Stress Evaluation in Axially Loaded Members of Masonry Buildings and Space Structures: From Traditional Methods to Combinations with Artificial Intelligence Approaches

Abstract

Stress state evaluation in axially loaded structural members is significant for sustaining and preserving the service life of buildings. While successful monitoring furnishes staunch information on the health, integrity, safety and serviceability of structures, maintaining the structural performance of a building with time significantly depends on assessing the occurrence. Variations in the stress in axially loaded members may occur in masonry buildings or space structures caused by different conditions and human-induced factors. In the last decades, numerous nondestructive methods have been generated to furnish practical means for identifying axial load in the tie-rods of masonry buildings and in the structural members of space structures. Significant effort has been put into dynamic-based approaches, which make use of the vibrational response of the monitored member to investigate its condition and evaluate the axial load. In particular, wide laboratory and field tests have been executed worldwide, resulting in several findings. Meanwhile, with flourishing sensing technology and computing power, Artificial Intelligence (AI) applications, such as hybrid methods, optimization techniques and deep learning algorithms, have become more practicable and widely used in vibration-based axial stress prediction, with efficiency and, frequently, with strict precision. While there have been various manuscripts published on dynamic-based axial stress evaluation, there are no works in which the passage from traditional methods to combinations with AI approaches have been illustrated. This article aims to address this gap by introducing the highlights of the traditional methods, and furnish a review of the applications of AI techniques used for nondestructive-based axial stress prediction in tie-rods and structural members. Conclusions, including further studies and field developments, have also been mentioned at the end of the article.

Research on the Method of Absolute Stress Measurement for Steel Structures via Laser Ultrasonic

“…Destructive testing, which can harm the integrity of the bridge, is not ideal for regular checks [5,6]. Consequently, the non-destructive testing/dynamic monitoring approaches of stress in steel structures, including ultrasonic and magnetic flux leakage testing, along with the corresponding artificial intelligence algorithms, have become the primary focus of research [7][8][9][10]. Ultrasonic testing, in particular, has widespread application, but its effectiveness is hampered by the need for direct contact and couplants, which can affect measurement sensitivity and accuracy [11,12].…”

Identifying Damage in Structures: Definition of Thresholds to Minimize False Alarms in SHM Systems

“…In the vibration-based method, damage detection is achieved by examining changes in the measured vibration response, where the modal parameters (natural frequencies, mode shapes, and modal damping) are indicative of the physical properties (mass, damping, and stiffness) of a structure [9]. Thus, changes in structural properties result in changes in modal properties [10][11][12], which can be detected either absolutely or more often by comparison to an undamaged state. Vibration-based damage detection has garnered significant attention, with a variety of methods proposed over Buildings 2024, 14, 821 2 of 16 recent decades, ranging from those based on changes in modal parameters to those incorporating signal processing, model updating, and optimization algorithms.…”