This state-of-the-art review comprehensively evaluates the seismic design and performance
assessment of concentrically braced frame (CBF) systems, specifically focusing on special …

This paper presents a rapid machine learning-based damage detection framework for
identifying the damage extent of concrete shear wall buildings. For this purpose, a …

The purpose of this study is to utilize machine learning techniques to detect any damages
that occurred in power transmission towers. In the first step, various machine learning …

Bridges are a crucial part of the transport infrastructure network, and their safety and
operational conditions need to be ensured. An early warning of damage is valuable for …

Recent earthquakes illustrated that damage to highway bridges, as one of the critical
components of transportation systems, could lead to irreparable social and economic losses …

The evaluation of structural response constitutes a fundamental task in the design of ground-
excited structures. In this context, the Monte Carlo simulation is a powerful tool to estimate …

In this paper, a damage detection strategy for beam-type structures based on frequency
response functions (FRFs) is presented. Five aluminum beams of equal nominal dimensions …

Methods of structural health monitoring (SHM) are often challenged by changing
environmental and operational conditions (EOC). This paper presents a novel experimental …

Structural health inspection systems are widely used to manage and maintain infrastructure
that involves massive sensor devices. However, these sensors receive the natural …

Structural health monitoring based on vibration signal analysis has been extensively
employed for damage identification. Mainstream machine learning techniques, such as …