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Advances in Structural Health Monitoring for Infrastructures

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Advanced Materials Characterization".

Deadline for manuscript submissions: closed (20 September 2023) | Viewed by 5562

Special Issue Editors


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Guest Editor
Department of Engineering Mechanics, College of Mechanics and Materials, Hohai University, Nanjing 210098, China
Interests: structural health monitoring; structural damage identification; vibro-acoustics
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Road Transport, Faculty of Transport and Aviation Engineering, Silesian University of Technology, 40-019 Katowice, Poland
Interests: transport; civil and mechanical engineering; vibroacoustic; noise and vibration; machine diagnostic; epidemic risk and transport safety; transport environmental issues
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Civil and Environmental Engineering, University of South Carolina, Columbia, SC 29208, USA
Interests: structural health monitoring; probabilistic analysis; nonlinear vibrations; machine learning; earthquake engineering
Special Issues, Collections and Topics in MDPI journals

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Guest Editor

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Guest Editor Assistant
1. College of Automation and College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210046, China 2. College of Civil and Transportation Engineering, Hohai University, 210098 Nanjing, China
Interests: optimization; soft computing; structural health monitoring; damage detection; evolutionary computation; fuzzy logic; swarm algorithms; deep learning; manufacturing; welding; evolutionary algorithms; damage identification; neural networks; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

A considerable amount of infrastructure has been constructed over the past few decades. Building materials of infrastructures could encounter degradation, corrosion, fatigue, etc., due to long-term services, as well as environmental and loading factors. Initial defects and damage could become more severe over time and threaten the safety and integrity of infrastructures. In this context, in-service infrastructures are anticipated to face a massive increase in demand for structural health monitoring (SHM) in the next decade. Advanced sensing networks and emerging technologies of big data and artificial intelligence have brought new opportunities and shown significant potential in the SHM field. Hence, it is of great significance to develop advanced sensing, processing, and evaluating technologies for SHM of infrastructures.

This Special Issue aims to collect papers that focus on all aspects of advances in SHM for infrastructures. The collections will be published after being peer-reviewed. The topics include but are not limited to:

  • Structural health monitoring
  • Structural damage identification
  • SHM-oriented building materials
  • Smart sensors
  • In-suit/wireless/online sensing networks
  • Big data/artificial intelligence technologies
  • Modal analysis and signal processing
  • Load identification and monitoring
  • Structural model updating
  • Vibration isolation and control
  • Failure prognostics and early warning
  • Structural health management
  • Structural condition/integrity/safety assessment

Prof. Dr. Wei Xu
Prof. Dr. Rafal Burdzik
Dr. Mahmoud Bayat
Prof. Dr. Maosen Cao
Guest Editors

Dr. Nizar Faisal Alkayem
Guest Editor Assistant

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Materials is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (3 papers)

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Research

14 pages, 3565 KiB  
Article
Permeability Coefficient of Concrete under Complex Stress States
by Jiafeng Gu, Qingwen Ren, Mei Tao, Yan Han and Linfei Zhang
Materials 2023, 16(12), 4368; https://doi.org/10.3390/ma16124368 - 13 Jun 2023
Viewed by 1251
Abstract
Hydraulic structures are typically subjected to long-term hydraulic loading, and concrete—the main material of structures—may suffer from cracking damage and seepage failure, which can threaten the safety of hydraulic structures. In order to assess the safety of hydraulic concrete structures and realize the [...] Read more.
Hydraulic structures are typically subjected to long-term hydraulic loading, and concrete—the main material of structures—may suffer from cracking damage and seepage failure, which can threaten the safety of hydraulic structures. In order to assess the safety of hydraulic concrete structures and realize the accurate analysis of the whole failure process of hydraulic concrete structures under the coupling effect of seepage and stress, it is vital to comprehend the variation law of concrete permeability coefficients under complex stress states. In this paper, several concrete samples were prepared, designed for loading conditions of confining pressures and seepage pressures in the first stage, and axial pressures in the later stage, to carry out the permeability experiment of concrete materials under multi-axial loading, followed by the relationships between the permeability coefficients and axial strain, and the confining and seepage pressures were revealed accordingly. In addition, during the application of axial pressure, the whole process of seepage–stress coupling was divided into four stages, describing the permeability variation law of each stage and analyzing the causes of its formation. The exponential relationship between the permeability coefficient and volume strain was established, which can serve as a scientific basis for the determination of permeability coefficients in the analysis of the whole failure process of concrete seepage–stress coupling. Finally, this relationship formula was applied to numerical simulation to verify the applicability of the above experimental results in the numerical simulation analysis of concrete seepage–stress coupling. Full article
(This article belongs to the Special Issue Advances in Structural Health Monitoring for Infrastructures)
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19 pages, 4360 KiB  
Article
The Study of Localized Crack-Induced Effects of Nonlinear Vibro-Acoustic Modulation
by Dariusz Broda, Krzysztof Mendrok, Vadim V. Silberschmidt, Lukasz Pieczonka and Wieslaw J. Staszewski
Materials 2023, 16(4), 1653; https://doi.org/10.3390/ma16041653 - 16 Feb 2023
Cited by 4 | Viewed by 1372
Abstract
The nonlinear interaction of longitudinal vibration and ultrasound in beams with cracks is investigated. The central focus is on the localization effect of this interaction, i.e., the locally enhanced nonlinear vibro-acoustic modulation. Both numerical and experimental investigations are undertaken. The finite element (FE) [...] Read more.
The nonlinear interaction of longitudinal vibration and ultrasound in beams with cracks is investigated. The central focus is on the localization effect of this interaction, i.e., the locally enhanced nonlinear vibro-acoustic modulation. Both numerical and experimental investigations are undertaken. The finite element (FE) method is used to investigate different crack models, including the bi-linear crack, open crack, and breathing crack. A parametric study is performed considering different crack depths, locations, and boundary conditions in a two-dimensional beam model. The study shows that observed nonlinearities (i.e., nonlinear crack–wave modulations) are particularly strong in the vicinity of the crack, allowing not only for crack localization but also for the separation of the crack-induced nonlinearity from other sources of nonlinearity. Full article
(This article belongs to the Special Issue Advances in Structural Health Monitoring for Infrastructures)
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24 pages, 5942 KiB  
Article
Probabilistic Structural Model Updating with Modal Flexibility Using a Modified Firefly Algorithm
by Zhouquan Feng, Wenzan Wang and Jiren Zhang
Materials 2022, 15(23), 8630; https://doi.org/10.3390/ma15238630 - 3 Dec 2022
Cited by 2 | Viewed by 1247
Abstract
Structural model updating is one of the most important steps in structural health monitoring, which can achieve high-precision matching between finite element models and actual engineering structures. In this study, a Bayesian model updating method with modal flexibility was presented, where a modified [...] Read more.
Structural model updating is one of the most important steps in structural health monitoring, which can achieve high-precision matching between finite element models and actual engineering structures. In this study, a Bayesian model updating method with modal flexibility was presented, where a modified heuristic optimization algorithm named modified Nelder–Mead firefly algorithm (m-NMFA) was proposed to find the most probable values (MPV) of model parameters for the maximum a posteriori probability (MAP) estimate. The proposed m-NMFA was compared to the original firefly algorithm (FA), the genetic algorithm (GA), and the particle swarm algorithm (PSO) through the numerical illustrative examples of 18 benchmark functions and a twelve-story shear frame model. Then, a six-story shear frame model test was performed to identify the inter-story stiffness of the structure in the original and the damage states, respectively. By comparing the two, the position and extent of damage were accurately found and quantified in a probabilistic manner. In terms of optimization, the proposed m-NMFA was powerful to find the MPVs much faster and more accurately. In the incomplete measurement case, only the m-NMFA achieved target damage identification results. The proposed Bayesian model updating method has the advantages of high precision, fast convergence, and strong robustness in MPV finding and the ability of parameter uncertainty quantification. Full article
(This article belongs to the Special Issue Advances in Structural Health Monitoring for Infrastructures)
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