• Tribology and Lubricants
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• v.17 no.1
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• pp.22-27
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• 2001

This paper presents an analysis of eccentricity ratio of rolling piston using mobility method which is a powerful tool for analyzing dynamically-loaded journal bearings with efficiency and applicability. And, we investigate influences of design parameters (discharge pressure, radial clearance, rotational velocity of shaft, and eccentricity of compressor) on bearing load and eccentricity ratio. The results show that the discharge pressure, radial clearance and rotational velocity of shaft have significant influence on eccentricity ratio, and the discharge pressure and eccentricity of compressor have influence on bearing load.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.12
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• pp.2475-2482
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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 compensated using the neural network. The neural network has trained training examples of normalized eccentricity, eccentric direction and direction of maximum stress at eccentric case using backpropagation learning process. The trained neural network could compensated the error of measured residual stress in experiments with hole eccentricity. The proposed neural network is very useful for compensation of the error due to hole eccentricity in hole-drilling method.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.412-418
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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 corrected using the neural network. The neural network has trained training examples of normalized eccentricity, eccentric direction and direction of maximum stress at eccentric case using backpropagation learning process. The trained neural network could corrected the error of measured residual stress in experiments with hole eccentricity. The proposed neural network is very useful for correction of the error due to hole eccentricity in hole-drilling method.

• Journal of Korean Association for Spatial Structures
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• v.1 no.1 s.1
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• pp.117-124
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• 2001

In Single-layer latticed domes with rectangular network which is composed of ring of circumferential direction and rafter of longitudinal direction, that is, rib domes, if we use the cross-membered junction's method for the advantage in fabrication and construction, the eccentricity is occurred in the nodal point of crossing members. This paper is aimed at investigating the buckling characteristics for the effect of eccentricity according to rise-span ratios and distance of eccentricity. Analysis method is based on FEM dealing with the geometrically nonlinear deflection problems. The conclusion were given as follows: 1. The maximum decreasing ratio of buckling strength due to the junction's eccentricity is about 60% in models of this paper. 2. In the increasing ratio of buckling strength for rise-span ratio, that of Type 3 models is larger than that of type 2 models. On the other hand, that of Type 2 mode is larger than that of Type 3 for eccentricity-distance. 3. In the viewpoint of the value of buckling strength, that of Type 2 models is larger than that of type 3 models. The effect of the junction's rigidity on buckling strength is not great for overall models. Therefore if we use the cross-membered junction's method for the advantage in fabrication and construction, the method of Type 2 will have the great advantage of that of Type 3.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1480-1483
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• 1996

A set of approaches suggested to control the eccentricity is discussed in this paper. Among these, filter-integrator method is used to design the controller, which also includes the input signal synchronization, stabilizing filter and eccentricity source discrimination. Using the S/W that is coded for real time application of that controller, we simulated the operations of that one. The simulation results show the characteristics of eccentricity compensation and eccentricity discrimination. However, from these results, we can see that only proper stabilization strategy certificates the safe eccentricity control.

• Structural Engineering and Mechanics
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• v.41 no.4
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• pp.527-538
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• 2012

In seismic analyses of structures, additional eccentricity is introduced to take account for oscillations of random and unknown origins. In many codes of practice, the torsion about the vertical axis is considered through empirical accidental eccentricity formulation. Due to the random nature of structural systems, it is very difficult to evaluate the accidental eccentricity in a deterministic way and to specify its effect on the overall seismic response of structures. The aim of this study is to develop a procedure for the evaluation of the accidental eccentricity induced by uncertainties in stiffness and mass of structural members, using the neural network techniques coupled with Monte Carlo simulations. This method gives very interesting results for single story structures. For real structures, this method can be used as a tool to determine the accidental eccentricity in the seismic vulnerability studies of buildings.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.8 s.179
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• pp.2059-2064
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• 2000

The measurement of residual stresses by the hole-drilling method has been commonly used to evaluate residual stresses in structural members. In this method, one of the source of error is due to the misalignment between the drilling hole and strain gage center. This paper presents a finite element analysis of the influence of such misalignment for the uniaxial residual stress field. The stress error increases proportionally to hole eccentricity. The correction equations which easily obtain the residual stress taking account of the hole eccentricity are derived. The stress error due to the hole eccentricity decreases by approximately one percent using this equations.

• 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 the Earthquake Engineering Society of Korea
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• v.17 no.5
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• pp.237-243
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• 2013

In the Korean Building Code (KBC), the Design Eccentricity involves the torsional amplification factor (TAF), and the inherent and accidental eccentricities. When a structure of less than 6-stories and assigned to seismic design category C or D is designed using equivalent static analysis method, both KBC-2006 and KBC-2009 use the TAF but apply different calculation methods for the of design eccentricity. The design eccentricity in KBC-2006 is calculated by multiplying the sum of inherent eccentricity and accidental eccentricity at each level by a TAF but that in KBC-2009 is calculated by multiplying only the accidental eccentricity by a TAF. In this paper, the damage indices of a building with planar structural irregularity designed by different design eccentricities are compared and the relationship between the earthquake damage and design eccentricity of the building is evaluated. On the basis of this study, the increment of design eccentricity results in the decrement of final eccentricity and global damage index of structure. It is observed that design eccentricity in KBC-2006 reduces the vulnerability of torsional irregular building compared to design eccentricity in KBC-2009.