• Nuclear Engineering and Technology
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• v.49 no.1
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• pp.43-53
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• 2017

Increasing the operation cycle length can be an important goal in the fuel reload design of a nuclear reactor core. In this research paper, a new optimization approach, electromagnetism mechanism (EM), is applied to the fuel arrangement design of the Bushehr WWER-1000 core. For this purpose, a neutronic solver has been developed for calculating the required parameters during the reload cycle of the reactor. In this package, two modules have been linked, including PARCS v2.7 and WIMS-5B codes, integrated in a solver for using in the fuel arrangement optimization operation. The first results of the prepared package, along with the cycle for the original pattern of Bushehr WWER-1000, are compared and verified according to the Final Safety Analysis Report and then the results of exploited EM linked with Purdue Advanced Reactor Core Simulator (PARCS) and Winfrith Improved Multigroup Scheme (WIMS) codes are reported for the loading pattern optimization. Totally, the numerical results of our loading pattern optimization indicate the power of the EM for this problem and also show the effective improvement of desired parameters for the gained semi-optimized core pattern in comparison to the designer scheme.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2253-2261
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• 1999

ACK generates optimized code using the string pattern matching technique in pattern table generator and peephole optimizer. But string pattern matching method is not effective due to the many comparative actions in pattern selection. We designed and implemented the EM intermediate code optimizer using tree pattern matching algorithm composed of EM tree generator, optimization pattern table generator and tree pattern matcher. Tree pattern matching algorithm practices the pattern matching that centering around root node with refer to the pattern table, with traversing the EM tree by top-down method. As a result, compare to ACK string pattern matching methods, we found that the optimized code effected to pattern selection time, and contributed to improved the pattern selection time by about 10.8%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.8
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• pp.793-798
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• 2009

In this paper, the simulation and optimization of SRH (Surface Relief Hologram) masks for printing LCD gate patterns using TIR (Total Internal Reflection) holographic lithography was investigated. A simulation and optimization algorithm based on SDTA (Scalar Diffraction Theory Analysis) method was developed. The accuracy of the algorithm was compared to that of the RCWA (Rigorous Coupled Wave Analysis) method for estimating the Fresnel diffraction pattern of Cr amplitude masks for the given system geometry. In addition, the results from the optimization algorithm were validated experimentally. It was found that one to the most important conditions for the fabrication of SRH masks is to avoid nonlinear shape distortions of the resulting grating. These distortions can be avoided by designing SRH masks with recorded gratings having small aspect ratios of width versus depth. The optimum gap size between the Cr and SRH masks was found using the optimization algorithm. A printed LCD gate pattern with a minimum line width of $1.5{\mu}m$ exposed using the optimized SRH mask was experimentally demonstrated.

• Geomechanics and Engineering
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• v.12 no.2
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• pp.197-210
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• 2017

This paper focuses on the regularization of structural configurations by employing meta-heuristic optimization algorithms such as Particle Swarm Optimization (PSO) and Biogeography-Based Optimization (BBO). The regularization of structural configuration means obtaining a structure whose members have equal or almost equal lengths, or whose member's lengths are based on a specific pattern; which in this case, by changing the length of these elements and reducing the number of different profiles of needed members, the construction of the considered structure can be made easier. In this article, two different objective functions have been used to minimize the difference between member lengths with a specific pattern. It is found that by using a small number of iterations in these optimization methods, a structure made of equal-length members can be obtained.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.4
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• pp.107-113
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• 2022

At present, it is possible to manufacture electrodes down to several micrometers (~ ㎛) using inkjet printing technology owing to the development of precision ejection heads. Inkjet printing technology is also used in the manufacturing of bio-sensors, electronic sensors, and flexible displays. To reduce the difference between the electrode design/simulation performance and actual printing pattern performance, it is necessary to analyze and optimize the processable area of the ink material, which is a fluid. In this study, process optimization was conducted to manufacture an IDE pattern and fabricate an impedance sensor. A total of 25 IDE patterns were produced, with five for each lamination process. Electrode line width and height changes were measured by stacking the designed IDE pattern with a nanoparticle-based conductive ink multilayer. Furthermore, the optimal process area for securing a performance close to the design result was analyzed through impedance and capacitance. It was observed that the increase in the height of stack layer 4 was the lowest at 4.106%, and the increase in capacitance was measured to be the highest at 44.08%. The proposed stacking process pattern, which is optimized in terms of uniformity, reproducibility, and performance, can be efficiently applied to bio-applications such as biomaterial sensing with an impedance sensor.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.5
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• pp.458-464
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• 2016

This paper proposes the compensation method which decreases the radiation pattern distortion caused by the mutual coupling in an array antenna. If the element distance of an array antenna decreases, the radiation pattern could be distorted by the strong mutual coupling, which changes the magnitude and phase of input signals and causes an unwanted radiation pattern. To remove the pattern distortion, compensated input signals are inserted in an array antenna. The magnitude and phase of input signals are determined by Particle Swarm Optimization (PSO) algorithm. A $4{\times}1$ dipole array antenna with omnidirectional elements is used to confirm the validity of the algorithm, where each element is placed in 0.2 wavelength to evoke the strong coupling. After input signals are optimized by PSO, it is found that the compensated radiation results in the same as the ideal case.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.779-787
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• 2010

In this paper, We introduce electrical tracking generated from surface activity associated with flow of leakage current on insulator under wet and contaminated conditions and design electrical tracking pattern recognition system by using LabVIEW. We measure the leaking current of contaminated wire by using LabVIEW software and the NI-c-DAQ 9172 and NI-9239 hardware. As pattern recognition algorithm and optimization algorithm for electrical tracking system, neural networks, Radial Basis Function Neural Networks(RBFNNs) and particle swarm optimization are exploited. The designed electrical tracking recognition system consists of two parts such as the hardware part of electrical tracking generator, the NI-c-DAQ 9172 and NI-9239 hardware and the software part of LabVIEW block diagram, LabVIEW front panel and pattern recognition-related application software. The electrical tracking system decides whether electrical tracking generate or not on electrical wire.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2367-2370
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• 2003

A fast pattern classification algorithm with Cellular Parallel Processing Network-based dynamic programming is proposed. The Cellular Parallel Processing Networks is an analog parallel processing architecture and the dynamic programming is an efficient computation algorithm for optimization problem. Combining merits of these two technologies, fast Pattern classification with optimization is formed. On such CPPN-based dynamic programming, if exemplars and test patterns are presented as the goals and the start positions, respectively, the optimal paths from test patterns to their closest exemplars are found. Such paths are utilized as aggregating keys for the classification. The pattern classification is performed well regardless of degree of the nonlinearity in class borders.

• Journal of Korean Association for Spatial Structures
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• v.1 no.1 s.1
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• pp.157-166
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• 2001

In general, the cutting pattern of the membrane structures is determined by dividing the complicated curved 3-D surface into several 2-D plane strip by using flattening technique. In this procedure, however, some discrepancies ore occurred between actual stresses of equilibrated state and designed uniform stresses because the material properties are not considered. These deviations can cause the critical structural problems, wrinkling or overstress, and thus a optimization process should be considered. In this paper, a new analytical method for determining an optimum cutting pattern considering material properties is presented. Here, iterative procedure is introduced to decrease the errors caused in numerical process. The optimization method proposed can diminish the deviations occurred by material properties and numerical errors, simultaneously. As a results, it is shown that the final stress distributions for the HP shell model are sufficiently near to design stress distributions, and it can be concluded that this method can be used to obtain the optimized cutting pattern of membrane structures.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.9
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• pp.540-546
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• 2003

A fast pattern classification algorithm with Cellular Nonlinear Network-based dynamic programming is proposed. The Cellular Nonlinear Networks is an analog parallel processing architecture and the dynamic programing is an efficient computation algorithm for optimization problem. Combining merits of these two technologies, fast pattern classification with optimization is formed. On such CNN-based dynamic programming, if exemplars and test patterns are presented as the goals and the start positions, respectively, the optimal paths from test patterns to their closest exemplars are found. Such paths are utilized as aggregating keys for the classification. The algorithm is similar to the conventional neural network-based method in the use of the exemplar patterns but quite different in the use of the most likely path finding of the dynamic programming. The pattern classification is performed well regardless of degree of the nonlinearity in class borders.