Special Issue "Innovate, Research, and Maintain Transportation Infrastructure"

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

Deadline for manuscript submissions: closed (15 August 2020).

Special Issue Editor

Dr. Mi G. Chorzepa
E-Mail Website
Guest Editor
712E Boyd Graduate Studies, The University of Georgia, 200 D. W. Brooks Drive, Athens, GA 30602, USA
Interests: structural analysis and design; experimental and numerical investigation of structures; nonlinear finite element analysis; materials modeling; forensic engineering; structural repair; composite materials; bridge design and evaluation; bridge maintenance

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to assimilate the current state-of-the-art knowledge in advances in materials and experimental/numerical investigation methods used to evaluate transportation infrastructure and create a forum for researchers and/or transportation agencies with a shared interest of vision, innovation, challenges, research, progress, and long-term asset management of new and existing transportation infrastructure. Examples of interested structures include, but are not limited to, bridges constructed with accelerated bridge construction methods, ultra-high-performance concrete (UHPC), bridge decks, steel bridges, traffic sign structures, foundation structures, bridge girders and piers, bearing elements, and concrete pavements.

This issue desires to combine contributions on the latest research developments, including experimental and analytical investigations to innovate research construction materials and delivery methods.  In addition, this issue hopes to address long-term maintenance aspects of transportation assets as they must be managed to adopt new technology, as well as innovative materials and delivery methods.

To this end, this Special Issue includes the following three main topics (or a combination of the topics), which are indispensable aspects of transportation infrastructure:

Innovation

  • innovative construction materials;
  • challenges with innovative materials;
  • accelerated bridge construction (ABC) and innovative delivery methods;
  • challenges with innovative construction or delivery methods;
  • innovation in construction methods and the use of technology;
  • innovation in bridge inspection methods;
  • innovation in research methods;

Research

  • computational modeling methods to evaluate innovation;
  • research projects to sustain and/or support transportation infrastructure;
  • experimental investigation;
  • ultra-high performance concrete (UHPC);
  • numerical predictions;
  • statistical analysis;
  • performance of reinforced concrete elements;
  • advancement in bridge monitoring methods.

Maintenance

  • failures and/or maintenance challenges resulting from (or inherent in) innovation;
  • analysis of bridge inventory data;
  • data collection, analysis, and management;
  • depreciation models used for transportation asset management;
  • infrastructures asset valuation;
  • effect of truck traffic and/or environmental factors;
  • analysis of condition scores;
  • long-term monitoring and management.

Dr. Mi G. Chorzepa
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. 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 1400 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

  • Computational
  • Accelerated
  • Bridge
  • Materials
  • UHPC
  • Numerical
  • Analysis
  • Experiment
  • Aging
  • Innovation
  • Depreciation
  • Maintenance
  • Research

Published Papers (6 papers)

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Research

Article
Investigation into Recycled Rubber Aggregates and Steel Wire Fiber for Use in Concrete Subjected to Impact Loading
Infrastructures 2020, 5(10), 82; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures5100082 - 10 Oct 2020
Cited by 3 | Viewed by 759
Abstract
This study investigated the potential use of tire derived rubber aggregates, particularly powdered rubber, and recycled steel-wire fibers in concrete subjected to impact loading. The fibers are approximately 0.4 mm in average diameter and 25 mm in length on average. There are two [...] Read more.
This study investigated the potential use of tire derived rubber aggregates, particularly powdered rubber, and recycled steel-wire fibers in concrete subjected to impact loading. The fibers are approximately 0.4 mm in average diameter and 25 mm in length on average. There are two main portions to this study. The first phase of this study involved small-scale batching to investigate the fresh and hardened properties of concrete mixtures with powdered rubber up to 50% replacement of sand volume and recycled steel fibers up to 0.25% by mixture volume. Additional mixtures containing powdered rubber, crumb rubber, and tire chips were evaluated for their mechanical performance. Based on fresh concrete properties, compressive strength, modulus of rigidity, and impact resilience, mixtures were selected for a second investigative phase. In this phase, static and impact testing were performed on two sets of scaled beams. One beam set was produced with concrete containing 40% powdered rubber as a sand replacement and another beam set with a combination mixture incorporating rubber products of varying sizes (10% powdered rubber, 10% crumb rubber, and 10% tire chip) and 0.25% recycled steel fiber. Flexural performance improved initially with the inclusion of powdered rubber but decreased with increasing concentrations. Mixtures including recycled steel fibers at 0.25% outperformed industrial steel fiber mixtures in both flexural strength and impact resistance. For both the static and impact beams with the recycled powdered rubber and steel fibers in the combination demonstrated improved load distribution and load-carrying capacity, acting as a sufficient replacement for industrial steel fiber reinforcement. Full article
(This article belongs to the Special Issue Innovate, Research, and Maintain Transportation Infrastructure)
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Article
A Strategic Move for Long-Term Bridge Performance within a Game Theory Framework by a Data-Driven Co-Active Mechanism
Infrastructures 2020, 5(10), 79; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures5100079 - 29 Sep 2020
Viewed by 785
Abstract
The Federal Highway Administration (FHWA) requires that states have less than 10% of the total deck area that is structurally deficient. It is a minimum risk benchmark for sustaining the National Highway System bridges. Yet, a decision-making framework is needed for obtaining the [...] Read more.
The Federal Highway Administration (FHWA) requires that states have less than 10% of the total deck area that is structurally deficient. It is a minimum risk benchmark for sustaining the National Highway System bridges. Yet, a decision-making framework is needed for obtaining the highest possible long-term return from investments on bridge maintenance, rehabilitation, and replacement (MRR). This study employs a data-driven coactive mechanism within a proposed game theory framework, which accounts for a strategic interaction between two players, the FHWA and a state Department of Transportation (DOT). The payoffs for the two players are quantified in terms of a change in service life. The proposed framework is used to investigate the element-level bridge inspection data from four US states (Georgia, Virginia, Pennsylvania, and New York). By reallocating 0.5% (from 10% to 10.5%) of the deck resources to expansion joints and joint seals, both federal and state transportation agencies (e.g., FHWA and state DOTs in the U.S.) will be able to improve the overall bridge performance. This strategic move in turn improves the deck condition by means of a co-active mechanism and yields a higher payoff for both players. It is concluded that the proposed game theory framework with a strategic move, which leverages element interactions for MRR, is most effective in New York where the average bridge service life is extended by 15 years. It is also concluded that the strategic move can lead to vastly different outcomes. Pennsylvania’s concrete bridge management strategy currently appears to leverage a co-active mechanism in its bridge MRR strategies. This is noteworthy because its bridges are exposed to similar environmental conditions to what is obtainable in Virginia and New York and are subjected to more aggressive weather conditions than those in Georgia. This study illustrates how a strategic move affects the payoffs of different players by numerically quantifying changes in service life from bridge time-dependent bridge performance relationships. Full article
(This article belongs to the Special Issue Innovate, Research, and Maintain Transportation Infrastructure)
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Article
Understanding Multi-Vehicle Collision Patterns on Freeways—A Machine Learning Approach
Infrastructures 2020, 5(8), 62; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures5080062 - 24 Jul 2020
Cited by 3 | Viewed by 1363
Abstract
Generating meaningful inferences from crash data is vital to improving highway safety. Classic statistical methods are fundamental to crash data analysis and often regarded for their interpretability. However, given the complexity of crash mechanisms and associated heterogeneity, classic statistical methods, which lack versatility, [...] Read more.
Generating meaningful inferences from crash data is vital to improving highway safety. Classic statistical methods are fundamental to crash data analysis and often regarded for their interpretability. However, given the complexity of crash mechanisms and associated heterogeneity, classic statistical methods, which lack versatility, might not be sufficient for granular crash analysis because of the high dimensional features involved in crash-related data. In contrast, machine learning approaches, which are more flexible in structure and capable of harnessing richer data sources available today, emerges as a suitable alternative. With the aid of new methods for model interpretation, the complex machine learning models, previously considered enigmatic, can be properly interpreted. In this study, two modern machine learning techniques, Linear Discriminate Analysis and eXtreme Gradient Boosting, were explored to classify three major types of multi-vehicle crashes (i.e., rear-end, same-direction sideswipe, and angle) occurred on Interstate 285 in Georgia. The study demonstrated the utility and versatility of modern machine learning methods in the context of crash analysis, particularly in understanding the potential features underlying different crash patterns on freeways. Full article
(This article belongs to the Special Issue Innovate, Research, and Maintain Transportation Infrastructure)
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Article
Analytical Model for Air Flow into Cracked Concrete Structures for Super-Speed Tube Transport Systems
Infrastructures 2019, 4(4), 76; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures4040076 - 17 Dec 2019
Cited by 2 | Viewed by 2731
Abstract
The super-speed tube transport (SSTT) system, which enables high-speed transportation in a partially vacuumed tube by minimizing the air resistance, is drawing attention as a next-generation transportation system. To evaluate the applicability of concrete as a material for the system, the effect of [...] Read more.
The super-speed tube transport (SSTT) system, which enables high-speed transportation in a partially vacuumed tube by minimizing the air resistance, is drawing attention as a next-generation transportation system. To evaluate the applicability of concrete as a material for the system, the effect of cracks on the airtightness of the system needs to be considered. This study aims to establish an analytical relationship between the cracks induced on a concrete tube structure and the system airtightness. An analytical model for the leakage rate through the concrete cracks is first applied to establish a differential equation, which can help determine the air flow rate into the concrete tube structure through the cracks. A mathematical formula for predicting the internal pressure changes over time in the concrete tube structure is then derived. The effect of crack development on the system airtightness is assessed through parametric analysis and a crack index for describing the extent of crack development is proposed by investigating the correlation with the system airtightness. Finally, assuming that the cracks due to external loadings are closely related to the displacement, the correlation between displacements and the airtightness of concrete tube structures is demonstrated through a set of experimental tests. As a result, the necessity of crack analysis for evaluation of the airtightness performance is emphasized. Full article
(This article belongs to the Special Issue Innovate, Research, and Maintain Transportation Infrastructure)
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Article
On the Use of Ensemble Empirical Mode Decomposition for the Identification of Bridge Frequency from the Responses Measured in a Passing Vehicle
Infrastructures 2019, 4(2), 32; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures4020032 - 04 Jun 2019
Cited by 11 | Viewed by 3393
Abstract
In this paper, ensemble empirical mode decomposition (EEMD) and empirical mode decomposition (EMD) methods are used for the effective identification of bridge natural frequencies from drive-by measurements. A vehicle bridge interaction (VBI) model is created using the finite element (FE) method in Matlab. [...] Read more.
In this paper, ensemble empirical mode decomposition (EEMD) and empirical mode decomposition (EMD) methods are used for the effective identification of bridge natural frequencies from drive-by measurements. A vehicle bridge interaction (VBI) model is created using the finite element (FE) method in Matlab. The EMD is employed to decompose the signals measured on the vehicle to their main components. It is shown that the bridge component of the response measured on the vehicle can be extracted using the EMD method. The influence of some factors, such as the road roughness profile and measurement noise, on the results are investigated. The results suggest that the EMD shows good performance under those conditions, but the accuracy of the results may still need to be improved. It is shown that in some cases, the EMD may not be able to decompose the signal effectively and includes mode mixing. This results in inaccuracies in the identification of bridge frequencies. The use of the ensemble empirical mode decomposition (EEMD) method is proposed to overcome the mode mixing problem. The influence of factors such as road profile, measurement noise and vehicle velocity are investigated. It is numerically demonstrated that employing the EEMD improves the results compared to the EMD. Full article
(This article belongs to the Special Issue Innovate, Research, and Maintain Transportation Infrastructure)
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Article
Effect of Scour on the Natural Frequency Responses of Bridge Piers: Development of a Scour Depth Sensor
Infrastructures 2019, 4(2), 21; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures4020021 - 07 May 2019
Cited by 8 | Viewed by 3682
Abstract
Local scour is the removal of soil around bridge foundations under the erosive action of flowing water. This hydraulic risk has raised awareness of the need for developing continuous monitoring techniques to estimate scour depth around bridge piers and abutments. One of the [...] Read more.
Local scour is the removal of soil around bridge foundations under the erosive action of flowing water. This hydraulic risk has raised awareness of the need for developing continuous monitoring techniques to estimate scour depth around bridge piers and abutments. One of the emerging techniques is based on monitoring the vibration frequency of either bridge piers or a driven sensor in the riverbed. The sensor proposed in this study falls into the second category. Some unresolved issues are investigated: the effect of the geometry and material of the sensor, the effect of the embedded length and the effect of soil type. To this end, extensive laboratory tests are performed using rods of different materials, with various geometries and lengths. These tests are conducted in both dry sand and a soft clayey soil. Since the sensor will be placed in the riverbed, it is crucial to evaluate the effect of immersed conditions on its response. A numerical 3D finite-element model was developed and compared against experimental data. This model was then used to compute the ‘wet’ frequencies of the sensor. Finally, based on both the experimental and numerical results, an equivalent cantilever model is proposed to correlate the variation of the frequency of the sensor to the scour depth. Full article
(This article belongs to the Special Issue Innovate, Research, and Maintain Transportation Infrastructure)
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