At the time of designing structures up to date, the density and magnitude of the load have
increased, and the requirements for regulation have also become more stringent. To ensure …

In recent years, many innovative optimization algorithms have been developed. These
algorithms have been employed to solve structural damage detection problems as an …

Optimization techniques are among the most promising methods to deal with real-world
problems, consisting of several objective functions and constraints. Over the decades, many …

Time series analysis and novelty detection are effective and promising methods for data-
driven structural health monitoring (SHM) based on the statistical pattern recognition …

Sensitivity-based methods using modal data are effective and reliable tools for damage
localization and quantification. However, those may fail in obtaining reasonable and …

Accurately predicting the dynamics of complex systems governed by partial differential
equations (PDEs) is crucial in various applications. Traditional numerical methods such as …

The structural health monitoring (SHM) approach plays a key role not only in structural
engineering but also in other various engineering disciplines by evaluating the safety and …

This study presents a convolutional neural network (CNN)-based model updating method for
structures using dynamic structural responses. In the presented method, the dynamic …

Finite element (FE) model of updating is the process of calibrating model parameters to
improve the accuracy of numerical prediction. This goal is usually achieved by solving an …

Optimization‐based methods are increasingly being implemented for structural damage
detection problems through the minimization of the objective functions based on vibration …