• Nuclear Engineering and Technology
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• v.50 no.1
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• pp.54-67
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• 2018

There have been recent efforts to establish methods for high-fidelity and multi-physics simulation with coupled thermal-hydraulic (T/H) and neutronics codes for the entire core of a light water reactor under accident conditions. Considering the computing power necessary for a pin-by-pin analysis of the entire core, subchannel-scale T/H analysis is considered appropriate to achieve acceptable accuracy in an optimal computational time. In the present study, the applicability of in-house code CUPID of the Korea Atomic Energy Research Institute was extended to the subchannel-scale T/H analysis. CUPID is a component-scale T/H analysis code, which uses three-dimensional two-fluid models with various closure models and incorporates a highly parallelized numerical solver. In this study, key models required for a subchannel-scale T/H analysis were implemented in CUPID. Afterward, the code was validated against four subchannel experiments under unheated and heated single-phase incompressible flow conditions. Thereafter, a subchannel-scale T/H analysis of the entire core for an Advanced Power Reactor 1400 reactor core was carried out. For the high-fidelity simulation, detailed geometrical features and individual rod power distributions were considered in this demonstration. In this study, CUPID shows its capability of reproducing key phenomena in a subchannel and dealing with the subchannel-scale whole core T/H analysis.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.89-97
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• 2008

In this paper, we present a method for the enhancement of marker detection correctness and marker recognition speed by using artificial neural network. Contours of objects are extracted from the input image. They are approximated to a list of line segments. Quadrangles are found with the geometrical features of the approximated line segments. They are normalized into exact squares by using the warping technique and scale transformation. Feature vectors are extracted from the square image by using principal component analysis. Artincial neural network is used to checks if the square image is a marker image or a non-marker image. After that, the type of marker is recognized by using an artificial neural network. Experimental results show that the proposed method enhances the correctness of the marker detection and recognition.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.115-119
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• 2018

Defining and measuring non-rigid or flexible parts has been controversial in industry for many years. There are two primary areas of controversy. The first is agreeing on what exactly a non-rigid part is. The second is agreeing on how to define and measure a non-rigid part. The subject of non-rigid parts is further complicated by the brief coverage it receives in the national and international standards. This leaves each company to improvise or create its own rules for non-rigid parts. There are some who believe that Geometrical Dimensioning and Tolerancing (GD&T) should not be used on non-rigid parts. This is not true. The ASME Y14.5M standard applies to rigid parts as a default condition. However, there is no definition given for a rigid part. The term rigid part has been used in industry for so long that it has gained a definition by its general use. When most people in industry say rigid part, they are referring to a part doesn't move (deform or flex) when a force (including gravity) is applied. How much force is relative based on the part characteristics. In reality, all parts will deform (or flex) if enough force is applied. Using this logic, all parts would be considered non-rigid. However, we all know that this is not how parts are treated in industry. Although GD&T defaults to rigid parts, it should also be used on non-rigid parts with a few special techniques. Actually 50~60% of all products designed contain parts or features on parts that are non-rigid. Therefore, we try to suggest the definitions of rigid and non-rigid parts and method to measure non-rigid parts.

• The KIPS Transactions:PartB
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• v.14B no.3 s.113
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• pp.191-198
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• 2007

In this paper, we present a marker detection and recognition method from camera image for a disabled person to interact with a server system which can control appliance of surrounding environment. It converts the camera image to a binary image by using multi-threshold and extracts contours of objects in the binary image. After that, it approximates the contours to a list of line segments. It finds rectangular markers by using geometrical features which are extracted from the approximated line segments. It normalizes the shape of extracted markers into exact squares by using the warping technique. It extracts feature vectors from marker image by using principal component analysis and then recognizes the marker. The proposed marker recognition system is robust for light change by using multi-threshold. Also, it is robust for angular variation of camera by using warping technique and principal component analysis. Experimental results show that the proposed method achieves 100% recognition rate at maximum for 21 markers and execution speed of 12 frames/sec.

• Corrosion Science and Technology
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• v.8 no.6
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• pp.217-222
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• 2009

The production of advanced high strength steels requires the improvement of cooling technology. The use of high cooling rates allows relatively low levels of expensive alloying additions to ensure sufficient hardenability. In classical annealing and hot-dip galvanizing lines a mixing station is used to provide atmosphere gas containing 3-5% hydrogen and 97-95% nitrogen in the various sections of the furnace, including the rapid cooling section. Heat exchange enhancement in this cooling section can be insured by the increased hydrogen concentration. Drever International developed a patented improvement of cooling technology based on the following features: pure hydrogen gas is injected only in the rapid cooling section whereas the different sections of the furnace are supplied with pure nitrogen gas; the control of flows through atmosphere gas management allows to get high hydrogen concentration in cooling section and low hydrogen content in the other furnace zones. This cooling technology development insures higher cooling rates without additional expensive hydrogen gas consumption and without the use of complex sealing equipments between zones. In addition reduction in electrical energy consumption is obtained. This atmosphere control development can be combined with geometrical design improvements in order to get optimised cooling technology providing high cooling rates as well as reduced strip vibration amplitudes. Extensive validation of theoretical research has been conducted on industrial lines. New lines as well as existing lines, with limited modifications, can be equipped with this new development. Up to now this technology has successfully been implemented on 6 existing and 7 new lines in Europe and Asia.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.743-752
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• 2007

Proteins combine with other materials to achieve their function and have similar function if their active sites are similar. Thus we can infer the function of protein by identifying the binding area of proteins. This paper suggests the novel method to select binding area of protein using MCL (Markov Cluster) algorithm. We construct the distance matrix from surface residues distance on protein. Then this distance matrix is transformed to connectivity matrix for applying MCL process. We adopted Catalytic Site Atlas (CSA) data to evaluate the proposed method. In the experimental result using CSA data (94 selected single chain proteins), our algorithm detects the 91 (97%) binding area near by active site of each protein. We introduced a new geometrical features and this mainly contributes to reduce the time to analyze the protein by selecting the residues near by active site.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.754-758
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• 2005

Optimization of process variables such as arc current, welding voltage and welding speed in terms of the weld characteristics desired is the key step in achieving high quality and improving performance characteristics without increasing the cost. Consequently, incorrect settings of those process variables give rise to deviations in the welding characteristics from the desired bead geometry. Therefore, trainee welders are referred to the tabulated information relating different metal types and thickness as to recommend the desired values of process variables. Basically, the bead geometry plays an important role in determining the mechanical properties of the weld. So that it is very important to select the process variables for obtaining optimal bead geometry. However, it is difficult for the traditional identification methods to provide an accurate model because the optimized welding process is non-linear and time-dependent. In this paper, the possibilities of the Infra-red sensor in sensing and control of the bead geometry in the automated welding process are presented. Infra-red sensor is a well-known method to deal with the problems with a high degree of fuzziness so that the sensor is employed to build the relationship between process variables and the quality characteristic the proposed above respectively. Based on several neural networks, the mathematical models are derived from extensive experiments with different welding parameters and complex geometrical features. The developed system enables to select the optimal welding parameters and control the desired weld dimensions during arc welding process.

• Steel and Composite Structures
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• v.19 no.2
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• pp.277-292
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• 2015

Previous research has shown that steel plate shear walls (SPSWs) are efficient lateral force-resisting systems against both wind and seismic loads. A properly designed SPSW can have high initial stiffness, strength, and energy absorption capacity as well as superior ductility. SPSWs have been commonly designed with unstiffened and stiffened infill plates based on economical and performance considerations. Recent introduction and application of corrugated plates with advantageous structural features has motivated the researchers to consider the employment of such elements in stiffened SPSWs with the aim of lowering the high construction cost of such high-performing systems. On this basis, this paper presents results from a numerical investigation of the hysteretic performance of SPSWs with trapezoidally corrugated infill plates. Finite element cyclic analyses are conducted on a series of flat- and corrugated-web SPSWs to examine the effects of web-plate thickness, corrugation angle, and number of corrugation half-waves on the hysteretic performance of such structural systems. Results of the parametric studies are indicative of effectiveness of increasing of the three aforementioned web-plate geometrical and corrugation parameters in improving the cyclic response and energy absorption capacity of SPSWs with trapezoidally corrugated infill plates. Increasing of the web-plate thickness and number of corrugation half-waves are found to be the most and the least effective in adjusting the hysteretic performance of such promising lateral force-resisting systems, respectively. Findings of this study also show that optimal selection of the web-plate thickness, corrugation angle, and number of corrugation half-waves along with proper design of the boundary frame members can result in high stiffness, strength, and cyclic performances of such corrugated-web SPSWs.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.97-107
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• 2006

In this paper, we present a method for the detection and recognition of rectangular markers from a camera image. It converts the camera image to a binary image and extracts contours of objects in the binary image. After that. it approximates the contours to a list of line segments. It finds rectangular markers by using geometrical features which are extracted from the approximated line segments. It normalizes the shape of extracted markers into exact squares by using the warping technique. It extracts feature vectors from marker image by using principal component analysis. It then calculates the distance between feature vector of input marker image and those of standard markers. Finally, it recognizes the marker by using minimum distance method. Experimental results show that the Proposed method achieves 98% recognition rate at maximum for 50 markers and execution speed of 11.1 frames/sec for images which contains eleven markers.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.1-8
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• 2020

This study presents a shear strength estimation model, in which the shear failure of a reinforced concrete (RC) member is assumed to be governed by the flexure-shear mechanism. Two shear demand curves and corresponding potential capacity curves for cracked tension and uncracked compression zones are derived, for which the bond mechanism developed between reinforcing bars and surrounding concrete is considered in flexural analysis. The shear crack concentration factor is also addressed to consider the so-called size effect induced in large RC members. In addition,unlike exising methods, a new formulation was addressed to consider the interaction between the shear contributions of concrete and stirrup. To verify the proposed method, an extensive shear database was established, and it appeared that the proposed method can capture the shear strengths of the collected test specimens regardless of their material properties, geometrical features, presence of stirrups, and bond characteristics.