Special Issue "Structural Sensing and Sustainable Infrastructure Maintenance"

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

Deadline for manuscript submissions: 29 December 2021.

Special Issue Editor

Prof. Dr. Fernando Moreu
E-Mail Website
Guest Editor
Department of Civil, Construction and Environmental Engineering, University of New MexicoAlbuquerque, NM 87131-1070, USA
Interests: structural dynamics; structural health monitoring

Special Issue Information

Dear Colleagues,

Structural health monitoring (SHM) has been receiving significant attention in the community as a means to quantify the different levels of performance and safety of structural systems. One popular application and challenge of SHM systems is to enable collecting data of interest for designers, managers, and decision makers. More specifically, the collection of data from structural sensing that can inform prioritization on maintenance decisions has been proven to be of highest value to decision makers. The value of structural sensing to transform decisions is in general not known and has not been documented to date, given limitations on specific data that correlate structural sensing with infrastructure maintenance. If structural sensing were connected to sustainability of infrastructure and maintenance operations, owners would save costs, prioritize location of investments for maintenance, and make better-informed decisions on how to manage their infrastructure from a data-informed perspective using structural sensing.

The implementation of structural sensing monitoring could become practical and valuable for owners if the community could learn more from real-world applications and correlation between structural sensing and infrastructure maintenance. This Special Issue is directed toward the collection of specific implementations of structural sensing in the context of sustainable infrastructure maintenance, with an emphasis on the following topics:

  • Cost-effective structural sensing that can inform sustainable infrastructure maintenance;
  • Case studies relating field structural sensing with maintenance decisions;
  • Correlation between sensing development and structural information with sustainable infrastructure maintenance;
  • Structural sensing and maintenance prioritization based on field monitoring;
  • New cost-effective sensors that can save infrastructure maintenance operations;
  • Comparisons and evidence of field monitoring of structural sensing and saving of infrastructure maintenance and management;
  • New sensing monitoring approaches that can save costs and increase decisions;
  • New theories related to infrastructure management, sensor development, and sustainable infrastructure maintenance;
  • Structural sensing developments related to inspection and infrastructure maintenance;
  • New technologies that relate structural sensing to human decisions related to maintenance in the field, such as Augmented Reality and other human–infrastructure interfaces;
  • Other related structural sensing areas related to maintenance decisions.

The top priority of this Special Issue is to provide the community with information on past success in structural sensing and infrastructure maintenance with new laboratory and experiment evidence that can contribute to the community of SHM, structural sensors, and structural management.

Prof. Dr. Fernando Moreu
Guest Editor

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 papers will be 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 1900 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

Article
Cost-Effective Inspection of Rebar Spacing and Clearance Using RGB-D Sensors
Sustainability 2021, 13(22), 12509; https://doi.org/10.3390/su132212509 - 12 Nov 2021
Viewed by 233
Abstract
The quality assurance of constructing reinforced concrete (RC) structures in compliance with their design plays a key role in the durability, serviceability, and sustainability of the built RC elements. One area of concern in the quality control of constructing RC structures is examining [...] Read more.
The quality assurance of constructing reinforced concrete (RC) structures in compliance with their design plays a key role in the durability, serviceability, and sustainability of the built RC elements. One area of concern in the quality control of constructing RC structures is examining the position and dimension of the rebars before pouring fresh concrete. Currently, this is accomplished by visual inspection and individually by hand with limited time available between construction stages. Over the past decades, structural health and monitoring during the construction period has applied remote sensing technologies. However, little research has focused on the use of such technologies to inspect and evaluate rebar placement prior to concrete pouring as quality control. In this study we develop an algorithm that facilitates inspecting the positions of rebars and the cover of concrete using a new-generation low-cost RGB-D sensor to find incorrect rebar placement. The proposed method is evaluated using a typical 5 × 5 two-layer rebar cage in the laboratory by comparing the proposed technique with traditional inspection methods. The results show that the RGB-D sensor can achieve cost-effective inspection for rebar spacing and clearance with an acceptable tolerance. The evaluation of rebar spacing results shows that the maximum standard deviation for rebar spacing is 0.34 inch (8.64 mm) between longitudinal rebar 2 and 3, which is the same as the rebar construction and traditional tape measurement results. The concrete cover estimation results show that the maximum standard deviation for rebar cage concrete cover is 0.19 inch (4.83 mm) for longitudinal rebar 3. The issues of new RGB-D sensor scan settings and the test results will be helpful for practitioners in improving construction quality. Full article
(This article belongs to the Special Issue Structural Sensing and Sustainable Infrastructure Maintenance)
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Article
A Roadmap for Sustainable Smart Track—Wireless Continuous Monitoring of Railway Track Condition
Sustainability 2021, 13(13), 7456; https://doi.org/10.3390/su13137456 - 03 Jul 2021
Cited by 1 | Viewed by 687
Abstract
Ensuring safe train operation, minimizing service interruptions, and optimizing maintenance procedures are primary railway industry focus areas. To support these goals, a multi-disciplinary team of researchers at the University of Illinois at Urbana-Champaign proposed a wireless, continuous, and accurate methodology to monitor track [...] Read more.
Ensuring safe train operation, minimizing service interruptions, and optimizing maintenance procedures are primary railway industry focus areas. To support these goals, a multi-disciplinary team of researchers at the University of Illinois at Urbana-Champaign proposed a wireless, continuous, and accurate methodology to monitor track conditions. This project, referred to as “Smart Track”, included the development of a conceptual design plan for efficient and effective implementation of smart monitoring technologies. The project began by establishing guiding research questions, and revising those questions based on track-caused accident data obtained from the Federal Railroad Administration (FRA) and expert opinions from rail experts in the public and private sectors. Next, the research team combined these findings and developed metrics for assigning risk and priorities to various track assets and inspection needs. In parallel, the project team conducted a survey of available wireless technologies for intra-site and site-to-cloud communications. These capabilities were mapped to instrumentation types and requirements (e.g., strain gauges, accelerometers) to ensure compatibility in terms of energy consumption, bandwidth, and communications range. Results identified the rail, crosstie and support, ballast and sub-structure, bridge deck and support, and special trackwork as priority locations for instrumentation. Additionally, IEEE 802.15.4 was found to be the most appropriate cellular communication system within field sites and 4G LTE cellular was determined to be the wireless technology best suited for field site-to-cloud communication. The conceptual design presented in this paper is the first step in achieving the broader goal of Smart Track; to improve the rail industry’s ability to answer critical safety and maintenance-related questions related to the track infrastructure by monitoring and predicting track health. Full article
(This article belongs to the Special Issue Structural Sensing and Sustainable Infrastructure Maintenance)
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Article
Aerial Tramway Sustainable Monitoring with an Outdoor Low-Cost Efficient Wireless Intelligent Sensor
Sustainability 2021, 13(11), 6340; https://doi.org/10.3390/su13116340 - 03 Jun 2021
Viewed by 731
Abstract
Infrastructures such as aerial tramways carry unique traffic operations and have specific maintenance requirements that demand constant attention. It is common that old structures lack any type of automatization or monitoring systems, relying only on human judgment. Owners are interested in implementing techniques [...] Read more.
Infrastructures such as aerial tramways carry unique traffic operations and have specific maintenance requirements that demand constant attention. It is common that old structures lack any type of automatization or monitoring systems, relying only on human judgment. Owners are interested in implementing techniques that assist them in making maintenance decisions, but are reluctant to invest in expensive and complex technology. In this study, researchers discussed with the owners different options and proposed a sustainable and cost-efficient solution to monitor the Sandia Peak Tramway operations with just two strategically located acceleration sensors. To maximize the success options researchers worked with the owners and developed a sensor that satisfied their needs. A Low-cost Efficient Wireless Intelligent Sensor 4—Outdoors (LEWIS 4) was developed, tested and validated during the experiment. Two solar-powered units were installed by the tramway staff and recorded data for three days. When retrieved, researchers analyzed the data recorded and concluded that with only two sensors, the acceleration data collected were sufficient to determine the position and location of the tramway cars. It was also found that the sensor on the tower provides data about the cable–tower interaction and the forces caused by the friction on the system, this being a critical maintenance factor. This work summarizes a methodology for infrastructure owners consisting of guidelines to design a sustainable and affordable monitoring approach that is based on the design, development and installation of low-cost sensors. Full article
(This article belongs to the Special Issue Structural Sensing and Sustainable Infrastructure Maintenance)
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