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Infrastructures
Special Issues
Structural Health Monitoring of Civil Infrastructures
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Structural Health Monitoring of Civil Infrastructures

A special issue of Infrastructures (ISSN 2412-3811). This special issue belongs to the section "Infrastructures and Structural Engineering".

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 47274

Special Issue Editors

Dr. Carlo Rainieri

E-Mail Website
Guest Editor
National Research Council of Italy, Construction Technologies Institute, Corso Nicolangelo Protopisani 70, 80146 Naples, Italy
Interests: operational modal analysis; vibration-based structural health monitoring; self-sensing materials; digital twin of structures and infrastructures
Special Issues, Collections and Topics in MDPI journals
Dr. Andy Nguyen

E-Mail Website
Guest Editor
School of Engineering, University of Southern Queensland, Springfield Central, QLD 4300, Australia
Interests: structural health monitoring; resilient and intelligent infrastructure; AI for infrastructure
Special Issues, Collections and Topics in MDPI journals
Dr. You Dong

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China
Interests: risk and resilience; structural engineering; lifecycle engineering; climate change; sustainability
Special Issues, Collections and Topics in MDPI journals
Dr. Dmitri Tcherniak

E-Mail Website
Guest Editor
Brüel & Kjær Sound & Vibration Measurement A/S, Nærum, Denmark
Interests: structural dynamics; signal processing; NVH

Special Issue Information

Dear Colleagues,

Timely detection of damage is critical to ensuring the safe operation of bridges, wind turbines, and civil infrastructures more generally, allowing early warnings to be issued and to avoid significant life, economic, and secondary losses. Moreover, monitoring can provide relevant information for structural management and maintenance. While two dominant competing philosophies for civil Structural Health Monitoring (SHM) have emerged in the last decades (data driven vs. model-based approaches), several aspects are still worthy of investigation, including the selection of effective damage features and their automatic extraction from response measurements as well as sensitivity to environmental and operational factors, the appropriate setting of statistical models and thresholds in data-driven approaches, the role of system identification and model updating for damage assessment, the optimization techniques to use for a reliable solution of the inverse problem, the prediction of the remaining useful life of structures, and the support to decision making.

The goal of this Special Issue is to discuss the latest achievements in the field of data processing procedures for SHM of civil infrastructures, and multidisciplinary contributions are especially encouraged. Potential topics for submissions include but are not limited to:

  • Optimal sensor layout and automated damage feature extraction (including automated modal parameter identification)
  • Influence of environmental and operational variability on SHM reliability and compensation methods
  • Data mining and data fusion approaches for civil SHM
  • Damage feature selection and comparative assessment of damage sensitivity of different damage indexes
  • Approaches for damage detection, location, extension, and classification from response measurements
  • Techniques for robust solution of the inverse problem in model-based SHM techniques
  • Artificial intelligence in civil SHM
  • Comparative assessment of data-driven and model-based SHM approaches in the context of a given damage scenario
  • Residual life prediction
  • Role of SHM in decision making, including early warning, emergency management, and support to structural maintenance in service conditions
Dr. Carlo Rainieri
Dr. Andy Nguyen
Dr. You Dong
Dr. Dmitri Tcherniak
Guest Editors

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. Infrastructures is an international peer-reviewed open access monthly 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 1800 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.

Keywords

  • structural health monitoring
  • influence of environmental factors
  • damage features
  • inverse problems
  • artificial intelligence
  • residual life

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Published Papers (14 papers)

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Research

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19 pages, 6393 KiB  
Article
Simplicial Complex-Enhanced Manifold Embedding of Spatiotemporal Data for Structural Health Monitoring
by Nan Xu, Zhiming Zhang and Yongming Liu
Infrastructures 2023, 8(3), 46; https://doi.org/10.3390/infrastructures8030046 - 5 Mar 2023
Cited by 1 | Viewed by 2152
Abstract
Structural Health Monitoring requires the continuous assessment of a structure’s operational conditions, which involves the collection and analysis of a large amount of data in both spatial and temporal domains. Conventionally, both data-driven and physics-based models for structural damage detection have relied on [...] Read more.
Structural Health Monitoring requires the continuous assessment of a structure’s operational conditions, which involves the collection and analysis of a large amount of data in both spatial and temporal domains. Conventionally, both data-driven and physics-based models for structural damage detection have relied on handcrafted features, which are susceptible to the practitioner’s expertise and experience in feature selection. The limitations of handcrafted features stem from the potential for information loss during the extraction of high-dimensional spatiotemporal data collected from the sensing system. To address this challenge, this paper proposes a novel, automated structural damage detection technique called Simplicial Complex Enhanced Manifold Embedding (SCEME). The key innovation of SCEME is the reduction of dimensions in both the temporal and spatial domains for efficient and information-preserving feature extraction. This is achieved by constructing a simplicial complex for each signal and using the resulting topological invariants as key features in the temporal domain. Subsequently, curvature-enhanced topological manifold embedding is performed for spatial dimension reduction. The proposed methodology effectively represents both intra-series and inter-series correlations in the low-dimensional embeddings, making it useful for classification and visualization. Numerical simulations and two benchmark experimental datasets validate the high accuracy of the proposed method in classifying different damage scenarios and preserving useful information for structural identification. It is especially beneficial for structural damage detection using complex data with high spatial and temporal dimensions and large uncertainties in reality. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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11 pages, 4327 KiB  
Article
Investigating Concrete Properties Using Dielectric Constant from Ground Penetrating Radar Scans
by Jonathan M. Taylor and Isabel M. Morris
Infrastructures 2022, 7(12), 173; https://doi.org/10.3390/infrastructures7120173 - 17 Dec 2022
Cited by 2 | Viewed by 3168
Abstract
Determining the material properties and existing capacity of concrete infrastructure using nondestructive techniques is challenging due to evolving design requirements, unknown as-built conditions, and ongoing maintenance and deterioration. Concrete’s material properties, including density, porosity, and compressive strength, are usually determined by mechanical testing, [...] Read more.
Determining the material properties and existing capacity of concrete infrastructure using nondestructive techniques is challenging due to evolving design requirements, unknown as-built conditions, and ongoing maintenance and deterioration. Concrete’s material properties, including density, porosity, and compressive strength, are usually determined by mechanical testing, but being able to measure these properties noninvasively could aid engineers in maintaining and designing concrete infrastructure. Research into nondestructive methods for determining material properties of concrete has shown relationships between mechanical properties and ground penetrating radar (GPR) properties such as dielectric constant, attenuation, and instantaneous amplitude. We investigated direct relationships between dielectric constant and the density, porosity, and compressive strength of 23 mature concrete samples with varying mix designs using a commercial 1 GHz GPR. In normal-weight concrete, weak trends were seen between a dielectric for compressive strength (R2=0.76) and one for density (R2=0.64), whereas no significant trend was found with porosity (R2=0.52). The GPR unit used provides acceptable data but has limited resolution for analyses and utility. The dielectrics showed distinct clustering by mix type—particularly the inclusion of materials such as blast furnace slag. While demonstrating that the dielectric constant is a candidate for rapid concrete comparisons, there is also a demonstrated need for further investigation of the complex relationships between mechanical and electromagnetic properties in concrete. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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20 pages, 1088 KiB  
Article
The Benefit of Informed Risk-Based Management of Civil Infrastructures
by Pier Francesco Giordano and Maria Pina Limongelli
Infrastructures 2022, 7(12), 165; https://doi.org/10.3390/infrastructures7120165 - 5 Dec 2022
Cited by 4 | Viewed by 1926
Abstract
One of the most interesting applications of Structural Health Monitoring (SHM) is the possibility of providing real-time information on the conditions of civil infrastructures during and following disastrous events, thus supporting decision-makers in prompt emergency operations. The Bayesian decision theory provides a rigorous [...] Read more.
One of the most interesting applications of Structural Health Monitoring (SHM) is the possibility of providing real-time information on the conditions of civil infrastructures during and following disastrous events, thus supporting decision-makers in prompt emergency operations. The Bayesian decision theory provides a rigorous framework to quantify the benefit of SHM through the Value of Information (VoI) accounting for different sources of uncertainties. This decision theory is based on utility considerations, or, in other words, it is based on risk. Instead, decision-making in emergency management is often based on engineering judgment and heuristic approaches. The goal of this paper is to investigate the impact of different decision scenarios on the VoI. To this aim, a general framework to quantify the benefit of SHM information in emergency management is applied to different decision scenarios concerning bridges under scour and seismic hazards. Results indicate that the considered decision scenario might tremendously affect the results of a VoI analysis. Specifically, the benefit of SHM information could be underestimated when considering non-realistic scenarios, e.g., those based on risk-based decision-making, which are not adopted in practice. Besides, SHM information is particularly valuable when it prevents the selection of suboptimal emergency management actions. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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17 pages, 4458 KiB  
Article
Behavior of Half-Joints: Design and Simulation of Laboratory Tests
by Rebecca Asso, Marco Domaneschi, Giuseppe C. Marano, Fabrizio Palmisano and Giuseppe Palombella
Infrastructures 2022, 7(12), 160; https://doi.org/10.3390/infrastructures7120160 - 24 Nov 2022
Cited by 1 | Viewed by 2886
Abstract
European countries are characterized by an extensive infrastructural network, mainly built around the 1960s and 1970s. In that period prefabrication processes were starting to gain ground, and one of the most spread and studied typologies of bridges was constituted by reinforced or prestressed [...] Read more.
European countries are characterized by an extensive infrastructural network, mainly built around the 1960s and 1970s. In that period prefabrication processes were starting to gain ground, and one of the most spread and studied typologies of bridges was constituted by reinforced or prestressed concrete decks. Those structures have gone through years of service, which caused the inevitable degradation of the materials and relevant deterioration of structural elements. Moreover, the design and construction processes of that period have soon become obsolete, and the knowledge relative to the influence of detailing increased significantly. One particular element that has been commonly used has been the half-joint, which is easy to prefabricate and has a strategic impact. However, in recent years this solution is showing critical aptitudes in resisting structural degradation and material decay. In addition, structural health monitoring (SHM) strategies are gaining attention since they are a very useful tool for gathering information on the current state of the structure and then for evaluating intervention plans to improve safety. Indeed, existing bridges, despite their working age, are still crucial to the development and sustainability of community life, and their decommissioning would be an act of critical impact on the communities (e.g., economy, logistics, sustainability). This contribution presents the design and the simulation of laboratory tests on half-joints of reinforced concrete beams that will be developed at the Politecnico di Torino in a subsequent step of the present research. They are designed to test and compare different monitoring techniques along with different steel reinforcement configurations. Specifically, the first part of the manuscript focuses on a review of the literature regarding the design, strengthening, and monitoring of half-joints. Subsequently, the laboratory setup to test half-joints is presented along with the numerical simulation to support the experimental design. Laboratory tests will involve the use of monitoring systems to detect the local response of the system and also to propose new solutions specifically for this type of connection using emerging technologies. Numerical collapse simulations show the effect of different reinforcement configurations and the collapse behavior. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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20 pages, 4020 KiB  
Article
Development of a Cognitive Digital Twin for Pavement Infrastructure Health Monitoring
by Cristobal Sierra, Shuva Paul, Akhlaqur Rahman and Ambarish Kulkarni
Infrastructures 2022, 7(9), 113; https://doi.org/10.3390/infrastructures7090113 - 29 Aug 2022
Cited by 13 | Viewed by 4619
Abstract
A road network is the key foundation of any nation’s critical infrastructure. Pavements represent one of the longest-living structures, having a post-construction life of 20–40 years. Currently, most attempts at maintaining and repairing these structures are performed in a reactive and traditional fashion. [...] Read more.
A road network is the key foundation of any nation’s critical infrastructure. Pavements represent one of the longest-living structures, having a post-construction life of 20–40 years. Currently, most attempts at maintaining and repairing these structures are performed in a reactive and traditional fashion. Recent advances in technology and research have proposed the implementation of costly measures and time-intensive techniques. This research presents a novel automated approach to develop a cognitive twin of a pavement structure by implementing advanced modelling and machine learning techniques from unmanned aerial vehicle (e.g., drone) acquired data. The research established how the twin is initially developed and subsequently capable of detecting current damage on the pavement structure. The proposed method is also compared to the traditional approach of evaluating pavement condition as well as the more advanced method of employing a specialized diagnosis vehicle. This study demonstrated an efficiency enhancement of maintaining pavement infrastructure. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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22 pages, 22705 KiB  
Article
Performance Evaluation of Blind Modal Identification in Large-Scale Civil Infrastructure
by Ali Abasi and Ayan Sadhu
Infrastructures 2022, 7(8), 98; https://doi.org/10.3390/infrastructures7080098 - 22 Jul 2022
Cited by 4 | Viewed by 2615
Abstract
The monitoring and maintenance of existing civil infrastructure has recently received worldwide attention. Several structural health monitoring methods have been developed, including time-, frequency-, and time–frequency domain methods of modal identification and damage detection to estimate the structural and modal parameters of large-scale [...] Read more.
The monitoring and maintenance of existing civil infrastructure has recently received worldwide attention. Several structural health monitoring methods have been developed, including time-, frequency-, and time–frequency domain methods of modal identification and damage detection to estimate the structural and modal parameters of large-scale structures. However, there are several implementation challenges of these modal identification methods, depending on the size of the structures, measurement noise, number of available sensors, and their operational loads. In this paper, two modal identification methods, Second-Order Blind Identification (SOBI) and Time-Varying Filtering Empirical Mode Decomposition (TVF-EMD), are evaluated and compared for large-scale structures including a footbridge and a wind turbine blade with a wide range of dynamic characteristics. The results show that TVF-EMD results in better accuracy in modal identification compared to SOBI for both structures. However, when the number of sensors is equal to or more than the number of target modes of the structure, SOBI results in better computational efficiencies compared to TVF-EMD. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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28 pages, 1997 KiB  
Article
Signal Processing Methodology of Response Data from a Historical Arch Bridge toward Reliable Modal Identification
by Aram Cornaggia, Rosalba Ferrari, Maurizio Zola, Egidio Rizzi and Carmelo Gentile
Infrastructures 2022, 7(5), 74; https://doi.org/10.3390/infrastructures7050074 - 23 May 2022
Cited by 9 | Viewed by 2649
Abstract
The paper is part of a case study concerning the structural assessment of a historical infrastructure in the local territory, a road three-span reinforced concrete arch bridge over a river, built by the end of World War I (1917). The purpose of the [...] Read more.
The paper is part of a case study concerning the structural assessment of a historical infrastructure in the local territory, a road three-span reinforced concrete arch bridge over a river, built by the end of World War I (1917). The purpose of the paper is twofold: first, in-situ acquired response data are systematically analysed by specific signal processing techniques, to form a devoted methodological procedure and to extract useful information toward possible interpretation of the current structural conditions; second, the deciphered information is elaborated, in view of obtaining peculiar conceptualisations of detailed features of the structural response, as meant to achieve quantitative descriptions and modelling, for final Structural Health Monitoring (SHM) and intervention purposes. The proposed methodology, integrating self-implemented and adapted classical signal processing methods, and refined techniques, such as Wavelet analysis and ARMA models, assembles a rather general, systematic methodological approach to signal processing, highlighting the capability to extract useful and fundamental information from acquired response data, also endowed of a non-stationary character, toward final structural interpretation, identification and modelling, thus enabling for developing a reliable and effective SHM platform, on strategic ageing infrastructures. For the present case study, non-stationary characteristics of the response signals are revealed and flattened out, to identify the underlying fundamental frequencies of the infrastructure and to advance particular interpretations of its current structural behaviour, in forming an enlarging structural consciousness of the bridge at hand. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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15 pages, 4490 KiB  
Article
Field-Deployable Fiber Optic Sensor System for Structural Health Monitoring of Steel Girder Highway Bridges
by Renxiang Lu and Johnn Judd
Infrastructures 2022, 7(2), 16; https://doi.org/10.3390/infrastructures7020016 - 26 Jan 2022
Cited by 7 | Viewed by 3343
Abstract
Structural health monitoring of highway bridges is a vital but currently challenging aspect of infrastructure engineering due to the number of sensors required, power requirements, and harsh environmental conditions. The purpose of this study is to develop a structural health monitoring system using [...] Read more.
Structural health monitoring of highway bridges is a vital but currently challenging aspect of infrastructure engineering due to the number of sensors required, power requirements, and harsh environmental conditions. The purpose of this study is to develop a structural health monitoring system using fiber optic sensors based on fiber Bragg gratings that addresses these issues and is field deployable. Prototype systems were installed on two steel girder bridges. The first bridge used sensors adhered to the web and flange. The second bridge used a flange-only array of mechanically mounted sensors. The results demonstrated the accuracy of the fiber Bragg grating sensors and indicated that fewer multiplexed fiber optic cables and loosely routed cables were needed to maintain signal integrity. Adhered sensors were prone to lose their bond due to the curing conditions in the field. The findings suggest that the proposed system may be best used in a hybrid deployment, where a diagnostic field test with conventional sensors is used to determine the baseline bridge response and fiber optic sensors are periodically installed for short-term monitoring. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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22 pages, 3402 KiB  
Article
Comparative Assessment of Criticality Indices Extracted from Acoustic and Electrical Signals Detected in Marble Specimens
by Stavros K. Kourkoulis, Ermioni D. Pasiou, Andronikos Loukidis, Ilias Stavrakas and Dimos Triantis
Infrastructures 2022, 7(2), 15; https://doi.org/10.3390/infrastructures7020015 - 24 Jan 2022
Cited by 21 | Viewed by 2885
Abstract
The quantitative determination of the current load carrying capability of already loaded structural elements and the possibility to detect proper indices that could be considered as signals for timely warning that the load carrying capacity is exhausted is the subject of this study. [...] Read more.
The quantitative determination of the current load carrying capability of already loaded structural elements and the possibility to detect proper indices that could be considered as signals for timely warning that the load carrying capacity is exhausted is the subject of this study. More specifically, it aims to explore the possibility of detecting signals that can be considered as indices warning about upcoming fracture and then to compare quantitatively such signals provided by different techniques. The novelty of the present study lies exactly in this quantitative comparison of the pre-failure signals provided by various sensing techniques and various methods of analysis of the experimental data. To achieve this target, advantage is taken of data concerning the acoustic and electrical activities produced while marble specimens are subjected to mechanical loading. The respective signals are detected and recorded by means of the acoustic emissions technique and that of the pressure stimulated currents. The signals detected by the acoustic emissions technique are analyzed in terms of three formulations, i.e., the b-value, the F-function and the parameters variance κ1, entropy S and entropy under time reversal S_ according to the natural time analysis. The signals detected by the pressure stimulated currents technique are analyzed by means of the intensity of the electric current recorded. The study indicates that all quantities considered provide promising pre-failure indicators. Furthermore, when the specimen is subjected to near-to-failure load levels, the temporal evolution of three of the quantities studied (b-value, F-function, pressure stimulated currents) is governed by a specific power law. The onset of validity of this law designates some differentiation of the damage mechanisms activated. Quantitative differences are observed between the time instants at which this power law starts dictating the evolution of the above parameters, indicating the imperative need for further investigation, despite the quite encouraging results of the present study. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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24 pages, 5785 KiB  
Article
Designing a Structural Health Monitoring System Accounting for Temperature Compensation
by Valeria Francesca Caspani, Daniel Tonelli, Francesca Poli and Daniele Zonta
Infrastructures 2022, 7(1), 5; https://doi.org/10.3390/infrastructures7010005 - 30 Dec 2021
Cited by 17 | Viewed by 3451
Abstract
Structural health monitoring is effective if it allows us to identify the condition state of a structure with an appropriate level of confidence. The estimation of the uncertainty of the condition state is relatively straightforward a posteriori, i.e., when monitoring data are available. [...] Read more.
Structural health monitoring is effective if it allows us to identify the condition state of a structure with an appropriate level of confidence. The estimation of the uncertainty of the condition state is relatively straightforward a posteriori, i.e., when monitoring data are available. However, monitoring observations are not available when designing a monitoring system; therefore, the expected uncertainty must be estimated beforehand. This paper proposes a framework to evaluate the effectiveness of a monitoring system accounting for temperature compensation. This method is applied to the design process of a structural health monitoring system for civil infrastructure. In particular, the focus is on the condition-state parameters representing the structural long-term response trend, e.g., due to creep and shrinkage effects, and the tension losses in prestressed concrete bridges. The result is a simple-to-use equation that estimates the expected uncertainty of a long-term response trend of temperature-compensated response measurements in the design phase. The equation shows that the condition-state uncertainty is affected by the measurement and model uncertainties, the start date and duration of the monitoring activity, and the sampling frequency. We validated our approach on a real-life case study: the Colle Isarco viaduct. We verified whether the pre-posterior estimation of expected uncertainty, performed with the experimented approach, is consistent with the real uncertainty estimated a posteriori based on the monitoring data. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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16 pages, 2846 KiB  
Article
Modification of Variance-Based Sensitivity Indices for Stochastic Evaluation of Monitoring Measures
by David Sanio, Mark Alexander Ahrens and Peter Mark
Infrastructures 2021, 6(11), 149; https://doi.org/10.3390/infrastructures6110149 - 23 Oct 2021
Viewed by 1929
Abstract
In complex engineering models, various uncertain parameters affect the computational results. Most of them can only be estimated or assumed quite generally. In such a context, measurements are interesting to determine the most decisive parameters accurately. While measurements can reduce parameters’ variance, structural [...] Read more.
In complex engineering models, various uncertain parameters affect the computational results. Most of them can only be estimated or assumed quite generally. In such a context, measurements are interesting to determine the most decisive parameters accurately. While measurements can reduce parameters’ variance, structural monitoring might improve general assumptions on distributions and their characteristics. The decision on variables being measured often relies on experts’ practical experience. This paper introduces a method to stochastically estimate the potential benefits of measurements by modified sensitivity indices. They extend the established variance-based sensitivity indices originally suggested by Sobol’. They do not quantify the importance of a variable but the importance of its variance reduction. The numerical computation is presented and exemplified on a reference structure, a 50-year-old pre-stressed concrete bridge in Germany, where the prediction of the fatigue lifetime of the pre-stressing steel is of concern. Sensitivity evaluation yields six important parameters (e.g., shape of the S–N curve, temperature loads, creep, and shrinkage). However, taking into account individual monitoring measures and suited measurements identified by the modified sensitivity indices, creep and shrinkage, temperature loads, and the residual pre-strain of the tendons turn out to be most efficient. They grant the highest gains of accuracy with respect to the lifetime prediction. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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14 pages, 756 KiB  
Article
Aspects of Vibration-Based Methods for the Prestressing Estimate in Concrete Beams with Internal Bonded or Unbonded Tendons
by Angelo Aloisio
Infrastructures 2021, 6(6), 83; https://doi.org/10.3390/infrastructures6060083 - 2 Jun 2021
Cited by 6 | Viewed by 3369
Abstract
The estimate of internal prestressing in concrete beams is essential for the assessment of their structural reliability. Many scholars have tackled multiple and diverse methods to estimate the measurable effects of prestressing. Among them, many experimented with dynamics-based techniques; however, these clash with [...] Read more.
The estimate of internal prestressing in concrete beams is essential for the assessment of their structural reliability. Many scholars have tackled multiple and diverse methods to estimate the measurable effects of prestressing. Among them, many experimented with dynamics-based techniques; however, these clash with the theoretical independence of the natural frequencies of the forces of internally prestressed beams. This paper examines the feasibility of a hybrid approach based on dynamic identification and the knowledge of the elastic modulus. Specifically, the author considered the effect of the axial deformation on the beam length and the weight per unit of volume. It is questioned whether the uncertainties related to the estimate of the elastic modulus and the first natural frequency yield reasonable estimates of the internal prestressing. The experimental testing of a set of full-scale concrete girders with known design prestressing supports a discussion about its practicability. The author found that the uncertainty in estimating the natural frequencies and elastic modulus significantly undermines a reliable estimate of the prestressing state. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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17 pages, 1790 KiB  
Article
The Way Forward for Indirect Structural Health Monitoring (iSHM) Using Connected and Automated Vehicles in Europe
by Konstantinos Gkoumas, Kyriaki Gkoktsi, Flavio Bono, Maria Cristina Galassi and Daniel Tirelli
Infrastructures 2021, 6(3), 43; https://doi.org/10.3390/infrastructures6030043 - 13 Mar 2021
Cited by 23 | Viewed by 4012
Abstract
Europe’s aging transportation infrastructure requires optimized maintenance programs. However, data and monitoring systems may not be readily available to support strategic decisions or they may require costly installations in terms of time and labor requirements. In recent years, the possibility of monitoring bridges [...] Read more.
Europe’s aging transportation infrastructure requires optimized maintenance programs. However, data and monitoring systems may not be readily available to support strategic decisions or they may require costly installations in terms of time and labor requirements. In recent years, the possibility of monitoring bridges by indirectly sensing relevant parameters from traveling vehicles has emerged—an approach that would allow for the elimination of the costly installation of sensors and monitoring campaigns. The advantages of cooperative, connected, and automated mobility (CCAM), which is expected to become a reality in Europe towards the end of this decade, should therefore be considered for the future development of iSHM strategies. A critical review of methods and strategies for CCAM, including Intelligent Transportation Systems, is a prerequisite for moving towards the goal of identifying the synergies between CCAM and civil infrastructures, in line with future developments in vehicle automation. This study presents the policy framework of CCAM in Europe and discusses the policy enablers and bottlenecks of using CCAM in the drive-by monitoring of transport infrastructure. It also highlights the current direction of research within the iSHM paradigm towards the identification of technologies and methods that could benefit from the use of connected and automated vehicles (CAVs). Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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Review

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30 pages, 4193 KiB  
Review
Latest Advances in Finite Element Modelling and Model Updating of Cable-Stayed Bridges
by Thomas Sharry, Hong Guan, Andy Nguyen, Erwin Oh and Nam Hoang
Infrastructures 2022, 7(1), 8; https://doi.org/10.3390/infrastructures7010008 - 5 Jan 2022
Cited by 16 | Viewed by 5516
Abstract
As important links in the transport infrastructure system, cable-stayed bridges are among the most popular candidates for implementing structural health monitoring (SHM) technology. The primary aim of SHM for these bridges is to ensure their structural integrity and satisfactory performance by monitoring their [...] Read more.
As important links in the transport infrastructure system, cable-stayed bridges are among the most popular candidates for implementing structural health monitoring (SHM) technology. The primary aim of SHM for these bridges is to ensure their structural integrity and satisfactory performance by monitoring their behaviour over time. Finite element (FE) model updating is a well-recognised approach for SHM purposes, as an accurate model serves as a baseline reference for damage detection and long-term monitoring efforts. One of the many challenges is the development of the initial FE model that can accurately reflect the dynamic characteristics and the overall behaviour of a bridge. Given the size, slenderness, use of long cables, and high levels of structural redundancy, precise initial models of long-span cable-stayed bridges are desirable to better facilitate the model updating process and to improve the accuracy of the final updated model. To date, very few studies offer in-depth discussions on the modelling approaches for cable-stayed bridges and the methods used for model updating. As such, this article presents the latest advances in finite element modelling and model updating methods that have been widely adopted for cable-stayed bridges, through a critical literature review of existing research work. An overview of current SHM research is presented first, followed by a comprehensive review of finite element modelling of cable-stayed bridges, including modelling approaches of the deck girder and cables. A general overview of model updating methods is then given before reviewing the model updating applications to cable-stayed bridges. Finally, an evaluation of all available methods and assessment for future research outlook are presented to summarise the research achievements and current limitations in this field. Full article
(This article belongs to the Special Issue Structural Health Monitoring of Civil Infrastructures)
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