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Applied Sciences
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Infrastructure Management and Maintenance: Methods and Applications
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Infrastructure Management and Maintenance: Methods and Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 5800

Special Issue Editors

Dr. José Campos Matos

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Guest Editor
Civil Engineering Department, School of Engineering, Minho University, Campus de Azurem, 4800-058 Guimaraes, Portugal
Interests: asset management systems; life-cycle costs (LCC); safety assessment; risk evaluation; sustainability
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Alfred Strauss

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Guest Editor
Institute for Structural Engineering, Department of Civil Engineering and Natural Hazards, University of Natural Resources and Life Sciences, Gregor-Mendel-Straße 33, 1180 Vienna, Austria
Interests: infrastructures; reliability engineering; life-cycle analysis; monitoring
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Rade Hajdin

E-Mail Website
Guest Editor
1.Faculty of Civil Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, 11000 Belgrade, Serbia 2.Infrastructure Management Consultants LLC., Bellerivestrasse 209, 8008 Zurich, Switzerland
Interests: infrastructure management; structural engineering; transportation; vulnerability assessment; infrastructure asset management; multiple-criteria decision analysis
Dr. Ngoc-Son Dang

E-Mail Website
Guest Editor
Department of Civil Engineering, University of Minho, 4800-058 Guimarães, Portugal
Interests: digitalization; digital twinning; BIM; BMS; holographic computing
Dr. Hélder Sousa

E-Mail Website
Guest Editor
Department of Civil Engineering, University of Minho, ISISE, ARISE, 4800-058 Guimarães, Portugal
Interests: structural analysis safety; structural engineering; safety and reliability; predictive modeling; mechanical testing; mechanical characterization; mechanical properties; civil engineering; earthquake engineering; construction; building; construction materials; building materials; civil engineering materials; concrete technologies; nondestructive testing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are inviting submissions to this Special Issue on “Infrastructure Management and Maintenance: Methods and Applications”.

Transport infrastructure has increasingly become one of the most crucial factors for the development of modern society. In the last decade, awareness of the demands in maintaining the existing infrastructures has been raised. The future of the infrastructure industry will lie in those existing and properly maintained rather than replacements. Therefore, sustainability and resilience issues are the top priorities for engineers and researchers within the infrastructure field.

In particular, the development of methods and applications that are more accurate, efficient, cost-effective, and sustainable to support all aspects of lifecycle management is essential to the successful completion of this settlement on maintaining the existing infrastructure.

Dr. José António Silva Carvalho Campos Matos
Prof. Dr. Alfred Strauss
Prof. Dr. Rade Hajdin
Dr. Ngoc-Son Dang
Dr. Hélder Sousa
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. Applied Sciences 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 2400 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

  • infrastructure
  • bridge
  • sustainability
  • resilience
  • BMS

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Published Papers (4 papers)

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Research

29 pages, 9173 KiB  
Article
Structure Deterioration Identification and Model Updating for Prestressed Concrete Bridges Based on Massive Point Cloud Data
by Zhe Sun, Sihan Zhao, Bin Liang and Zhansheng Liu
Appl. Sci. 2024, 14(21), 10007; https://doi.org/10.3390/app142110007 - 1 Nov 2024
Viewed by 642
Abstract
As a critical component of the transportation system, the safety of bridges is directly related to public safety and the smooth flow of traffic. This study addresses the aforementioned issues by focusing on the identification of bridge structure deterioration and the updating of [...] Read more.
As a critical component of the transportation system, the safety of bridges is directly related to public safety and the smooth flow of traffic. This study addresses the aforementioned issues by focusing on the identification of bridge structure deterioration and the updating of finite element models, proposing a systematic research framework. First, this study presents a preprocessing method for bridge point cloud data and determines the parameter ranges for key algorithms through parameter tuning. Subsequently, based on the massive point cloud data, this research explores and optimizes the methods for identifying bridge cracks and spatial deformations, significantly enhancing the accuracy and efficiency of identification. On this basis, the particle swarm optimization algorithm is employed to optimize the key parameters in crack detection, ensuring the reliability and precision of the algorithm. Additionally, the study summarizes the methods for detecting bridge structural deformations based on point cloud data and establishes a framework for updating the bridge model. Finally, by integrating the results of bridge crack and deformation detection and combining Bayesian model correction and adaptive nested sampling methods, this research sets up the process for updating finite element model parameters and applies it to the analysis of actual bridge point cloud data. Full article
(This article belongs to the Special Issue Infrastructure Management and Maintenance: Methods and Applications)
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17 pages, 550 KiB  
Article
A Hybrid Deep Learning Model Utilizing Cross-Structural Multi-Behavioral Comparative Recommendation for Sustainable Electric Transportation Infrastructure
by Zihang Xu and Chiawei Chu
Appl. Sci. 2024, 14(7), 3092; https://doi.org/10.3390/app14073092 - 7 Apr 2024
Viewed by 801
Abstract
Ensuring the sustainability of transportation infrastructure for electric vehicles (e-trans) is increasingly imperative in the pursuit of decarbonization goals and addressing the pressing energy shortage. By prioritizing the development and maintenance of resilient e-trans platforms through the optimization of the public charging network, [...] Read more.
Ensuring the sustainability of transportation infrastructure for electric vehicles (e-trans) is increasingly imperative in the pursuit of decarbonization goals and addressing the pressing energy shortage. By prioritizing the development and maintenance of resilient e-trans platforms through the optimization of the public charging network, electric vehicle businesses can effectively meet the needs of users, thereby contributing to efforts aimed at improving environmental quality. To achieve this goal, researching the dynamics of vehicle user behaviors plays a crucial role. In this paper, we propose cross-structure multi-behavior contrastive learning for recommendation (C-MBR), which takes into account the dynamic preferences of users, and develops model profiles from the global structure module, local structure module, cross-behavior contrastive learning module, cross-structure contrastive learning module, and model prediction and optimization. C-MBR is mainly designed to learn user preferences from the diversity of users’ behaviors in the process of interacting with the project, so as to grasp the different behavioral intentions of users. The experimental and analytical research is further conducted and validated for dealing with cold start problems. The results indicate that C-MBR has a strong ability to deal with the problem of sparse data. Compared with the ablation experiment, the model performance of C-MBR is significantly enhanced, showing that the C-MBR model can fully apply the information of a global structure and local structure in cross-structure comparative learning and multi-behavioral comparative learning to further alleviate the problem of data sparsity. As a result, the e-trans infrastructure will be significantly enhanced by addressing the issue of data-driven disruption. Full article
(This article belongs to the Special Issue Infrastructure Management and Maintenance: Methods and Applications)
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12 pages, 4593 KiB  
Article
Dependence of Sensitivity Factors on Ratio of Traffic Load to Dead Load
by Goran Milutinovic and Rade Hajdin
Appl. Sci. 2024, 14(3), 985; https://doi.org/10.3390/app14030985 - 24 Jan 2024
Viewed by 823
Abstract
According to modern structural codes, a design is considered to be adequate if the limit states are not exceeded. For the ultimate limit state, the design value of action effect Ed is required to be less or equal than the design value [...] Read more.
According to modern structural codes, a design is considered to be adequate if the limit states are not exceeded. For the ultimate limit state, the design value of action effect Ed is required to be less or equal than the design value of ultimate resistance Rd. This ensures, according to the Eurocode, a sufficiently low probability of failure expressed as the target reliability index β. Consequently, the distributions of action effect and of resistance need to satisfy the following conditions: PE>Ed≤Φ+αEβ and PR≤Rd≤Φ−αRβ, where αE and αR, with |α| ≤ 1, are the values of the FORM sensitivity factors. The values of the sensitivity factors αE and αR are suggested, according to EN1990, as −0.7 and 0.8, respectively; for the accompanying actions, the sensitivity factor is recommended as 0.28. In this paper, the dependence of the sensitivity factors for traffic live load, dead load, and resistance on the ratio of traffic load to dead load is studied (which is directly proportional to the maximum span of the bridge). Significantly different sensitivity factors for resistance, dead load, and traffic load, other than proposed by the Eurocode, has been calculated for typical ratio of traffic to dead load. It further showed that, if it is assumed that Ed = Rd and the Eurocode partial safety factors are used, a different design point than the starting point, i.e., Ed = Rd, is obtained. Full article
(This article belongs to the Special Issue Infrastructure Management and Maintenance: Methods and Applications)
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16 pages, 7729 KiB  
Article
Development of a Novel Apparatus to Determine Multiaxial Tensile Failure Criteria of Bridge Repair Materials
by Trevor Looney and Jeffery Volz
Appl. Sci. 2023, 13(18), 10207; https://doi.org/10.3390/app131810207 - 11 Sep 2023
Viewed by 818
Abstract
Aging infrastructure is increasingly costing taxpayers due to increased repair and replacement costs. Ultra-high performance concrete (UHPC) has recently been recognized as a viable material for both the repair of concrete and steel infrastructure as well as a replacement material for new structures [...] Read more.
Aging infrastructure is increasingly costing taxpayers due to increased repair and replacement costs. Ultra-high performance concrete (UHPC) has recently been recognized as a viable material for both the repair of concrete and steel infrastructure as well as a replacement material for new structures due to its enhanced mechanical and durability properties. Such uses require a much better understanding of the multiaxial tensile properties of UHPC to utilize the material more efficiently. This study focused on developing a novel apparatus capable of subjecting specimens to tensile forces in each of the three principal directions simultaneously. Such an apparatus could collect data for a portion of the failure surface that currently only has a small dataset to establish trends. The “Looney Bin” was designed to test 50-mm cube specimens in triaxial tension, biaxial tension, tension-compression, and tension-tension-compression stress states. Once the apparatus and fixtures were designed and fabricated, trial tests were conducted on a non-proprietary UHPC without steel fibers to establish a test method for each of the stress states evaluated. Data were then collected for different stress states using the established procedures and plotted against previously published failure models for UHPC to verify that the collected data were reasonable. Full article
(This article belongs to the Special Issue Infrastructure Management and Maintenance: Methods and Applications)
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