Issue 64

P. Ghannadi et alii, Frattura ed Integrità Strutturale, 64 (2023) 51-76; DOI: 10.3221/IGF-ESIS.64.04

A review of the application of the simulated annealing algorithm in structural health monitoring (1995-2021)

Parsa Ghannadi Department of Civil Engineering, Ahar Branch, Islamic Azad University, Ahar, Iran parsa.ghannadi@gmail.com, https://orcid.org/0000-0001-5441-9243 Seyed Sina Kourehli Department of Civil Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran ss.kourehli@azaruniv.ac.ir, https://orcid.org/0000-0001-7599-8053 Seyedali Mirjalili Centre for Artificial Intelligence Research and Optimisation, Torrens University, Adelaide, SA 5000, Australia Yonsei Frontier Lab, Yonsei University, Seoul, South Korea ali.mirjalili@torrens.edu.au, https://orcid.org/0000-0002-1443-9458

A BSTRACT . In recent years, many innovative optimization algorithms have been developed. These algorithms have been employed to solve structural damage detection problems as an inverse solution. However, traditional optimization methods such as particle swarm optimization, simulated annealing (SA), and genetic algorithm are constantly employed to detect damages in the structures. This paper reviews the application of SA in different disciplines of structural health monitoring, such as damage detection, finite element model updating, optimal sensor placement, and system identification. The methodologies, objectives, and results of publications conducted between 1995 and 2021 are analyzed. This paper also provides an in-depth discussion of different open questions and research directions in this area. K EYWORDS . Simulated Annealing, Inverse Problem, Structural Health Monitoring, Damage Detection

Citation: Ghannadi, P., Kourehli, SS., Mirjalili, SA., A review of the application of the simulated annealing algorithm in structural health monitoring (1995-2021), Frattura ed Integrità Strutturale, 64 (2023) 51-76.

Received: 13.09.2022 Accepted: 06.01.2023 Online first: 18.01.2023 Published: 01.04.2023

Copyright: © 2023 This is an open access article under the terms of the CC-BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

I NTRODUCTION

he vital role of structures and infrastructures is undeniable in organizing voluminous human activities in large societies [1]. These structures are exposed to damage due to extreme conditions such as strong earthquakes, winds, or human-induced events [2,3]. Many structures have been constructed and are still in service despite expiration [4]. For instance, approximately 40% of bridges are more than fifty years old in the United States of America [5]. To provide structural safety and avoid human disasters and also financial losses, structural health monitoring (SHM) is a necessary T

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