Special Issue "Non-destructive Testing and Evaluation for Civil Infrastructures"

A special issue of Infrastructures (ISSN 2412-3811).

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 3572

Special Issue Editors

Dr. Alireza Joshaghani
E-Mail
Guest Editor
Texas A and M University, College Station, TX, USA
Interests: concrete Pavement; non destructive tests; slag paste
Dr. Sattar Dorafshan
E-Mail Website
Guest Editor
Department of Civil Engineering, University of North Dakota, Grand Forks, ND, USA
Interests: non-destructive testing; construction; crack detection in concrete
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Special Issue Information

Dear Colleagues,

A comprehensive structural condition assessment and structural safety of civil infrastructure (bridges, roads, buildings, etc.) is not possible without evaluating the material properties (steel, concrete, timer, masonry, etc.) and detecting surface and subsurface defects. Nondestructive evaluation and testing (NDE and T) methods such as impact echo, ground penetrating radar, ultrasonic surface waves, infrared thermography, etc. have been used for this task for the past half century. Despite decades of effort for NDE and T implementation in structural engineering, though, their applications are still somewhat limited, since the raw data associated with these techniques require user expertise. Introducing automation to NDE and T data analysis could alleviate this issue and would pave the way for more popular implementations of the NDE and T techniques in future. Using artificial intelligence and signal and image processing, especially deep learning models, has shown substantial advantages over traditional data analysis; however, they are either relatively new to the practice or are completely untested for NDE and T techniques. This issue could be associated to the lack of available and reliable ground truth. The editor invites the civil and structural engineering community (researchers, engineers, NDE and T manufacturers, and users) to submit their solutions to the aforementioned issues. The scope of this Special Issue includes but is not limited to the followings:

  • Data papers: Introducing and sharing annotated NDE and T datasets (with reliable ground truth);
  • Technical papers: Implementing of artificial intelligence for NDE and T data analysis;
  • Technical papers: Decision making using data fusion techniques for two or more NDE and T methods;
  • Technical papers: Data augmentation techniques to generate realistic NDE and T data for deep learning implementation;
  • Review papers: History of using artificial intelligence for NDE and T techniques, challenges, and potentials.

Dr. Alireza Joshaghani
Dr. Sattar Dorafshan
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 1600 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

  • Ground-penetrating radar (GPR)
  • Impact echo (IE)
  • Ultrasonic surface waves (USW)
  • Infrared thermography (IRT)
  • Signal processing
  • Image processing
  • Deep learning
  • Ground truth
  • NDE
  • NDT

Published Papers (2 papers)

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Research

Article
Bridge Inspection and Defect Recognition with Using Impact Echo Data, Probability, and Naive Bayes Classifiers
Infrastructures 2021, 6(9), 132; https://doi.org/10.3390/infrastructures6090132 - 14 Sep 2021
Cited by 1 | Viewed by 1049
Abstract
Interpretation of IE data have been carried out by analyzing IE signals in frequency domain to determine the maximum frequency. However, the current peak frequency method can be inaccurate. The purpose of this research is to introduce features in IE signals that can [...] Read more.
Interpretation of IE data have been carried out by analyzing IE signals in frequency domain to determine the maximum frequency. However, the current peak frequency method can be inaccurate. The purpose of this research is to introduce features in IE signals that can be used for effective classification and interpretation for bridge deck evaluation through statistical analysis and Naive Bayes classifiers. The dataset contained IE data collected from eight slabs created at Advanced Sensing Technology FAST NDE laboratory (FHWA). A set of statistical features in time domain, normalized peak values, and length of preprocessed signals were used to classify the IE data, statistically. Then, Naive Bayes classifiers was employed to recognize defect area. Finally, the result of statistical classification was compared with frequency approach. The result shows that 19 and 21% of the IE signals collected from the defect area have multiple peaks, respectively. However, 85% of the IE signals collected from the sound set had only one peak. A probability classifier was used to find the relationship between the result of the frequency method and statistical analysis. The result shows that 10% of the IE signals were usable for estimating the thickness in the sound group. Full article
(This article belongs to the Special Issue Non-destructive Testing and Evaluation for Civil Infrastructures)
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Article
A Novel Structural Health Monitoring Method for Reinforced Concrete Bridge Decks Using Ultrasonic Guided Waves
Infrastructures 2020, 5(6), 49; https://doi.org/10.3390/infrastructures5060049 - 17 Jun 2020
Cited by 5 | Viewed by 1786
Abstract
This article presents the latest improvements in a recently developed nondestructive testing (NDT) approach for early detection of various flaws (corrosion, delamination, and concrete cracking) in reinforced concrete (RC) bridge decks. The proposed method involves the use of internal steel reinforcement as a [...] Read more.
This article presents the latest improvements in a recently developed nondestructive testing (NDT) approach for early detection of various flaws (corrosion, delamination, and concrete cracking) in reinforced concrete (RC) bridge decks. The proposed method involves the use of internal steel reinforcement as a wave guide for transmitting ultrasonic waves through the system and the measurement of leaked energy from the surface of the concrete. This paper builds upon the progress made in the previously published phases of the project and aims to further explore the capabilities and practicality of the proposed NDT method. Specifically, the limits of propagation distance, effect of bidirectional reinforcement, methods of attachment and coupling of the sensors to the reinforcement and concrete, and suggestions for optimal sensor arrays are discussed in this paper based on the findings from the most recent laboratory tests and pilot field tests. The results show that with careful placement of sensors and data interpretation, early stages of localized corrosion and delamination can be detected, even when bidirectional and multiple layers of reinforcement are present. For field applications, an angled seat made of fast-setting Hydrocal gypsum cement is recommended, and it is projected that the optimal angle of attachment is 33 degrees or less from the vertical axis. Full article
(This article belongs to the Special Issue Non-destructive Testing and Evaluation for Civil Infrastructures)
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