this paper presents the application of three main artificial neural networks (anns) in damage detection of steel bridges. this method has the ability to indicate damage in structural elements due to a localized change of stiffness called damage zone. the changes in structural response is used to identify the states of structural damage. to circumvent the difficulty arising from the non-linear n...

this paper presents new sensitivity-based methods for detection of structural damage using incomplete noisy modal data. these methods are based on the first-order derivative of modal parameters. changes of natural frequency do not usually provide spatial information on the structural damage. they are also not sensitive to the local damage. in this paper, a new sensitivity function is proposed u...

During their service life, marine pipelines continually accumulate damage as a result of the action of various environmental forces. Clearly, the development of robust techniques for early damage detection is very important to avoid the possible occurrence of a disastrous structural failure. Most of vibration-based damage detection methods require the modal properties that are obtained from mea...

this paper presents the application of three main artificial neural networks (anns) in damage detection of steel bridges. this method has the ability to indicate damage in structural elements due to a localized change of stiffness called damage zone. the changes in structural response is used to identify the states of structural damage. to circumvent the difficulty arising from the non-linear n...

Structural health monitoring and damage detection is one of the most important subjects for mechanic and aerospace engineers. Structural fault can cause uncompensated problems for both human and environment. There are several methods for solving this problem, but the most useful methods are those which focuse on structural change in the vibrational properties. This paper presents a feasibility ...

an analytical nonlinear stress-strain model and a microscopic damage index for confined and unconfined concretes together with a macroscopic damage index for reinforced concrete (rc) structures under cyclic loading are proposed. in order to eliminate the problem of scale effect, an adjustable finite element computer program was generated to simulate rc structures subjected to cyclic loading. by...

This paper presents the application of three main Artificial Neural Networks (ANNs) in damage detection of steel bridges. This method has the ability to indicate damage in structural elements due to a localized change of stiffness called damage zone. The changes in structural response is used to identify the states of structural damage. To circumvent the difficulty arising from the non-linear n...

The determination of structural and nonstructural damage under earthquake excitations is usually considered as a key factor in performance-based seismic design (PBSD) methods is In this regard, various damage indices have been developed in recent years to quantitatively estimate structural damage. The aim of this study is to develop a simple method to evaluate performance levels of zipper-brace...

the main cause of structural damage in buildings subjected to seismic actions is lateral drift. in almost all reinforced concrete (rc) structures, whether designed with walls or frames, it is likely to be the code drift limits that control the design drift. the design drift limits and their contribution to damage may be represented indirectly through the material strain limits. the aim of this ...