of candidates, thus decreasing the number of tested points. First, we will present the current state of art of SD with their advantages and disadvantages. Then, the overview of simply geometrical approaches for ordering is presented to address the question to overcome the disadvantages. The computer simulation results shown that, thanks to the aid of ordering, the ordering SDs can achieve optimal bit-error-rate (BER) performance while requiring the very low complexity, which is comparable to that of linear sub-optimal decoders.

• Journal of Industrial Technology
• /
• v.28 no.B
• /
• pp.101-109
• /
• 2008

In general, non-stationary or chaos time series forecasting is very difficult since there exists a drift and/or nonlinearities in them. To overcome this situation, we suggest a new prediction method based on multiple model TS fuzzy predictors combined with preprocessing of time series data, where, instead of time series data, the differences of them are applied to predictors as input. In preprocessing procedure, the candidates of optimal difference interval are determined by using con-elation analysis and corresponding difference data are generated. And then, for each of them, TS fuzzy predictor is constructed by using k-means clustering algorithm and least squares method. Finally, the best predictor which minimizes the performance index is selected and it works on hereafter for prediction. Computer simulation is performed to show the effectiveness and usefulness of our method.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.12
• /
• pp.2109-2115
• /
• 2007

The wind generators have been installed with high output power to increase the energy production and efficiency. Hence, Optimal design of the direct-driven PM wind generator, coupled with F.E.M(Finite Element Method) and Genetic Algorithm(GA), has been performed to maximize the Annual Energy Production(AEP) over the whole wind speed characterized by the statistical model of wind speed distribution. Particularly, the parallel computing via internet web service has been applied to loose excessive computing times for optimization. The results of the optimal design of Surface-Mounted Permanent Magnet Synchronous Generator(SPMSG) are compared with each other candidates to verify the usefulness of the maximizing AEP model.

• Proceedings of the KSME Conference
• /
• 2003.11a
• /
• pp.1310-1315
• /
• 2003

In many practical engineering design problems, there are some design and manufacturing considerations that are difficult or infeasible to express in terms of an objective function or a constraint. In this situation, a set of optimal candidate designs having different topological complexities, not just a single optimal design, is preferred. To generate systematically such design candidates, we propose a hierarchical multiscale design resolution control scheme. In order to adjust its topological complexity by choosing a different starting resolution level in the hierarchical design space, we propose to employ a general M-band wavelet transform in transforming the original design space into the multiscale design space.

• Smart Structures and Systems
• /
• v.13 no.3
• /
• pp.389-406
• /
• 2014

Optimal sensor placement techniques play a significant role in enhancing the quality of modal data during the vibration based health monitoring of civil structures, where many degrees of freedom are available despite a limited number of sensors. The literature has shown a shift in the trends for solving such problems, from expansion or elimination approach to the employment of heuristic algorithms. Although these heuristic algorithms are capable of providing a global optimal solution, their greatest drawback is the requirement of high computational effort. Because a highly efficient optimisation method is crucial for better accuracy and wider use, this paper presents an improved simulated annealing (SA) algorithm to solve the sensor placement problem. The algorithm is developed based on the sensor locations' coordinate system to allow for the searching in additional dimensions and to increase SA's random search performance while minimising the computation efforts. The proposed method is tested on a numerical slab model that consists of two hundred sensor location candidates using three types of objective functions; the determinant of the Fisher information matrix (FIM), modal assurance criterion (MAC), and mean square error (MSE) of mode shapes. Detailed study on the effects of the sensor numbers and cooling factors on the performance of the algorithm are also investigated. The results indicate that the proposed method outperforms conventional SA and Genetic Algorithm (GA) in the search for optimal sensor placement.

• Smart Structures and Systems
• /
• v.26 no.6
• /
• pp.721-733
• /
• 2020

The present study investigates the employing of piezoelectric patches in active control of a sandwich plate. Indeed, the active control and optimal patch distribution on this structure are presented together. A sandwich plate with honeycomb core and composite reinforced by carbon nanotubes in facesheet layers is considered so that the optimum position of actuator/sensor patches pair is guaranteed to suppress the vibration of sandwich structures. The sandwich panel consists of a search space which is a square of 200 × 200 mm with a numerous number of candidates for the optimum position. Also, different dimension of square and rectangular plates to obtain the optimal placement of piezoelectric actuator/senor patches pair is considered. Based on genetic algorithm and LQR, the optimum position of patches and fitness function is determined, respectively. The present study reveals that the efficiency and performance of LQR control is affected by the optimal placement of the actuator/sensor patches pair to a large extent. It is also shown that an intelligent selection of the parent, repeated genes filtering, and 80% crossover and 20% mutation would increase the convergence of the algorithm. It is noted that a fitness function is achieved by collection actuator/sensor patches pair cost functions in the same position (controllability). It is worth mentioning that the study of the optimal location of actuator/sensor patches pair is carried out for different boundary conditions of a sandwich plate such as simply supported and clamped boundary conditions.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.26 no.3
• /
• pp.205-213
• /
• 2023

An optimal design of a simple beam-shaped flexure hinge mount supporting an optical mirror is presented. An optical mirror assembly is an opto-mechanically coupled system as the optical and mechanical behaviors interact. This side-supporting mount is flexible in the radial direction and rigid for the remaining degrees of freedom to support the mirror without transferring thermal load. Through thermo-elastic, optical and eigenvalue analysis, opto-mechanical performance was predicted to establish the objective functions for optimization. The key design parameters for this flexure are the thickness and length. To find the optimal values of design parameters, response surface analysis was performed using the design of experiment based on nested FCD. Optimal design candidates were derived from the response surface analysis, and the optimal design shape was confirmed through Opto-mechanical performance validation analysis.

• Nuclear Engineering and Technology
• /
• v.52 no.8
• /
• pp.1817-1825
• /
• 2020

Background: Cosmic ray-induced particles can lead to failure of semiconductors packaged for export during air transport. This work performed MCNP 6.2 simulations to optimize shielding against neutrons and protons induced by cosmic radiation Methods and materials: The energy spectra of protons and neutrons by incident angle at the flight altitude were determined using atmospheric cuboid model. Various candidates for the shielding materials and the geometry of the Unit Load Device Container were evaluated to determine the conditions that allow optimal shielding at all sides of the container. Results: It was found that neutrons and protons, at the flight altitude, generally travel with a downward trajectory especially for the particles with high energy. This indicated that the largest number of particles struck the top of the container. Furthermore, the simulation results showed that, among the materials tested, borated polyethylene and stainless steel were the most optimal shielding materials. The optimal shielding structure was also determined with the weight limit of the container in consideration. Conclusions: Under the determined optimal shielding conditions, a significantly reduced number of neutrons and protons reach the contents inside the container, which ultimately reduces the possibility of semiconductor failure during air transport.