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Inspection, Assessment and Retrofit of Transport Infrastructure

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

Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 24224

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Special Issue Editors

Dr. Reza Haghani

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Guest Editor

Department of Architectural and Civil Engineering, Chalmers University of Technology, Sven Hultins Gata 6, 41296 Gothenburg, Sweden
Interests: strengthening and repair of structures; application of fiber polymer composite (FPC) materials in construction; environmental durability of FPC materials and systems
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Rami Hawileh

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Guest Editor

College of Engineering, Department of Civil Engineering, American University of Sharjah, Sharjah, United Arab Emirates
Interests: FRP strengthening of RC structures; fire performance of FRP strengthened structures; computational modeling
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Paolo S. Valvo

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Guest Editor

Department of Civil and Industrial Engineering, University of Pisa, Largo Lucio Lazzarino, I-56122 Pisa (PI), Italy
Interests: mechanics of solids and structures; fracture mechanics; stability and dynamics of structures; computational mechanics; composite and advanced materials; structural strengthening; energy harvesting
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The road and railway transport network forms the backbone of transportation systems, the performance of which is largely dependent on the state of the critical infrastructure such as bridges. Bridges serve as a vital part of the infrastructure and have a very high asset value as capital to be protected.

Many of these bridges are subjected to aging effects such as corrosion of internal steel reinforcement. The adverse aging effects in infrastructure is expected to accelerate in the future as a result of “climate change”. Moreover, the load demands on bridges have been constantly increasing in the past few decades, and many elder bridges are currently carrying heavier loads compared to their original design loads. It is expected that the increase in load demands will continue in the future, indicating faster aging and more stringent requirements on old bridge stock.

There is currently a great demand for innovations in the maintenance of existing bridge infrastructure, including inspection, assessment, strengthening and repair, and management. In this Special Issue, we request high-quality original research articles focused on the state-of-the-art techniques and methods addressing the inspection, assessment, and upgrading of old bridge infrastructure. We welcome both theoretical and applied papers of high technical standard across various branches in construction sector, thus facilitating an awareness of techniques and methods applicable in bridges that may be relevant to other structures.

Topics of interest include, but are not limited to:

Advances in inspection, sensoring and structural health monitoring (SHM) methods and technologies for bridges;
Advances in assessment methods, e.g., load-carrying capacity evaluation of reinforced concrete (RC) structures with corrosion damage, fatigue life assessment in welded steel bridges, probabilistic structural integrity assessment;
New materials and techniques for strengthening and repair of existing bridges (e.g., application of shape memory alloys, advanced fiber-reinforced polymer composites);
Long-term behavior, environmental durability, and fire performance of strengthening and repair systems;
Design codes and guidelines;
Recent case studies (e.g., lessons learned);
Monitoring and field measurements on rehabilitated bridges;
Advances in management of maintenance works and planning, e.g., risk-informed asset management (RIAM).

Original submissions related to other types of structure relevant to focus areas of this special issue are also welcome.

Prof. Dr. Reza Haghani
Prof. Dr. Rami Hawileh
Prof. Dr. Paolo S. Valvo
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

strengthening
repair, inspection, structural assessment
management of maintenance.

Published Papers (6 papers)

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Research

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18 pages, 7247 KiB

Open AccessArticle

Deep Learning and YOLOv3 Systems for Automatic Traffic Data Measurement by Moving Car Observer Technique

by Marco Guerrieri and Giuseppe Parla

Infrastructures 2021, 6(9), 134; https://doi.org/10.3390/infrastructures6090134 - 18 Sep 2021

Cited by 12 | Viewed by 3031

Abstract

Macroscopic traffic flow variables estimation is of fundamental interest in the planning, designing and controlling of highway facilities. This article presents a novel automatic traffic data acquirement method, called MOM-DL, based on the moving observer method (MOM), deep learning and YOLOv3 algorithm. The proposed method is able to automatically detect vehicles in a traffic stream and estimate the traffic variables flow q, space mean speed vs. and vehicle density k for highways in stationary and homogeneous traffic conditions. The first application of the MOM-DL technique concerns a segment of an Italian highway. In the experiments, a survey vehicle equipped with a camera has been used. Using deep learning and YOLOv3 the vehicles detection and the counting processes have been carried out for the analyzed highway segment. The traffic flow variables have been calculated by the Wardrop relationships. The first results demonstrate that the MOM and MOM-DL methods are in good agreement with each other despite some errors arising with MOM-DL during the vehicle detection step due to a variety of reasons. However, the values of macroscopic traffic variables estimated by means of the Drakes’ traffic flow model together with the proposed method (MOM-DL) are very close to those obtained by the traditional one (MOM), being the maximum percentage variation less than 3%. Full article

(This article belongs to the Special Issue Inspection, Assessment and Retrofit of Transport Infrastructure)

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22 pages, 5248 KiB

Open AccessArticle

Fiber Reinforced Polymer Culvert Bridges—A Feasibility Study from Structural and LCC Points of View

by Reza Haghani, Jincheng Yang, Marte Gutierrez, Christopher D. Eamon and Jeffery Volz

Infrastructures 2021, 6(9), 128; https://doi.org/10.3390/infrastructures6090128 - 7 Sep 2021

Cited by 3 | Viewed by 5001

Abstract

Soil–steel composite bridges (SSCB) have become increasingly popular for short-span bridges as an alternative to concrete slab bridges mainly due to their low initial cost, rapid manufacture, simplified construction, and geometrical adaptability. SSCBs have a variety of applications and can be used over waterways or roadways. While conventional bridges tend to lose their load-carrying capacity due to degradation, SSCBs gain strength because of backfill soil consolidation. However, the load carrying capacity and integrity of such structures highly depends on the condition and load-carrying capacity of the steel arch element. A major drawback of SSCBs, especially those located on waterways or with poor drainage, is corrosion and subsequent loss of cross-sectional capacity. Unfortunately, the inspection of such bridges is not straightforward and any damage/collapse will be very costly to repair/replace. Fiber reinforced polymer (FRP) composites offer an attractive alternative to replace the steel in these types of bridges. FRP composites have significantly improved durability characteristics compared to steel, which will reduce maintenance costs and improve life-cycle costs (LLCs). This paper presents a new concept to use glass FRP as a construction material to construct soil–FRP composite bridges (SFCB). Various aspects of design and manufacturing are presented along with results and conclusions from a case study involving alternative bridge designs in steel and FRP composites. Full article

(This article belongs to the Special Issue Inspection, Assessment and Retrofit of Transport Infrastructure)

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17 pages, 4942 KiB

Open AccessArticle

Mechanical Properties of Strengthening 5083-H111 Aluminum Alloy Plates at Elevated Temperatures

by Wael Abuzaid, Rami Hawileh and Jamal Abdalla

Infrastructures 2021, 6(6), 87; https://doi.org/10.3390/infrastructures6060087 - 14 Jun 2021

Cited by 7 | Viewed by 3915

Abstract

The use of aluminum alloys for external strengthening of reinforced concrete (RC) beams has been capturing research interest. Exposure to harsh environmental conditions can severely impact the strengthening efficiency. This works aims to investigate the degradation in the mechanical properties of aluminum alloy AA 5083 plates when exposed to temperatures ranging from 25 to 300 °C. Quasi-static Isothermal tensile experiments were conducted at different temperatures. It was observed from the experimental results that the yield strength remained constant in the temperature range of 25–150 °C before starting to drop beyond 150 °C, with a total reduction of ≈ 40% at 300 °C. The elastic modulus was temperature sensitive with about 25% reduction at 200 °C before experiencing a significant and pronounced reduction at 300 °C. The percentage drops in stiffness and yield strength at 300 °C were 62.8% and 38%, respectively. In addition, the Mechanical Threshold Strength Model (MTS) parameters were established to capture the yield strength temperature dependence. Two analytical models were developed based on the experimental results. Both models can reasonably predict the elastic modulus and yield strength of AA 5083 plates as a function of temperature. It was concluded that AA plates should be properly insulated when used as externally bonded reinforcement to strengthen RC beams. Full article

(This article belongs to the Special Issue Inspection, Assessment and Retrofit of Transport Infrastructure)

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35 pages, 2663 KiB

Open AccessArticle

A Comprehensive Uncertainty-Based Framework for Inspection Planning of Highway Bridges

by Abdelrahman M. Abdallah, Rebecca A. Atadero and Mehmet E. Ozbek

Infrastructures 2021, 6(2), 27; https://doi.org/10.3390/infrastructures6020027 - 11 Feb 2021

Cited by 11 | Viewed by 2747

Abstract

Bridge inspection standards in the United States require routine visual inspections to be conducted on most bridges at a maximum interval of two years regardless of the bridge condition. Limitations of this uniform calendar-based approach have been reported in the literature. Accordingly, the objective of this study is to provide a new systematic approach for inspection planning that integrates information from bridge condition prediction models, inspection data, and expert opinion using Bayesian analysis to enhance inspection efficiency and maintenance activities. The uncertainty-based inspection framework proposed in this study can help bridge owners avoid unnecessary or delayed inspections and repair actions, determine the inspection method, and consider more than one deterioration process or bridge component during the inspection planning process. The inspection time and method are determined based on the uncertainty and risks associated with the bridge condition. As uncertainty in the bridge condition reaches a defined threshold, an inspection is scheduled utilizing nondestructive techniques to reduce the uncertainty level. The framework is demonstrated on a new and on an existing reinforced concrete bridge deck impacted by corrosion deterioration. The results show that the framework can reduce the number of inspections by 50% compared to conventional scheduling methods, and the uncertainty regarding the bridge maintenance time is reduced by 16%. Full article

(This article belongs to the Special Issue Inspection, Assessment and Retrofit of Transport Infrastructure)

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Review

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28 pages, 8063 KiB

Open AccessReview

gPCE-Based Stochastic Inverse Methods: A Benchmark Study from a Civil Engineer’s Perspective

by Filippo Landi, Francesca Marsili, Noemi Friedman and Pietro Croce

Infrastructures 2021, 6(11), 158; https://doi.org/10.3390/infrastructures6110158 - 5 Nov 2021

Cited by 6 | Viewed by 2182

Abstract

In civil and mechanical engineering, Bayesian inverse methods may serve to calibrate the uncertain input parameters of a structural model given the measurements of the outputs. Through such a Bayesian framework, a probabilistic description of parameters to be calibrated can be obtained; this approach is more informative than a deterministic local minimum point derived from a classical optimization problem. In addition, building a response surface surrogate model could allow one to overcome computational difficulties. Here, the general polynomial chaos expansion (gPCE) theory is adopted with this objective in mind. Owing to the fact that the ability of these methods to identify uncertain inputs depends on several factors linked to the model under investigation, as well as the experiment carried out, the understanding of results is not univocal, often leading to doubtful conclusions. In this paper, the performances and the limitations of three gPCE-based stochastic inverse methods are compared: the Markov Chain Monte Carlo (MCMC), the polynomial chaos expansion-based Kalman Filter (PCE-KF) and a method based on the minimum mean square error (MMSE). Each method is tested on a benchmark comprised of seven models: four analytical abstract models, a one-dimensional static model, a one-dimensional dynamic model and a finite element (FE) model. The benchmark allows the exploration of relevant aspects of problems usually encountered in civil, bridge and infrastructure engineering, highlighting how the degree of non-linearity of the model, the magnitude of the prior uncertainties, the number of random variables characterizing the model, the information content of measurements and the measurement error affect the performance of Bayesian updating. The intention of this paper is to highlight the capabilities and limitations of each method, as well as to promote their critical application to complex case studies in the wider field of smarter and more informed infrastructure systems. Full article

(This article belongs to the Special Issue Inspection, Assessment and Retrofit of Transport Infrastructure)

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37 pages, 9415 KiB

Open AccessReview

Pollutant Emissions in Ports: A Comprehensive Review

by Salvatore Barberi, Mariacrocetta Sambito, Larysa Neduzha and Alessandro Severino

Infrastructures 2021, 6(8), 114; https://doi.org/10.3390/infrastructures6080114 - 14 Aug 2021

Cited by 32 | Viewed by 6164

Abstract

In recent decades, maritime transport demand has increased along with world population and global trades. This is associated with higher pollution levels, including the emissions of GHG and other polluting gases. Ports are important elements within maritime transport and contribute themselves to pollutant emissions. This paper aims to offer a comprehensive yet technical review of the latest related technologies, explaining and covering aspects that link ports with emissions, i.e., analyzing, monitoring, assessing, and mitigating emissions in ports. This has been achieved through a robust scientific analysis of very recent and significant research studies, to offer an up-to-date and reliable overview. Results show the correlation between emissions and port infrastructures, and demonstrate how proper interventions can help with reducing pollutant emissions and financial costs as well, in ports and for maritime transportation in general. Besides, this review also wishes to propose new ideas for future research: new future experimental studies might spin-off from it, and perhaps port Authorities might be inspired to experiment and implement dedicated technologies to improve their impact on environment and sustainability. Full article

(This article belongs to the Special Issue Inspection, Assessment and Retrofit of Transport Infrastructure)

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