• Progress in Superconductivity and Cryogenics
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• v.20 no.3
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• pp.5-10
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• 2018

This study presents that various grain boundary junctions are prepared by controlling the seed orientation combined with an artificial hole in a melt process REBCO bulk superconductor. Large grain YBCO superconductors have been fabricated with various grain boundary junctions that the angle between the grain boundary and the <001> axis of Y123 crystal is $0^{\circ}$, $30^{\circ}$ and $45^{\circ}$, respectively. The presence of the artificial hole is beneficial for the formation of clean grain boundary junction and single peak trapped magnetic field profiles have been obtained. Artificial hole makes two growth fronts meet at a point on a periphery of the artificial hole. The presence of artificial hole is not likely to affect on the distribution of Y211 particles. The newly formed <110> facet lines are explained by the formation of new Y123/liquid interface with (010) crystallographic plane.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.956-963
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• 2001

The measurement of residual stresses by the hole-drilling method has been commonly used to evaluate residual stresses in structural members. In this method, eccentricity can usually occur between the hole center and rosette gage center. In this study, the error due to the hole eccentricity is predicted using the artificial neural network. The neural network has trained training examples of stress ratio, normalized eccentricity, off-centered direction and stress error using backpropagation loaming process. The prediction results of the error using the trained neural network are good agreement with FE analyzed ones.

• Journal of Welding and Joining
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• v.16 no.3
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• pp.64-73
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• 1998

This paper is concerned with defects detection and evaluation of heat affected zone (HAZ) in austenitic stainless steel type 304 by ultrasonic wave and neural network. In experiment, the reflected ultrasonic defect signals from artificial defects (side hole, vertical hole, notch) of HAZ appears as beam distance of prove-defect, distance of probe-surface, depth of defect-surface on CRT. For defect classification simulation, neural network system was organized using total results of ultrasonic experiment. The organized neural network system was learned with the accuracy of 99%. Also it could be classified with the accuracy of 80% in side hole, and 100% in vertical hole, 90% in notch about ultrasonic pattern recognition. Simulation results of neural network agree fairly well with results of ultrasonic experiment. Thus were think that the constructed system (ultrasonic wave - neural network) in this work is useful for defects dection and classification such as holes and notches in HAZ of austenitic stainless steel 304.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.3
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• pp.436-444
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• 2002

The measurement of residual stresses by the hole-drilling method has been commonly used to evaluate residual stresses in structural members. In this method, eccentricity can usually occur between the hole center and rosette gage center. In this study, the error due to the hole eccentricity is predicted using the artificial neural network. The neural network has trained training examples of stress ratio, normalized eccentricity, off-centered direction and stress error using backpropagation learning process. The prediction results of the error using the trained neural network are good agreement with FE analyzed ones.

• Explosives and Blasting
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• v.36 no.3
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• pp.1-9
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• 2018

This study was conducted to evaluate the influences of the angle of artificial joints, the distance between the artificial joints and the blast hole, and the number of artificial joints on the pressure wave propagation, crack propagation, and blast wave velocity. The evaluation was conducted numerically by use of the Euler-Lagrange solver supported by the AUTODYN, which is a dynamic FEM program. As a result, it was found that the blast wave velocity was decreased most rapidly as either the distance between the artificial joint and the blast hole was decreased or the angle of the artificial joint was increased. In contrast to the case of no artificial joint, the amount of attenuation of the blast wave velocity was considerably large when an artificial joint was present. However, the effect of the number of artificial joint on the attenuation of the blast wave velocity was negligible under the given condition.

• Journal of Power System Engineering
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• v.15 no.4
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• pp.37-41
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• 2011

This paper introduces the special eddy current sensor and its characteristic for bolt hole defect evaluation in gas turbine rotor. In the past, Fluorescent penetration inspection method was used for qualitative defect evaluation in gas turbine rotor bolt hole. This method can defect the bolt hole defect but can not evaluate the defect size. Nowadays, eddy current method is used quantitative defect evaluation due to advanced sensor design technology. And eddy current method is more time and cost saving than the old method. We developed bolt shape eddy current sensor for the rotor bolt hole defect detection and evaluation. The eddy current sensor moves to the bolt hole guided by screw nut and detects the defect on the bolt hole. The bolt hole mock-up and artificial defects were made and used for the signal detection & resolution analysis of eddy current sensor. The results show that signal detection capability is enough to detect 0.2 mm depth defect. And the resolution capability is enough to differentiate 02, 0.5, 1.0 and 2.0 mm depth defect.

• Journal of the Korean Society for Heat Treatment
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• v.12 no.3
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• pp.215-220
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• 1999

Rotary bending fatigue tests were carried out to investigate the artificial defect sensitivity of fatigue limit in annealed and austempered ductile irons. Artificial defect(hole, diameter${\leq}0.4mm$) machined on specimen surface did not bring about an obvious reduction of fatigue limit in austempered ductile iron as compared with annealed. As a result of investigation on $\sqrt{area}$ c which is the critical artificial defect size. $\sqrt{area}$ c of austempered ductile iron is larger than that of annealed. This means that the crack initiation at artificial defect in austempered ductile iron is more difficult in comparison with annealed. In case that the $\sqrt{area}$ c of artificial defect and graphite nodule are same, the rate of crack initiation for graphite nodule is higher than that of artificial defect.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5574-5591
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• 2017

Inspired by the idea of Artificial Immune System, many researches of wireless sensor network (WSN) intrusion detection is based on the artificial intelligent system (AIS). However, a large number of generated detectors, black hole, overlap problem of NSA have impeded further used in WSN. In order to improve the anomaly detection performance for WSN, detector generation mechanism need to be improved. Therefore, in this paper, a Differential Evolution Constraint Multi-objective Optimization Problem based Negative Selection Algorithm (DE-CMOP based NSA) is proposed to optimize the distribution and effectiveness of the detector. By combining the constraint handling and multi-objective optimization technique, the algorithm is able to generate the detector set with maximized coverage of non-self space and minimized overlap among detectors. By employing differential evolution, the algorithm can reduce the black hole effectively. The experiment results show that our proposed scheme provides improved NSA algorithm in-terms, the detectors generated by the DE-CMOP based NSA more uniform with less overlap and minimum black hole, thus effectively improves the intrusion detection performance. At the same time, the new algorithm reduces the number of detectors which reduces the complexity of detection phase. Thus, this makes it suitable for intrusion detection in WSN.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.6
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• pp.56-63
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• 2003

In this study, an automatic ultrasonic testing system is used to detect the defects of the natural flaw test specimen and of the artificial flaw test specimen. We evaluate the detection performance of the acceptance standard for the natural flaw test specimen and of the acceptance standard for the artificial flaw test specimen. We also study the potential problems of those acceptance standards. The results indicate that the acceptance standard for the detection of defects in weldzone is good then the sensitivity correction is performed and that we must clearly specify special check points of the acceptance standard for the system in use.

• Progress in Superconductivity
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• v.12 no.1
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• pp.12-16
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• 2010

We have measured the trapped field of YBCO bulk with different configuration by applying the magnetic field of $Nb_3Sn$ superconducting magnet. Initially the circular type of YBCO bulk superconductor was prepared and then hole, parallel to the c-axis and located at the center of bulk was mechanically drilled. The YBCO bulk with hole was filled with resin. Typical size of hole in YBCO bulk was 10 mm in diameter. Trapped field characteristics were compared with different specimen conditions. Our preliminary result indicates the increment rate of trapped field, 0.232 kG, measured on the YBCO without hole was much higher than that, 0.011 kG, measured on YBCO with hole.