• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.5
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• pp.25-33
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• 2011

In the nonlinear response history analysis of building structures, the input ground accelerations have considerable effect on the nonlinear response characteristics of structural systems. As the properties of the ground motion, using time history analysis, are interrelated with many factors such as the fault mechanism, the seismic wave propagation from source to site, and the amplification characteristics of the soil, it is difficult to properly select the input ground motions for seismic response analysis. In this paper, the most unfavourable real seismic design ground motions were selected as input motions. The artificial earthquake waves were generated according to these earthquake events. The artificial waves have identical phase angles to the recorded earthquake waves, and their overall response spectra are compatible with the seismic design spectrum with 5% of critical viscous damping. It is concluded that the artificial earthquake waves simulated in this paper are applicable as input ground motions for a seismic response analysis of building structures.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.547-552
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• 2006

There have been various cohesion measurements studied considering reference relation among attributes and methods in a class. Generally, these cohesion measurement are camed out in one class. If the range of reference relation considered are extended from one class to two classes, we could find out the reference relation between two classes. Tn this paper, we proposed a neural network to determine the method location. Neural network is effective to predict output value from input data not to be included in training and generalize after training input and output pattern repeatedly. Learning vector is generated with 30-dimensional input vector and one target binary values of method location in a constraint that there are two classes which have less than or equal to 5 attributes and methods The result of the proposed neural network is about 95% in cross-validation and 88% in testing.

• Journal of the Korean Ceramic Society
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• v.47 no.6
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• pp.498-502
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• 2010

Aluminium titanate($Al_2TiO_5$) has extremely anisotropic thermal expansion properties in single crystals, and polycrystalline material spontaneously microcracks in the cooling step after sintering process. These fine intergranular cracks limit the strength of the material, but provide an effective mechanism for absorbing strain energy during thermal shock and preventing catastrophic crack propagation. Furthermore, since machinable BN-ceramics used as an insulating substrate in current micro-electronic industry are very expensive, the development of new low-cost machinable substrate ceramics are consistently required. Therefore, cheap $Al_2TiO_5$-machinable ceramics was studied for the replacement of BN ceramics. $Al_2O_3-Al_2TiO_5$ ceramic composite was fabricated via in-situ reaction sintering. $Al_2O_3$ and $TiO_2$ powders were mixed with various mol-ratio and sintered at 1400 to $1600^{\circ}C$ for 1 h. Density, hardness and strength of sintered ceramics were systematically measured. Phase analysis and microstructures were observed by XRD and SEM, respectively. Machinability of each specimens was tested by micro-hole machining. The results of research showed that the $Al_2TiO_5$-composites could be used for low-cost machinable ceramics.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.9
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• pp.1787-1794
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• 2002

TiNi alloy fiber was used to solve the problem of the tensile residual stress as the reinforced material. TiNi alloy fiber improves the tensile strength of composite by occurring compressive residual stress in the matrix using shape memory effect. In order to generate compressive residual stress in TiNi/Al6061 shape memory alloy(SMA) composite, 1, 3 and 5% pre-strains were applied to the composite in advance. It was also evaluated the effect of compressive residual stress corresponding to the pre-strain variation and the volume fraction of TiNi alloy. AE technique was used to clarify the microscopic damage behavior at high temperature and the effect of pre-strain in TiNi/Al6061 SMA composite. The results of the microscopic damage evaluation of TiNi/Al6061 SMA composite under various pre-strain using AE technique can be divided into three stage corresponding to the AE signals. AE counts and events were useful parameters to evaluate the fracture mechanism according to the variation of pre-strain. In addition, two dimensional AE source location technique was applied for monitoring the crack initiation and propagation in composite.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.12
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• pp.2581-2589
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• 2002

In this research, fretting tests were conducted in air to investigate the wear characteristics of fuel cladding materials with the fretting parameters such as normal load, slip amplitude, frequency and the number of cycles. A high frequency fretting wear tester was designed for this experiment by KAERI. After the experiments, the wear volume and the shape of wear contour were measured by the surface roughness tester. Tribologically transformed structures(TTS) were analysed by means of optical and scanning electron microscopes to identify the main wear mechanisms. The results of this study showed that the wear volume were increased with increasing slip amplitude, and the shape of wear contour was transformed V-type to W-type. Also, it was found that the critical slip amplitude was 168${\mu}{\textrm}{m}$. These phenomena mean that wear mechanism transformed partial slip to gross slip to accelerate wear volume. The wear depth increased with an increase of friction coefficient due to increase of normal load and frequency. The fretting wear mechanisms were believed that, after adhesion and surface plastic deformation occurred by relative sliding motion on the contact between two specimens, TTS creation was induced by surface strain hardening and wear debris were detached from the contact surface which were produced by the micro crack propagation and creation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.10
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• pp.1069-1077
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• 2015

In tunnel excavation using blast, the wire saw rock cutting method generates a discontinuity perimeter around the center cut, and thus prevents blast vibration propagation to reduce vibration and noise. Therefore, the method is expected to be easy to use and economical compared with other methods. In this paper, the cutting mechanism of wire saw in tunnel excavation is investigated. A model describing the changes in cutting depth and wire saw shape inside a rock during cutting is established and validated for this purpose. Through a simulation using the model, the important characteristics of wire saw cut are investigated, and the influences of cutting conditions, such as wire saw tension, wire saw speed, feed speed, depth, and diameter of boring, on cutting performance are also examined. A method to improve the cutting performance is proposed based on the results.

• Earthquakes and Structures
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• v.7 no.4
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• pp.587-607
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• 2014

Progressive collapse, which is referred to as the collapse of the entire building under local damages, is a common failure mode happened by earthquakes. The collapse process highly depends on the whole structural system. Since, asymmetry of the building plan leads to the local damage concentration; it may intensify the progressive collapse mechanism of asymmetric buildings. In this research the progressive collapse of regular and irregular 6-story RC ordinary moment resisting frame buildings are studied in the presence of the earthquake loads. Collapse process and collapse propagation are investigated using nonlinear time history analyses (NLTHA) in buildings with 5%, 15% and 25% mass asymmetry with respect to the number of collapsed hinges and story drifts criteria. Results show that increasing the value of mass eccentricity makes the asymmetric buildings become unstable earlier and in the early stages with lower number of the collapsed hinges. So, with increasing the mass eccentricity in building, instability and collapse of the entire building occurs earlier, with lower potential of the progressive collapse. It is also demonstrated that with increasing the mass asymmetry the decreasing trend of the number of collapsed beam and column hinges is approximately similar to the decreasing trend in the average story drifts of the mass centers and stiff edges. So, as an alternative to a much difficult-to-calculate local response parameter of the number of collapsed hinges, the story drift, as a global response parameter, measures the potential of progressive collapse more easily.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.227-247
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• 2018

For intermittently connected wireless sensor networks deployed in hash environments, sensor nodes may fail due to internal or external reasons at any time. In the process of data collection and recovery, we need to speed up as much as possible so that all the sensory data can be restored by accessing as few survivors as possible. In this paper a novel redundant data storage algorithm based on minimum spanning tree and quasi-randomized matrix-QRNCDS is proposed. QRNCDS disseminates k source data packets to n sensor nodes in the network (n>k) according to the minimum spanning tree traversal mechanism. Every node stores only one encoded data packet in its storage which is the XOR result of the received source data packets in accordance with the quasi-randomized matrix theory. The algorithm adopts the minimum spanning tree traversal rule to reduce the complexity of the traversal message of the source packets. In order to solve the problem that some source packets cannot be restored if the random matrix is not full column rank, the semi-randomized network coding method is used in QRNCDS. Each source node only needs to store its own source data packet, and the storage nodes choose to receive or not. In the decoding phase, Gaussian Elimination and Belief Propagation are combined to improve the probability and efficiency of data decoding. As a result, part of the source data can be recovered in the case of semi-random matrix without full column rank. The simulation results show that QRNCDS has lower energy consumption, higher data collection efficiency, higher decoding efficiency, smaller data storage redundancy and larger network fault tolerance.

• Explosives and Blasting
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• v.14 no.4
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• pp.13-19
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• 1996

Lately, the improtance of smooth blasting is increasing on every construction fields, suchas underground caves, tunnels, and roadconstruction, etc. The main purpose of smooth blasting is to prevent unnecessary cracks from the base rockwhich preserved permanently and is to gain the smooth fracture plane. So, in smooth blashing, explosives with low detonating velocity are generally used. But it is difficult to discuss general theory on the smooth blashing because the mechanical properties of pertienent rocks are difficult regionally. Accordingly basic reserches on the smooth blasting are demended. In this paper, the mechanisms of the smooth blasting on the rocks containing discontinuities were discussd. Firstly, the writer predicted the formation of fracture plane and unevenness using mathematical methodology, the next the model blast tests were conducted in order to simulate the crack propagation modes from the blast holes. Through the research, the following conclusions were obtained l)The blast test results were in reasonally good agreement with the theoretical prediction. 2)The degree of discontinuity has an influence on the fracture morphology.