• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.9
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• pp.884-891
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• 2009

This study investigates some of swarm intelligence algorithms to tackle a traditional damage detection problem having stiffness degradation or damage in mechanical structures. Particle swarm(PSO) and ant colony optimization(ACO) methods have been exploited for localizing and estimating the location and extent damages in a structure. Both PSO and ACO are population-based, stochastic algorithms that have been developed from the underlying concept of swarm intelligence and search heuristic. A finite element (FE) model updating is implemented to minimize the difference in a set of natural frequencies between measured and baseline vibration data. Stiffness loss of certain elements is considered to simulate structural damages in the FE model. It is numerically shown that PSO and ACO algorithms successfully completed the optimization process of model updating in locating unknown damages in a truss structure.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.137-142
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• 2008

In this paper, we apply a logistic regression model to the data of snow damage on sugi (Cryptomeria japonica) occurred in Toyama prefecture (in Japan) in 2004 for estimating the risk probability. In order to specify the factors effecting snow damage, we apply a model selection procedure determining optimal subset of explanatory variables. In this process we consider the following 3 information criteria, 1) Akaike's information criterion, 2) Baysian information criterion, 3) Bias-corrected Akaike's information criterion. For the selected variables, we give a proper interpretation from the viewpoint of natural disaster.

• Smart Structures and Systems
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• v.18 no.5
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• pp.839-864
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• 2016

This paper presents an efficient method for updating the structural finite element model. Model updating is performed through minimizing the difference between the recorded acceleration of a real damaged structure and a hypothetical damaged one. This is performed by updating physical parameters (module of elasticity in this study) in each step using iterative process of modified nonlinear conjugate gradient (M-NCG) and modified Broyden-Fletcher-Goldfarb-Shanno algorithm (M-BFGS) separately. These algorithms are based on sensitivity analysis and provide a solution for nonlinear damage detection problem. Three illustrative test examples are considered to assess the performance of the proposed method. Finally, it is demonstrated that the proposed method is satisfactory for detecting the location and ratio of structural damage in presence of noise.

• Textile Coloration and Finishing
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• v.24 no.1
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• pp.27-32
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• 2012

Generally, hair treatments by complementary actions to give a sense of activity are permanent setting, dyeing, and bleaching, etc. In this study, we investigated the wave formation ability and hair damage occuring in permanent setting and bleaching process. The wave formation ability was evaluated by the differences of length and curl diameter after permanent setting. And the hair damage was also evaluated by the protein release ability and SEM of hair. The bleached hair immediately after permanent setting treatment has better wave formation ability, but much more damaged than the bleached hair after rinsing thoroughly with warm water. It was considered that the chain of hair keratin broke down easily by the bleaching action in the existence of permanent setting agents.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.56-64
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• 2008

To maintain effectively the functionality of major railroad facilities such as bridges, identifying and evaluating damage in a structure and taking appropriate action via continuous structural health monitoring are very important. However, most damage identification methods for structural health monitoring developed to date utilize modal domain responses which inevitably contain errors in transforming the domain of responses. In this paper, a damage identification method using time-domain operational deflection shapes is proposed. Since the proposed method utilizes time-domain responses, the error in the process of transformation to response domain can be avoided, and the accuracy of structural health evaluation can be improved. The feasibility of the proposed method is verified via a numerical example of a simple bridge structure.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.321-329
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• 2002

Artificial neural network has been used for damage assessment by many researchers, but there are still some barriers that must be overcome to improve its accuracy and efficiency. The major problems with the conventional neural network are the necessity of many training patterns for neural network teaming process and ambiguity in the relationship of neural network structure to the convergence of solution. In this paper, the PNN is used as a pattern classifier to detect the damages of the railway bridge using dynamic response. The comparison between the mode shape and the natural frequency of structure as training pattern is investigated for approriate selection of the training pattern in the damage detection of railway bridge using the PNN.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.11a
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• pp.124-127
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• 2000

In this study, a technique for monitoring of fatigue damage of composite laminates by measuring the stiffness change using embedded intensity-based optical fiber sensors was investigated. Firstly, the underlying measurement principle and structure of intensity-based sensors and then a simple stiffness conversion process was explained. The monitoring technique was evaluated by fatigue tests of composite laminates with an embedded intensity-based sensor. From the test results, the response of the intensity-based sensor showed good correlation with that of surface mounted extensometer. Therefore, it can be concluded that the intensity-based sensors have good potential for the monitoring of fatigue damage of composite structures under fatigue loading. In addition, it could be confirmed that the intensity-based sensors have higher resistance to fatigue than the commercial electrical strain gauge.

• Journal of the Society of Naval Architects of Korea
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• v.29 no.4
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• pp.179-192
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• 1992

An elasto-plastic-damage constitutive model for ductile materials was derived under the framework of thermodynamic approach of contimuum damage mechanics(CDM) in which internal irreversible thermodynamic change of micro-structure of materials such as plastic deformation and damage evolution were considered as thermodynamic state variables. New constitutive model can predict not only the elasto-plastic behaviors but also the sequential degradation process of ductile materials more rationally.

• Structural Engineering and Mechanics
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• v.45 no.2
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• pp.211-232
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• 2013

In this study a multi-objective optimization problem is solved. The objectives used here include simultaneous minimum construction cost in term of sections weight, minimum structural damage using a damage index, and minimum non-structural damage in term of inter-story drift under the applied ground motions. A high-speed and low-error neural network is trained and employed in the process of optimization to estimate the results of non-linear time history analysis. This approach can be utilized for all steel or concrete frame structures. In this study, the optimal design of a planar eccentric braced steel frame is performed with great detail, using the presented multi-objective algorithm with a discrete population and then a moment resisting frame is solved as a supplementary example.

• Computers and Concrete
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• v.13 no.5
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• pp.633-648
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• 2014

The seismic safety of concrete dams is one of the important problems in the engineering due to the vast socio-economic disasters which may be caused by collapse of these infrastructures. The accuracy of the risk evaluation associated with these existing dams as well as the efficient design of future dams is highly dependent on a proper understanding of their behaviour due to earthquakes. This paper develops an anisotropic damage model for arch dam under strong earthquakes. The modified Drucker-Prager criterion is adopted as the failure criteria of the dynamic damage evolution of concrete. Some process fields and other necessary information for the safety evaluation are obtained. The numerical results show that the seismic behaviour of concrete dams can be satisfactorily predicted.