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Infrastructures
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Advanced Technologies in Data Collection, Evaluation, and Visualization of Reinforced...
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Advanced Technologies in Data Collection, Evaluation, and Visualization of Reinforced Concrete Structures

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

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 5788

Special Issue Editors

Dr. Kien Dinh

E-Mail Website
Guest Editor
1. Civil Engineering Department, Embry-Riddle Aeronautical University, Daytona Beach, FL, USA
2. NDT Concrete LLC, Deltona, FL, USA
Interests: ground-penetrating radar (GPR); ultrasonic tomography; concrete inspection; concrete imaging; nondestructive testing/evaluation (NDT/NDE); structural health monitoring (SHM)
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Nenad Gucunski

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, Rutgers, The State of University of New Jersey, Piscataway, NJ 08854, USA
Interests: seismic methods and nondestructive evaluation (NDE) techniques; dynamic soil structure Interaction; numerical Modeling

Special Issue Information

Dear Colleagues,

The use of advanced sensing technologies and robotic data collection has recently become a trend in concrete inspection. As an example, drones have been used by researchers and engineers all over the world to inspect large concrete structures such as high-rise buildings, dams, and bridges. As another example, robotic systems have been developed to carry sensors for bridge deck and tunnel inspection. Other than those hardware related developments, many significant innovations have also been made in terms of algorithms to interpret and analyze the data collected by existing or new sensors. For instance, machine learning and artificial intelligence have been used to automate the analysis of sensing/imaging data, and augmented reality has been applied to bridge inspection. That being said, MDPI’s Infrastructures Journal has proposed and organized this Special Issue to assemble the latest studies in this area. Specifically, it aims to publish study results and research papers that present advanced technologies in the data collection, evaluation, and visualization of reinforced concrete structures. In addition, it also encourages papers that provide a comprehensive review of the literature on this topic.

Dr. Kien Dinh
Prof. Dr. Nenad Gucunski
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

  • reinforced concrete structures
  • robotic/automated data collection
  • non-destructive evaluation
  • structural health monitoring
  • automated data analysis
  • machine learning
  • artificial intelligence

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Published Papers (2 papers)

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Research

21 pages, 6053 KiB  
Article
A Large-Crack Image-Stitching Method with Cracks as the Regions of Interest
by Szu-Pyng Kao, Jhih-Sian Lin, Feng-Liang Wang and Pen-Shan Hung
Infrastructures 2024, 9(4), 74; https://doi.org/10.3390/infrastructures9040074 - 16 Apr 2024
Viewed by 1891
Abstract
While crack detection is crucial for maintaining concrete structures, existing methods often overlook the analysis of large cracks that span multiple images. Such analyses typically rely on image stitching to create a complete image of a crack. Current stitching methods are not only [...] Read more.
While crack detection is crucial for maintaining concrete structures, existing methods often overlook the analysis of large cracks that span multiple images. Such analyses typically rely on image stitching to create a complete image of a crack. Current stitching methods are not only computationally demanding but also require manual adjustments; thus, a fast and reliable solution is still lacking. To address these challenges, we introduce a stitching method that leverages the advantages of crack image-segmentation models. This method first utilizes the Mask R-CNN model for the identification of crack regions as regions of interest (ROIs) within images. These regions are then used to calculate keypoints of the scale-invariant feature transform (SIFT), and descriptors for these keypoints are computed with the original images for image matching and stitching. Compared with traditional methods, our approach significantly reduces the computational time; by 98.6% in comparison to the Brute Force (BF) matcher, and by 58.7% with respect to the Fast Library for Approximate Nearest Neighbors (FLANN) matcher. Our stitching results on images with different degrees of overlap or changes in shooting posture show superior structural similarity index (SSIM) values, demonstrating excellent detail-matching performance. Moreover, the ability to measure complete crack images is indicated by the relative error of 7%, which is significantly better than that of traditional methods. Full article
(This article belongs to the Special Issue Advanced Technologies in Data Collection, Evaluation, and Visualization of Reinforced Concrete Structures)
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22 pages, 15879 KiB  
Article
Imaging Concrete Structures with Ultrasonic Shear Waves—Technology Development and Demonstration of Capabilities
by Kien Dinh, Khiem Tran, Nenad Gucunski, Christopher C. Ferraro and Tu Nguyen
Infrastructures 2023, 8(3), 53; https://doi.org/10.3390/infrastructures8030053 - 14 Mar 2023
Cited by 8 | Viewed by 3114
Abstract
Since 1987 when dry-point-contact (DPC) transducers were invented in the USSR, ultrasonic shear wave devices based on those transducers have been commercialized and have become one of the most effective technologies for imaging concrete. That said, the objectives of this paper are (1) [...] Read more.
Since 1987 when dry-point-contact (DPC) transducers were invented in the USSR, ultrasonic shear wave devices based on those transducers have been commercialized and have become one of the most effective technologies for imaging concrete. That said, the objectives of this paper are (1) to provide a brief review of the historical development of these powerful devices and (2) to provide a comprehensive assessment of their capabilities in imaging internal entities and structural defects. Regarding the former, the paper presents the context that gave birth to DPC technology and different generations of ultrasonic shear wave devices for concrete inspection. For the latter, one of the state-of-the-art ultrasonic shear wave devices (MIRA 3D) was used to collect data on concrete specimens with different built-in flaws/defects. Those data are then visualized with a commonly used data processing algorithm, the so-called synthetic aperture focusing technique (SAFT). Finally, based on the resulting images, the capabilities of the device are discussed in detail for each concrete imaging problem. A main limitation of ultrasonic shear wave technique for concrete inspection is that it requires a significant amount of time and effort for data collection. Full article
(This article belongs to the Special Issue Advanced Technologies in Data Collection, Evaluation, and Visualization of Reinforced Concrete Structures)
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