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Structural Health Monitoring and Sustainable Built Structures

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (30 March 2023) | Viewed by 13326

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Special Issue Editors

Prof. Dr. Abhijit Mukherjee

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Guest Editor

School of Civil and Mechanical Engineering, Curtin University, Bentley, WA 6102, Australia
Interests: structural health monitoring; lifecycle analysis; non-destructive testing; signal processing; self-healing self-sensing materials

Dr. Subhra Majhi

E-Mail Website
Guest Editor

School of Civil and Mechanical Engineering, Curtin University, Bentley, WA 6102, Australia
Interests: structural health monitoring; non-destructive testing; sensors; signal processing

Special Issue Information

Dear Colleagues,

It is our pleasure to announce a new Special Issue “Structural Health Monitoring for Sustainable Built Structures” of the journal Sustainability.

If construction industry were a country, it would be the third-largest emitter of CO₂ behind China and the United States. Emission from this industry is significant at all stages—construction, operation, and demolition. For effective management of the lifecycle of built facilities, reliable yet economical health monitoring is imperative. This Special Issue will report recent advances in structural health monitoring for sustainable built structures. It will unite disparate research outcomes in non-destructive testing, sensing technologies, signal processing, and lifecycle management towards the goal of sustainable built structures.

The Special Issue invites contributions, including, but not limited to, the following detailed topics:

Structural health monitoring;
Vibration-based structural deterioration models;
Wave propagation for condition monitoring;
Electrochemical techniques for condition monitoring;
Sensing technologies and signal analysis for built structures;
Data-driven IoT based condition monitoring;
Field application and case studies;
Numerical models and model updating techniques;
Self-healing and self-sensing structural system;
Life cycle assessment of built structures;
SHM-based sustainability assessment.

Prof. Dr. Abhijit Mukherjee
Dr. Subhra Majhi
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. Sustainability 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 2400 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

non-destructive evaluation
structural health monitoring
sensors and sensing
numerical models
self-healing self-sensing materials
sustainable construction materials

Published Papers (5 papers)

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Research

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23 pages, 13171 KiB

Open AccessArticle

Accurate Detection of Concrete Pavement Thickness Based on Ultrasonic Array

by Yu Tian, Jinyu Wu, Shifu Liu, Jianming Ling, Yaqi Zheng, Xindong Zhao and Le Liu

Sustainability 2023, 15(10), 8228; https://doi.org/10.3390/su15108228 - 18 May 2023

Viewed by 1058

Abstract

Thickness detection of concrete pavement is a critical step in construction completion acceptance and serves as an important metric for subsequent pavement performance evaluations. The crux of thickness evaluation lies in determining the interface reflection echo propagation sound time. Based on the acoustic impedance difference between the surface layer and contact layer, pavement can be classified into two types: large-difference and small-difference. By examining the singularity of the detection signal, we employed the improved correlation coefficient method and the wavelet transform maximum value method to identify the interface reflection echo sound time. This study refines the traditional correlation coefficient method by using the surface direct wave as the reference signal, simplifying the signal analysis process. In actual detection, for the type of concrete pavement with large differences in acoustic impedance, the average relative error between the improved correlation coefficient method and the core drilling method can be reduced to 1.7%; for the type with small differences, the average relative error of the detection results obtained using the wavelet transform modulus maximum method can be reduced to 1.9%, showcasing high accuracy. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Sustainable Built Structures)

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24 pages, 14225 KiB

Open AccessArticle

Classification of Corrosion Severity in Concrete Structures Using Ultrasonic Imaging and Linear Discriminant Analysis

by Prasanna Kumar Mayakuntla, Debdutta Ghosh and Abhijit Ganguli

Sustainability 2022, 14(23), 15768; https://doi.org/10.3390/su142315768 - 27 Nov 2022

Cited by 1 | Viewed by 1402

Abstract

The deterioration of concrete structures due to rebar corrosion is a key issue affecting the safety and service life of civil infrastructure. Reinforced concrete (RC) structures in coastal areas are subjected to harsh environmental conditions that cause rebar corrosion. From the perspective of safety, repair, and structural rehabilitation, it is essential to ascertain the level of corrosion severity and associated damage in RC structures through non-destructive evaluation (NDE) techniques. In this study, the potential of pattern recognition techniques for ascertaining the severity damage at various stages of rebar corrosion in concrete samples was explored. A contact ultrasonic compressional wave transducer pair with 250 kHz centre frequency was used as source and reflected signals from the rebar were acquired using a tied-together scanning approach. To expedite the corrosion process in the laboratory, accelerated corrosion of the embedded rebar was employed. The synthetic aperture focusing technique (SAFT) was applied to reconstruct the image of the concrete subsurface from the acquired B-scans. Two approaches, i.e., the Mahalanobis distance (MD) and linear discriminant analysis (LDA), were adopted; both methods correctly classified the level of corrosion severity and damage to the concrete. The developed pattern recognition techniques can, therefore, be potential tools for generating important information towards economical and timely repair of damaged concrete structures affected by rebar corrosion. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Sustainable Built Structures)

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21 pages, 6586 KiB

Open AccessArticle

Using Computer Vision for Monitoring the Quality of 3D-Printed Concrete Structures

by Shanmugaraj Senthilnathan and Benny Raphael

Sustainability 2022, 14(23), 15682; https://doi.org/10.3390/su142315682 - 25 Nov 2022

Cited by 8 | Viewed by 2588

Abstract

Concrete 3D printing has the potential to reduce material and process waste in construction. Thus, it contributes to making the construction industry more sustainable through the use of digital-fabrication technologies. While concrete 3D printing is attractive due to its potential to realize complex designs, practical challenges include an increased chance of defects and deformities. Quality assessment of 3D-printed elements is essential for large-scale implementation. Workability of concrete is known to decrease with printing time and it impacts extrudability. It is usually visible in 3D-printed elements, with the lower layers having a smooth finish, while the top layers have cracks and discontinuities. A computer-vision-based quality assessment method is proposed in this paper using a two-bin Linear Binary Pattern textural analysis. Information entropy is used as the metric for measuring the texture variation within each layer and its changes over the layers are studied. A higher entropy value is found for layers having deformities. Finally, through the error-minimization technique, a threshold entropy value is calculated and, using this, the printed layers can be assessed and corrective actions taken. This paper contributes to developing a non-intrusive quality assessment technique for concrete 3D-printed elements. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Sustainable Built Structures)

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23 pages, 4681 KiB

Open AccessArticle

Multimodal Monitoring of Corrosion in Reinforced Concrete for Effective Lifecycle Management of Built Facilities

by Subhra Majhi, Leonarf Kevin Asilo, Abhijit Mukherjee, Nithin V. George and Brian Uy

Sustainability 2022, 14(15), 9696; https://doi.org/10.3390/su14159696 - 6 Aug 2022

Viewed by 1570

Abstract

Monitoring the corrosion of steel rebars is paramount to ensuring the safety and serviceability of reinforced concrete (RC) structures. Conventional electro-chemical techniques can provide an overall estimate of the extent of corrosion. However, a detailed account of the extent of corrosion would help in understanding the residual strength of corroding RC structures. A passive wave-based technique such as acoustic emissions can identify the location of corrosion but always requires the presence of transducers on the structure. In active wave-based techniques, the structure is excited through a pulse excitation and their subsequent response to this excitation is measured. Thus, for active techniques, the transducers need not always be present in the structure. In guided wave ultrasonics, the excitation pulse is imparted through a waveguide to determine the state of corrosion. This technique relies on parameters such as time of flight or attenuation of the incident signal to predict the state of corrosion. These parameters can be susceptible to uncertainties in the transducer of ultrasonic coupling. In the present study, concrete specimens with embedded steel bars have been subjected to accelerated corrosion. They have been monitored with a combination of active and passive techniques. The received signals are analyzed through a modified S-Transform-based time-frequency approach to obtain a range of modes that propagate through the specimen. The changes in the modal composition of the guided wave signals due to corrosion are parameterized and correlated to various stages of corrosion. A holistic understanding of the stages of corrosion is developed by the inclusion of acoustic emission hits to guided wave parameters. Based on the Guided Wave Ultrasonics and acoustic emission parameters, corrosion has been classified into Initiation, Intermediate, and Advanced. Subsequently, destructive tests have been performed to measure the residual strength of the corroded bars. Thus, this paper presents a novel proof of concept study for monitoring corrosion with Guided Wave Ultrasonics and acoustic emissions. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Sustainable Built Structures)

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Review

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24 pages, 2629 KiB

Open AccessReview

An In-Depth Survey Demystifying the Internet of Things (IoT) in the Construction Industry: Unfolding New Dimensions

by Kiran Khurshid, Aamar Danish, Muhammad Usama Salim, Muhammed Bayram, Togay Ozbakkaloglu and Mohammad Ali Mosaberpanah

Sustainability 2023, 15(2), 1275; https://doi.org/10.3390/su15021275 - 10 Jan 2023

Cited by 15 | Viewed by 5919

Abstract

In this digital era, many industries have widely adopted the Internet of Things (IoT), yet its implementation in the construction industry is relatively limited. Integration of Construction 4.0 drivers, such as business information modeling (BIM), procurement, construction safety, and structural health monitoring (SHM), with IoT devices, provides an effective framework for applications to enhance construction and operational efficiencies. IoT and Construction 4.0 driver integration research, however, is still in its infancy. It is necessary to understand the present state of IoT adoption in the Construction 4.0 context. This paper presented a comprehensive review to identify the IoT adoption status in the Construction 4.0 areas. Furthermore, this work highlighted the potential roadblocks to IoT’s seamless adoption that are unique to the areas of Construction 4.0 in developing countries. Altogether, 257 research articles were reviewed to present the current state of IoT adoption in developed and developing countries, as well as the topmost barriers encountered in integrating IoT with the key Construction 4.0 drivers. This study aimed to provide a reference for construction managers to observe challenges, professionals to explore the hybridization possibilities of IoT in the context of Construction 4.0, and laymen to understand the high-level scientific research that underpins IoT in the construction industry. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Sustainable Built Structures)

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