Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
2.8
Journals
CivilEng
Special Issues
Next Generation Infrastructure
share announcement

Next Generation Infrastructure

A special issue of CivilEng (ISSN 2673-4109).

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 33580

Special Issue Editors

Dr. Panagiotis Michalis

E-Mail Website
Guest Editor
Institute of Communication and Computer Systems (ICCS), National Technical University of Athens, Athens, Greece
Interests: smart sensing; critical infrastructure; intelligent structures; structural health monitoring; climatic risks; risk ecosystems; digital transformation of infrastructure
Special Issues, Collections and Topics in MDPI journals
Dr. Manousos Valyrakis

E-Mail Website
Guest Editor
Infrastructure and Environment Research Division, School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK
Interests: sediment transport dynamics; monitoring environmental flows; geomorphic processes and instrumentation
Special Issues, Collections and Topics in MDPI journals
Dr. Gordon Gilja

E-Mail Website
Guest Editor
Department of Hydroscience and Engineering, Faculty of Civil Engineering, University of Zagreb, 10000 Zagreb, Croatia
Interests: sediment transport; bridge scour; dune morphodynamics; flood hazard
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Zied Driss

E-Mail Website
Guest Editor
Mechanical Engineering Department, Ecole Nationale d'Ingénieurs de Sfax, Sfax 3038, Tunisia
Interests: computational fluid dynamics; experiments fluid mechanics; environmental flows; aerodynamics

Special Issue Information

Dear Colleagues,

The growing infrastructure crisis highlights the need to accelerate the incorporation of recent technological advancements to enhance the current out-of-date management regimes to fit the changing climatic conditions. The main factors that amplify infrastructure deterioration and impact can be attributed to (a) aging infrastructure that has exceeded its design lifespan and currently faces major deterioration issues, (b) increases in the frequency and intensity of natural and climatic hazards, which amplify the risk for the critical assets due to their outdated design, and (c) cascading effects and systemic risks that even minor incidents can trigger, causing significant disruption to the infrastructure system.

Reliable methods and systems to evaluate these factors are therefore important for the efficient and proactive management of critical infrastructure assets. Despite the recent advances in the development and application of technological solutions, infrastructure is still managed traditionally in most cases.

This Special Issue focuses on recent advances that contribute to the next generation of physical and digital infrastructure. Contributions may include the development of theoretical models and laboratory and field applications to enhance the ability of infrastructure assets (e.g., transportation, water, energy) and societies to withstand and adapt to the era of extreme events. Potential topics include but are not limited to the following:

  • State-of-the-art techniques to assess risk derived from natural and climatic hazards at various types of infrastructure.
  • Sensing solutions using in situ, remote sensing, and terrestrial instruments.
  • Structural health monitoring applications to assess the impact of water and geo-related hazards at critical structures.
  • Monitoring of ecosystems to assess risk for expected and unexpected events.
  • Early warning and decision support systems applied to critical structures and considering the dynamics derived from the infrastructure system perspective.
  • Advanced prediction capabilities of infrastructure deterioration.
  • Interoperability aspects to optimize infrastructure system operations.
  • Immersive technologies and crowdsourcing applications to enhance the management and maintenance of infrastructure and provide risk information (e.g., digital twins, mixed, virtual, and augmented reality).

The Special Issue is supported by the IAHR-EMI LT (Experimental Methods and Instrumentation leadership team).

Dr. Panagiotis Michalis  
Dr. Manousos Valyrakis
Dr. Gordon Gilja  
Prof. Dr. Zied Driss
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. CivilEng is an international peer-reviewed open access quarterly 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 1200 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

  • ageing infrastructure
  • bridges
  • embankments
  • dams
  • critical structures
  • climatic risks
  • natural hazards
  • flood impact
  • geo-hazards
  • smart sensing
  • intelligent structures
  • structural health monitoring
  • risk monitoring
  • disaster-resilient infrastructure
  • systemic risks and cascading effects
  • digitalization of infrastructure
  • crowd-sourcing, crowd-sensing solutions
  • mixed reality applications
  • early warning and decision support systems

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (10 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Other

12 pages, 2341 KiB  
Article
Utilization of Plastic Waste in Road Paver Blocks as a Construction Material
by Rajat Agrawal, Suraj Kumar Singh, Saurabh Singh, Deepak Kumar Prajapat, Sharma Sudhanshu, Sujeet Kumar, Bojan Đurin, Marko Šrajbek and Gordon Gilja
CivilEng 2023, 4(4), 1071-1082; https://doi.org/10.3390/civileng4040058 - 13 Oct 2023
Cited by 5 | Viewed by 9861
Abstract
India is confronted with the substantial issue of plastic debris due to the absence of an efficient waste management infrastructure. Recycled plastic has the potential to enhance various construction materials, such as roofing tiles, paving blocks, and insulation. The aforementioned materials possess notable [...] Read more.
India is confronted with the substantial issue of plastic debris due to the absence of an efficient waste management infrastructure. Recycled plastic has the potential to enhance various construction materials, such as roofing tiles, paving blocks, and insulation. The aforementioned materials possess notable attributes such as high strength, low weight, and exceptional resistance to extreme temperatures and humidity. The objective of this study is to ascertain feasible alternatives for manufacturing road paver blocks utilizing plastic waste (Polyethene terephthalate (PET)), and M-sand (stone dust). Three variations of a discarded plastic cube measuring 150 mm × 150 mm × 150 mm were prepared for the experiment. The experimental findings indicated that a ratio of 1:4 was determined to be the most effective in achieving the desired level of compressive strength. I-section road and brick paver blocks were produced as an alternative to the traditional concrete ones. Compressive strength tests were performed on I-sections and brick paver blocks, revealing that the 1:4 mix ratio exhibited the highest average compressive strength for both materials. The findings indicated that including plastic waste positively impacted the compressive strength of the I-sections and brick paver blocks. Additionally, the quality grading of these materials was evaluated using an ultrasonic pulse velocity test. The ultrasonic pulse velocity test results demonstrated a high-quality grading for the I-sections and brick paver blocks. Scanning electron microscopy (SEM) tests assessed the microstructural behavior and performance. The results of this study demonstrate that incorporating plastic waste in combination with M-sand can effectively improve the mechanical characteristics of composite materials, rendering them viable for use in construction-related purposes. Full article
(This article belongs to the Special Issue Next Generation Infrastructure)
►▼ Show Figures

Figure 1

14 pages, 1926 KiB  
Article
Port-of-Entry Simulation Model for Potential Wait Time Reduction and Air Quality Improvement: A Case Study at the Gateway International Bridge in Brownsville, Texas, USA
by Benjamin Stewart, Hiram Moya, Amit U. Raysoni, Esmeralda Mendez and Matthew Vechione
CivilEng 2023, 4(1), 345-358; https://doi.org/10.3390/civileng4010020 - 20 Mar 2023
Cited by 1 | Viewed by 2161
Abstract
The mathematical study known as queueing theory has recently become a major point of interest for many government agencies and private companies for increasing efficiency. One such application is vehicle queueing at an international port-of-entry (POE). When queueing, fumes from idling vehicles negatively [...] Read more.
The mathematical study known as queueing theory has recently become a major point of interest for many government agencies and private companies for increasing efficiency. One such application is vehicle queueing at an international port-of-entry (POE). When queueing, fumes from idling vehicles negatively affect the overall health and well-being of the community, especially the U.S. Customs and Border Protection (CBP) agents that work at the POEs. As such, there is a need to analyze and optimize the border crossing queuing operations to minimize wait times and number of vehicles in the queue and, thus, reduce the vehicle emissions. For this research, the U.S.–Mexico POE located at The Gateway International Bridge in Brownsville, Texas, is used as a case study. Due to data privacy concerns, the hourly wait times for vehicles arriving at the border had to be extracted manually each day using a live wait time tracker online. The data extraction was performed for the month of March 2022. Using these wait times, a queueing simulation software, SIMIO, was used to develop an interactive simulation model and calibrate the service rates. The output from the SIMIO model was then used to develop an artificial neural network (ANN) to predict hourly particulate matter content with an R2 of 0.402. From the ANN, a predictive equation has been developed, which may be used by CBP to make operational decisions and improve the overall efficiency of this POE. Thus, lowering the average wait times and the emissions from idling vehicles in the queue. Full article
(This article belongs to the Special Issue Next Generation Infrastructure)
►▼ Show Figures

Figure 1

19 pages, 9402 KiB  
Article
Predictive BIM with Integrated Bayesian Inference of Deterioration Models as a Four-Dimensional Decision Support Tool
by Hendrik Morgenstern and Michael Raupach
CivilEng 2023, 4(1), 185-203; https://doi.org/10.3390/civileng4010012 - 21 Feb 2023
Cited by 4 | Viewed by 2347
Abstract
The durability of concrete structures is essential for reliable infrastructure. Although many deterioration models are available, they are rarely applied in situ. For existing structures in need of repair or durability assessment, this is also the case for Building Information Modeling (BIM). However, [...] Read more.
The durability of concrete structures is essential for reliable infrastructure. Although many deterioration models are available, they are rarely applied in situ. For existing structures in need of repair or durability assessment, this is also the case for Building Information Modeling (BIM). However, both BIM and durability modeling hold great potential to both minimize expended resources and maximize the reliability of structures. At the Institute for Building Materials Research (ibac) at RWTH Aachen University, a novel approach to the calibration of deterioration models using Bayesian inference iteratively in a BIM model enriched with machine-readable diagnosis data to achieve a predictive decision support tool is being developed. This paper demonstrates the digital workflow, validates the proposed approach, and expresses the added value for the planning of repair measures. Full article
(This article belongs to the Special Issue Next Generation Infrastructure)
►▼ Show Figures

Figure 1

11 pages, 3272 KiB  
Article
Development of Prediction Model for Rutting Depth Using Artificial Neural Network
by Rami Khalifah, Mena I. Souliman and Mawiya Bin Mukarram Bajusair
CivilEng 2023, 4(1), 174-184; https://doi.org/10.3390/civileng4010011 - 10 Feb 2023
Cited by 4 | Viewed by 2628
Abstract
One of the most common pavement distresses in flexible pavement is rutting, which is mainly caused by heavy wheel load and various other factors. The prediction of rutting depth is important for safe travel and the long-term performance of pavements. Factors that are [...] Read more.
One of the most common pavement distresses in flexible pavement is rutting, which is mainly caused by heavy wheel load and various other factors. The prediction of rutting depth is important for safe travel and the long-term performance of pavements. Factors that are considered in this paper for the prediction of rut depth are Temperature, Equivalent Single Axle Load, Resilient modulus, and Thickness of hot mixed asphalt. The input data for all factors are collected from the Long-Term Pavement Performance Information Management System for the state of Texas. Regression analysis is performed for dependent and independent variables to obtain the empirical relationship. In various fields of civil engineering, artificial neural networks have recently been utilized to model the qualities and behavior of materials and to determine the complicated relationship between various properties. An Artificial Neural Network is used to develop a predictive model to predict the rutting depth. A total number of 70 observations were considered for the predictive model. A mathematical relation is developed and verified between rut depth and variable input data. Full article
(This article belongs to the Special Issue Next Generation Infrastructure)
►▼ Show Figures

Figure 1

29 pages, 8018 KiB  
Article
Assessing Effectiveness of Shape Memory Alloys on the Response of Bolted T-Stub Connections Subjected to Cyclic Loading
by Ahmadreza Torabipour, Nima Asghari, Homa Haghighi, Shaghayegh Yaghoubi and Girum Urgessa
CivilEng 2023, 4(1), 105-133; https://doi.org/10.3390/civileng4010008 - 30 Jan 2023
Cited by 8 | Viewed by 2669
Abstract
This study presents finite element analysis of double split tee (DST) connections with high-strength steel bolts and coupled split tee sections, to evaluate various cyclic response parameters and elements. The investigation included quantifying connection behavior and hysteretic response, damage indexes, and failure modes. [...] Read more.
This study presents finite element analysis of double split tee (DST) connections with high-strength steel bolts and coupled split tee sections, to evaluate various cyclic response parameters and elements. The investigation included quantifying connection behavior and hysteretic response, damage indexes, and failure modes. Over 40 specimens were simulated in ABAQUS under cyclic loading, including shape memory alloy (SMA)-built specimens. In the post-analysis phase, the T-stub thickness, the T-stub yield strength, the bolt preload and bolt number, and the stiffener type and stiffener material for the most significant parts of the DST connection were calculated. Simulation results showed that a lower ultimate moment yielded fewer needed stem bolts. The energy dissipation (ED) capacity increased as the horizontal distance between the stem bolts decreased. Additionally, increasing the strength of the bolt and T-stub by 15% resulted in a 3.86% increase in residual displacement (RD) for the bolt and a 1.73% decrease in residual displacement for the T-stub. T-stub stiffeners enhanced ED capacity by 31.7%. SMA materials were vulnerable to mode 1 failure when used in T-stubs, bolts, or stiffeners. However, the use of SMA increased the rate of energy dissipation. Adding stiffeners to the T-stubs altered the failure indexes and improved the pattern of failure modes. In addition, stiffeners decreased the rupture and pressure indexes. As a result, the failure index of a T-stub shifted from brittle failure to ductile failure. Full article
(This article belongs to the Special Issue Next Generation Infrastructure)
►▼ Show Figures

Figure 1

22 pages, 4866 KiB  
Article
A Three-Phase Model to Evaluate Effects of Phase Diffusivity and Volume Fraction upon the Crack Propagation in Concrete Subjected to External Sulphate Attack
by Chaofan Yi, Zheng Chen, Jiamin Yu and Vivek Bindiganavile
CivilEng 2023, 4(1), 12-33; https://doi.org/10.3390/civileng4010002 - 5 Jan 2023
Cited by 1 | Viewed by 1727
Abstract
This study models concrete as a multi-phase system that comprises the mortar, coarse aggregates, and interfacial transition zones (ITZs). The diffusivity and the volumetric fraction of these phases are considered to propose a three-phase diffusion–reaction model to simulate the external sulphate attack. Furthermore, [...] Read more.
This study models concrete as a multi-phase system that comprises the mortar, coarse aggregates, and interfacial transition zones (ITZs). The diffusivity and the volumetric fraction of these phases are considered to propose a three-phase diffusion–reaction model to simulate the external sulphate attack. Furthermore, the parametric analysis alongside the sensitivity analysis is carried out to quantify the effect of these phases on the expansive cracking in concrete when exposed to a sulphate-rich environment. The results show that mortar dominates the sulphate ingress and the ensuing distress, while the ITZ is found to be least significant. Due to its significantly low permeability, the coarse aggregate may act as a “deceleration strip” or a “dam”, which in turn obstructs the sulphate penetration. More importantly, this effect is further noted to evolve with a decrease in the diffusivity and a rise in the volumetric fraction of coarse aggregates. As for ITZ, its volume fraction may play a more dominant role than its diffusivity on sulphate attack in concrete. Full article
(This article belongs to the Special Issue Next Generation Infrastructure)
►▼ Show Figures

Figure 1

11 pages, 6160 KiB  
Article
Assessment of Infrastructure Reliability in Expansive Clays Using Bayesian Belief Network
by Golam Kabir and Shahid Azam
CivilEng 2022, 3(4), 1126-1136; https://doi.org/10.3390/civileng3040064 - 18 Dec 2022
Viewed by 1700
Abstract
Civil infrastructure supported by expansive clays is severely affected by extensive volumetric deformations. The reliability prediction of such facilities is quite challenging because of the complex interactions between several contributing factors, such as a scarcity of data, a lack of analytical equations, correlations [...] Read more.
Civil infrastructure supported by expansive clays is severely affected by extensive volumetric deformations. The reliability prediction of such facilities is quite challenging because of the complex interactions between several contributing factors, such as a scarcity of data, a lack of analytical equations, correlations between quantitative and qualitative information, and data integration. The main contribution of this research is the development of a modeling approach based on the Bayesian belief network. The modeling results highlight that facility age is the most critical parameter (23% variance), followed by facility type (1.37% variance), for all the investigated types of infrastructure, namely road embankments, buried pipelines, and residential housing. Likewise, the results of sensitivity analysis and extreme scenario analysis indicate that the new method is capable of predicting infrastructure reliability and the assessments were found to be in agreement with expected field behavior. The proposed model is useful in decision making related to civil infrastructure management in expansive clays. Full article
(This article belongs to the Special Issue Next Generation Infrastructure)
►▼ Show Figures

Figure 1

14 pages, 5097 KiB  
Article
Assessing the Rainfall Water Harvesting Potential Using Geographical Information Systems (GIS)
by Afzal Ahmed, Manousos Valyrakis, Abdul Razzaq Ghumman, Muhammad Arshad, Ghufran Ahmed Pasha, Rashid Farooq and Shahmir Janjua
CivilEng 2022, 3(4), 895-908; https://doi.org/10.3390/civileng3040051 - 12 Oct 2022
Cited by 4 | Viewed by 4298 | Correction
Abstract
Water scarcity is a major issue for developing countries due to the continuous increase in population every year, the major environmental challenges faced by developing countries such as Pakistan being the scarcity of water. One proposed solution to meet the requirements is to [...] Read more.
Water scarcity is a major issue for developing countries due to the continuous increase in population every year, the major environmental challenges faced by developing countries such as Pakistan being the scarcity of water. One proposed solution to meet the requirements is to conserve water from rainfall. The process consists of the collection, storage, and use of rainwater. The rooftop rainwater harvesting systems (RWH) and rainfall harvesting system for artificially recharged water by recharge wells have received increased attention in the recent past as an efficient means of water conservation. In this study, both the systems have been analyzed for the University of Engineering and Technology Taxila (UET Taxila), Pakistan. The objective of this study is to propose a system to harvest water from the rooftops of all of the buildings on the campus and also to propose the most optimum locations of recharge wells for the artificial recharge of groundwater development. Numerous field visits were conducted after every rainfall over the past few months to identify lower elevation areas, which were further validated by the results obtained by Arc GIS. The total area of catchments available for rainwater harvesting in UET Taxila and the amount of water that could be harvested or used for replenishing groundwater reserves were also assessed in the current study. The results show that the harvestable rooftop water per month is 59% of the currently available source for watering trees and plants, and the harvestable water by recharge wells is 761,400 ft3 per year. Full article
(This article belongs to the Special Issue Next Generation Infrastructure)
►▼ Show Figures

Figure 1

23 pages, 1895 KiB  
Article
Scrutinizing Competitiveness of Construction Companies Based on an Integrated Multi-Criteria Decision Making Model
by Ahmed Badawy, Abobakr Al-Sakkaf, Ghasan Alfalah, Eslam Mohammed Abdelkader and Tarek Zayed
CivilEng 2022, 3(4), 850-872; https://doi.org/10.3390/civileng3040049 - 28 Sep 2022
Cited by 1 | Viewed by 3535
Abstract
The construction sector continues to experience significant challenges brought by new techniques and technologies. Hence, there is a dire need for construction companies to address critical issues concerning changing environmental conditions, construction innovations, market globalization and many other aspects, thereby enhancing their competitive [...] Read more.
The construction sector continues to experience significant challenges brought by new techniques and technologies. Hence, there is a dire need for construction companies to address critical issues concerning changing environmental conditions, construction innovations, market globalization and many other aspects, thereby enhancing their competitive edge. Thus, the primary goal for this research is to develop a multi-criteria decision making model that would consider and evaluate all essential factors in determining the competitiveness index of construction companies. In the developed model, three new pillars (3P) for competitiveness are introduced: (1) non-financial internal pillar; (2) non-financial external pillar; and (3) financial pillar. The 3P includes 6 categories and 26 factors that are defined and incorporated in the developed assessment model for the purpose of measuring the companies’ competitiveness. The weights for the identified factors are computed using fuzzy analytical network process (FANP) to diminish the uncertainty inherited within the judgment of the respondents. The weight of factors and their affiliated performance scores are used as an input for the preference ranking organization method for enrichment evaluation (PROMETHEE II) technique. In this regard, PROMETHEE II is undertaken as a ranking technique to prioritize any given construction company by determining its respective competitiveness index. The developed model is validated through five cases studies that reveal its potential of illustrating detailed analysis with respect to the competitive ability of construction companies. A sensitivity analysis is carried out to determine the most influential factors that affect the competitiveness of construction companies. It is anticipated that the developed evaluation model can be used in the decision-making process by all parties involved in construction projects. For instance, contractors can leverage the evaluation model in taking better decisions pertinent to the markup values. In addition, it can benefit employers in the evaluation process of contractors. Full article
(This article belongs to the Special Issue Next Generation Infrastructure)
►▼ Show Figures

Figure 1

Other

Jump to: Research

1 pages, 150 KiB  
Correction
Correction: Ahmed et al. Assessing the Rainfall Water Harvesting Potential Using Geographical Information Systems (GIS). CivilEng 2022, 3, 895–908
by Afzal Ahmed, Manousos Valyrakis, Abdul Razzaq Ghumman, Muhammad Arshad, Ghufran Ahmed Pasha, Rashid Farooq and Shahmir Janjua
CivilEng 2024, 5(2), 501; https://doi.org/10.3390/civileng5020025 - 30 May 2024
Viewed by 712
Abstract
In the original publication [1], there were two mistakes in relation to the cited references (within the References section) as follows:Reference 52 (Xin-gang et al [...] Full article
(This article belongs to the Special Issue Next Generation Infrastructure)
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-10
Back to TopTop