Infrastructures

23 pages, 11038 KiB

Open AccessArticle

Flood Risk Assessment Index for Urban Mobility with the Aid of Quasi-2d Flood Model Applied to an Industrial Park in São Paulo, Brazil

by Matheus Martins de Sousa, Osvaldo Moura Rezende, Ana Caroline Pitzer Jacob, Luiza Batista de França Ribeiro, Paula Morais Canedo de Magalhães, Gladys Maquera and Marcelo Gomes Miguez

Infrastructures 2022, 7(11), 158; https://doi.org/10.3390/infrastructures7110158 - 18 Nov 2022

Cited by 1 | Viewed by 4639

Abstract

Risk can be defined as the relationship between the likelihood of a hazard causing a potential disaster and its consequences. This study aims to assess the likelihood that a new industrial region, located in the state of São Paulo (Brazil), will be flooded, [...] Read more.

Risk can be defined as the relationship between the likelihood of a hazard causing a potential disaster and its consequences. This study aims to assess the likelihood that a new industrial region, located in the state of São Paulo (Brazil), will be flooded, causing the disruption of the mobility system and local economic activities. To fulfill this aim, a new approach is proposed by combining the vector information of the highway network that serves the region with the result of a quasi 2-D raster flood model, generating a set of interpreting rules for classifying the safety of routes. The model called MODCEL is a quasi-2D hydrodynamic model that represents the watershed using compartments called cells, and it was adapted to work using a raster file format in which each pixel is represented as a flow cell connected to its surroundings by the Saint-Venant equations without the inertia terms. Therefore, this study proposes an assessment framework that can be replicated for similar problems of flood risks to mobility. The possible effects of flood events on the accessibility to areas of interest are determined, indicating a possible disruption to economic activities and transportation and allowing for planning alternatives in advance. Full article

(This article belongs to the Special Issue Smart, Sustainable and Resilient Infrastructures, 2nd Edition)

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22 pages, 2569 KiB

Open AccessArticle

Multi-Objective Optimization of Base-Isolated Tanks with Supplemental Linear Viscous Dampers

by Alexandros Tsipianitis and Yiannis Tsompanakis

Infrastructures 2022, 7(11), 157; https://doi.org/10.3390/infrastructures7110157 - 17 Nov 2022

Cited by 3 | Viewed by 2250

Abstract

Base isolation of liquid storage tanks has proven to be an efficient seismic protection measure, leading to a drastic reduction of a superstructure’s distress. However, many such tanks are located near seismic tectonic faults, which generate strong pulse-like ground motions that can impose [...] Read more.

Base isolation of liquid storage tanks has proven to be an efficient seismic protection measure, leading to a drastic reduction of a superstructure’s distress. However, many such tanks are located near seismic tectonic faults, which generate strong pulse-like ground motions that can impose excessive displacement demands on the isolators. For this reason, viscous dampers are incorporated into the isolation system to avoid overconservative isolators design. To optimize the seismic performance of hybrid isolation systems consisting of single friction pendulum bearings and linear viscous dampers, two novel multi-objective optimization approaches are proposed in the current study. Furthermore, suitable constraint functions and design variables are selected, considering the most critical parameters of the hybrid isolation system. The multi-objective genetic algorithm optimizer is used for the solution of both problems. The results are presented in the typical form of Pareto and certain optimal design solutions are carefully chosen and compared in terms of isolators fragility curves and tank accelerations. The main aim is to optimize the critical design parameters by achieving a reasonable balance among contradicting objectives. The tank industry can substantially benefit from this study, as a more cost-efficient design of hybrid base-isolation can be attained for large-scale tanks. Full article

(This article belongs to the Special Issue Advances in Structural Dynamics and Earthquake Engineering)

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17 pages, 495 KiB

Open AccessArticle

Determination of Shear Capacity for Load Rating of Concrete Bridges to AS 5100.7-2017

by Koon Wan Wong and Vanissorn Vimonsatit

Infrastructures 2022, 7(11), 156; https://doi.org/10.3390/infrastructures7110156 - 17 Nov 2022

Viewed by 2506

Abstract

According to Modified Compression Field Theory (MCFT), the ultimate shear capacity of a reinforced concrete section depends on load effects (shear, moment, torsion, and axial force) caused by factored design loads. In many design standards, including Australian AS 5100.7, MCFT has been incorporated [...] Read more.

According to Modified Compression Field Theory (MCFT), the ultimate shear capacity of a reinforced concrete section depends on load effects (shear, moment, torsion, and axial force) caused by factored design loads. In many design standards, including Australian AS 5100.7, MCFT has been incorporated for bridge assessment, which requires a load rating to be carried out according to the loading of the nominated rating vehicle as prescribed in the standard. Recently, some approaches have been proposed for bridge load rating that have suggested using an iterative-search procedure to determine the shear capacity by proportionally increasing the load effects until the shear capacity and shear are equal. This paper describes several adverse effects of using the proportional load, which is not consistent with the characteristic of the vehicle loading, to determine the shear capacity for load rating. Numerical examples of two bridge beams, one simply supported and the other continuous, are presented to demonstrate that the characteristic of the load effects caused by a moving vehicle is not representable by proportional load effects. Furthermore, the current practice in the bridge load rating does not load rate the longitudinal steel capacity in resisting the axial force induced by the load effects of the rating vehicle. This paper presents a new approach to the load rating that separately accounts for the load effect for axial failure mode of the longitudinal steel. Finally, it is pointed out that locating the critical section where the rating factor is minimum is tedious but can be automated by integrating load rating into the analysis of load effects. Full article

(This article belongs to the Topic Life Cycle Assessment of Deteriorating Structures and Infrastructure)

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30 pages, 17028 KiB

Open AccessArticle

A Geotechnical Perspective on a Complex Geological Environment in a High-Speed Railway Tunnel Excavation (A Case Study from Türkiye)

by Candan Gokceoglu, Ebu Bekir Aygar, Hakan A. Nefeslioglu, Servet Karahan and Suat Gullu

Infrastructures 2022, 7(11), 155; https://doi.org/10.3390/infrastructures7110155 - 14 Nov 2022

Cited by 5 | Viewed by 3825

Abstract

The T26 tunnel was designed within the scope of the Ankara-Istanbul high-speed railway in accordance with the speed of 250 km/h. Some serious problems and excessive deformations were encountered during the excavation works. The deformations in the tunnel caused subsidence on the surface [...] Read more.

The T26 tunnel was designed within the scope of the Ankara-Istanbul high-speed railway in accordance with the speed of 250 km/h. Some serious problems and excessive deformations were encountered during the excavation works. The deformations in the tunnel caused subsidence on the surface and the Tunnel Boring Machine (TBM) became stuck; therefore, tunnel excavation works were suspended. Design works for re-excavation in the T26 tunnel and extracting of the TBM were carried out and the tunnel was re-designed by the New Austrian Tunneling Method (NATM) system. The main purposes of the present study are to describe the problems encountered during the T26 tunnel and to discuss the sources of the problems. The advantages and disadvantages of TBM and NATM methods for the tunnel having difficult ground conditions were discussed. Critical points needing to be considered for the tunnels excavated with TBM through weak ground conditions and the effect of the TBM selection process were discussed. Considering the complex geological and geotechnical structure of the tunnel route, it is possible to say that the T26 case is an interesting case for tunnel engineering. Along the tunnel route, landslides, high seismic activity, groundwater conditions, and extremely weak rock mass features coexist. Therefore, the tunnel route is a very complex environment. However, due to the geometric limitations of the high-speed railways, relocation of the route is not possible. The experiences gained from tunnel excavations under difficult conditions are capable of bringing new horizons to future tunneling studies. Full article

(This article belongs to the Topic Resilient Civil Infrastructure)

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22 pages, 3720 KiB

Open AccessReview

High-Speed Railway Bridge and Pile Foundation: A Review

by Brian Bachinilla, Ana Evangelista, Milind Siddhpura, Assed N. Haddad and Bruno B. F. da Costa

Infrastructures 2022, 7(11), 154; https://doi.org/10.3390/infrastructures7110154 - 11 Nov 2022

Cited by 5 | Viewed by 6746

Abstract

High-speed railway is trending in developing countries for economic reasons, mobility in the aftermath of COVID-19, and environmental concerns. The high-speed railway operators continuously improve the operational speed to transport more passengers in less time. However, increasing the train loads at high speed [...] Read more.

High-speed railway is trending in developing countries for economic reasons, mobility in the aftermath of COVID-19, and environmental concerns. The high-speed railway operators continuously improve the operational speed to transport more passengers in less time. However, increasing the train loads at high speed might increase the dynamic loads of bridges and affect their pile foundation. A stiffer railway bridge is mandatory for high-speed train safety and passenger riding comfort. However, a flexible bridge is ideal for responding to earthquakes. Thus, these two objectives are conflicting. This review paper provides a bibliometric review aiming to determine the published studies by year and by country, and to visualize different research trends in cluster maps using the VOSviewer software, summarizing the published research for high-speed railway bridges starting from 1964. The review also extracted information from the latest studies by summarizing some essential objectives, useful methodologies, and notable findings that might be applicable to future studies. In conclusion, there is a need for further research to fill the knowledge gap in the study related to the soil–structure interaction phenomenon considering the performance-based seismic design of a high-speed railway bridge on a monopile foundation in the event of lateral spreading due to soil liquefaction. Full article

(This article belongs to the Special Issue Smart, Sustainable and Resilient Infrastructures, 2nd Edition)

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26 pages, 5747 KiB

Open AccessArticle

Evaluating the Role of Urban Drainage Flaws in Triggering Cascading Effects on Critical Infrastructure, Affecting Urban Resilience

by Antonio Krishnamurti Beleño de Oliveira, Bruna Peres Battemarco, Giuseppe Barbaro, Maria Vitória Ribeiro Gomes, Felipe Manoel Cabral, Ronan de Oliveira Pereira Bezerra, Victória de Araújo Rutigliani, Ianic Bigate Lourenço, Rodrigo Konrad Machado, Osvaldo Moura Rezende, Paulo Canedo de Magalhães, Aline Pires Veról and Marcelo Gomes Miguez

Infrastructures 2022, 7(11), 153; https://doi.org/10.3390/infrastructures7110153 - 11 Nov 2022

Cited by 11 | Viewed by 3734

Abstract

The urban drainage system plays an important role in the urban infrastructure resilience discussion. Its functional failures can trigger cascading effects on other urban systems and critical infrastructures. The main aim of this work is to investigate and quantify urban flood resilience, offering [...] Read more.

The urban drainage system plays an important role in the urban infrastructure resilience discussion. Its functional failures can trigger cascading effects on other urban systems and critical infrastructures. The main aim of this work is to investigate and quantify urban flood resilience, offering an integrated methodological approach. In this process, the flooding consequences were quantified by hydrodynamic simulations, using a case study in an exploratory research method. A set of indicators was proposed to map the cascading effects generated by floods and the consequent quantification of urban flooding resilience. Two simulation scenarios were proposed to validate the methodological assessment framework proposed in this work. The first scenario represented the current flooding situation and showed the negative effects on the city systems resulting from disordered urban growth. The second scenario considered the improvement of the drainage behavior, considering a sustainable urban drainage approach supported by the concept of blue-green infrastructure integrated with the urban open spaces system. A comprehensive flood resilience assessment over time was conducted by analyzing the evolution of the System Integrity Index on both scenarios. The results showed that water dynamics play an important role in ordering land use and that preserving water spaces can efficiently respond to urban developing threats, dealing with floods in an earlier development moment, proving the importance of the drainage system as a preliminary structuring driver for supporting a sustainable urban planning, ordered according to environmental constraints defined by water dynamics. Full article

(This article belongs to the Special Issue Smart, Sustainable and Resilient Infrastructures, 2nd Edition)

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Graphical abstract

12 pages, 2189 KiB

Open AccessArticle

Crack Detection and Classification in Moroccan Pavement Using Convolutional Neural Network

by Wafae Hammouch, Chaymae Chouiekh, Ghizlane Khaissidi and Mostafa Mrabti

Infrastructures 2022, 7(11), 152; https://doi.org/10.3390/infrastructures7110152 - 10 Nov 2022

Cited by 18 | Viewed by 3304

Abstract

Crack is a condition indicator of the pavement’s structure. Generally, crack detection is an essential task for effective diagnosis of the road network. Moreover, evaluation of road quality is necessary to ensure traffic security. Since 2011, a periodic survey of approximately 57,500 km [...] Read more.

Crack is a condition indicator of the pavement’s structure. Generally, crack detection is an essential task for effective diagnosis of the road network. Moreover, evaluation of road quality is necessary to ensure traffic security. Since 2011, a periodic survey of approximately 57,500 km of Moroccan roads has been performed using an inspection vehicle (SMAC) which is equipped with high resolution cameras and GPS/DGPS receivers. Until recently, the teams of the National Center for Road Studies and Research (CNER) analyzed road surface states by visualization of pavement surface image sequences captured by the Multifunctional Pavement Assessment System (SMAC) in order to detect defects in road surfaces and classify them according to their type. However, this method involves manual processing and is complex, time consuming and subjective. In this paper, we propose an automated methodology for crack detection and classification in Moroccan flexible pavements using Convolutional Neural Networks (CNN). Transfer learning is also applied by testing a pre-trained Visual Geometry Group 19 (VGG-19) model. For the dataset used in this paper, the results indicate that good crack detection and classification are achieved using both models. Full article

(This article belongs to the Special Issue Land Transport, Vehicle and Railway Engineering)

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17 pages, 6171 KiB

Open AccessArticle

Performance Evaluation of Carrying Capacity of Prestressed Bearers for Railway Turnouts Using Laboratory Experiments in Vietnam

by Tran Anh Dung and Said M. Easa

Infrastructures 2022, 7(11), 151; https://doi.org/10.3390/infrastructures7110151 - 8 Nov 2022

Viewed by 1752

Abstract

Previous studies have addressed railway turnouts (switches and crossings), but research on the performance of 1000 mm gauge turnouts is limited. At present, wooden sleeper structures are used at turnouts in Vietnam. However, these structures have many disadvantages in the operation process. This [...] Read more.

Previous studies have addressed railway turnouts (switches and crossings), but research on the performance of 1000 mm gauge turnouts is limited. At present, wooden sleeper structures are used at turnouts in Vietnam. However, these structures have many disadvantages in the operation process. This paper evaluates the performance of new prestressed bearer (PSB) for turnouts, designed for the 1000 mm gauge, to overcome the disadvantages of a wooden sleeper. Test samples of PSB were manufactured in the factory, and experiments were conducted in the laboratory according to European Standards to evaluate the PSB carrying capacity. The test results show that the proposed structure meets the carrying capacity under the standard test loads. In addition, the results of the static and fatigue tests of the bearers show a considerable reserve in the cross-section capacity. This means that the existing reserve can be used with a larger locomotive axle, and the bearer design can be optimized by arranging the prestressed strands and changing the bearer cross-section’s geometric dimensions. It is hoped that the proposed bearer design will be a viable alternative for designing railway turnouts. Full article

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21 pages, 11306 KiB

Open AccessArticle

Deep-Learning-Based Temporal Prediction for Mitigating Dynamic Inconsistency in Vehicular Live Loads on Roads and Bridges

by Ananta Sinha, Mi G. Chorzepa, Jidong J. Yang, Sung-Hee Sonny Kim and Stephan Durham

Infrastructures 2022, 7(11), 150; https://doi.org/10.3390/infrastructures7110150 - 31 Oct 2022

Cited by 2 | Viewed by 1964

Abstract

Weigh-In-Motion (WIM) data have been collected by state departments of transportation (DOT) in the U.S. and are anticipated to grow as state DOTs expand the number of WIM sites in order to better manage transportation infrastructure and enhance mobility. Traditional approaches for monitoring [...] Read more.

Weigh-In-Motion (WIM) data have been collected by state departments of transportation (DOT) in the U.S. and are anticipated to grow as state DOTs expand the number of WIM sites in order to better manage transportation infrastructure and enhance mobility. Traditional approaches for monitoring the vehicle weight measured in WIM systems include conducting statistical tests between two datasets obtained from two calibration visits. Depending on the frequency of visits, these traditional approaches are ineffective or resource-demanding for identifying calibration needs. Excessive vehicle-weight drifts exceeding 10% are usually indicative of poor performance by WIM systems. However, it has been difficult to consistently monitor such performance due to the sheer amount of data. In Georgia, the number of WIM sites have expanded from 12 to 29 in the past 3 years. This paper proposes a deep-learning-based temporal prediction approach for modeling sequential data and monitoring the time-history of the live loads imposed on roads and bridges. In total, 29 WIM sites in Georgia are analyzed to examine the effectiveness of a proposed temporal prediction approach for evaluating observed live loads. This study finds that the Jensen–Shannon divergence method is more effective than statistical difference tests, particularly when screening for live load anomalies. It is concluded that a LSTM neural network is able to capture temporal dynamics underlying the sequential load patterns observed in the WIM data and serves as an effective model for consistently monitoring the performance of WIM systems over time. Full article

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15 pages, 2516 KiB

Open AccessArticle

Development of Detailed Mix Design Methodology for Low Calcium Fly Ash Based Geopolymer Concrete Incorporating OPC and Crumb Rubber

by Parmender Gill and Parveen

Infrastructures 2022, 7(11), 149; https://doi.org/10.3390/infrastructures7110149 - 26 Oct 2022

Cited by 7 | Viewed by 2784

Abstract

This experimental study proposes a systematic mix-design procedure to develop rubberized geopolymer concrete (RGPC). The developed method is meant to identify the mix ratios for the production of high-strength, low-calcium fly ash-based geopolymer concrete, with OPC as a supplementary binder and crumb rubber [...] Read more.

This experimental study proposes a systematic mix-design procedure to develop rubberized geopolymer concrete (RGPC). The developed method is meant to identify the mix ratios for the production of high-strength, low-calcium fly ash-based geopolymer concrete, with OPC as a supplementary binder and crumb rubber as a partial replacement for the fine aggregates. The binder (80% fly ash + 20% OPC) content (350, 375, and 400 kg/m³), crumb rubber percentage (0, 5, 10, and 15%), and NaOH molarity (8, 10, and 12 M) are identified as key variables, with the focus on attaining the targeted compressive strength and workability under heat curing (60 °C). Thirty-six mix designs were tested for their compressive strength after 7 and 28 days, and their graphical relationship with the chosen variables is presented (CR-GPC graphs). A trial experiment with an example is performed to establish the validity of the developed mix-design procedure. It was found that the targeted compressive strength and slump of the rubberized GPC can be achieved with conviction. Full article

(This article belongs to the Section Infrastructures and Structural Engineering)

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24 pages, 8164 KiB

Open AccessArticle

Data-Driven Prediction of Stability of Rock Tunnel Heading: An Application of Machine Learning Models

by Chayut Ngamkhanong, Suraparb Keawsawasvong, Thira Jearsiripongkul, Lowell Tan Cabangon, Meghdad Payan, Kongtawan Sangjinda, Rungkhun Banyong and Chanachai Thongchom

Infrastructures 2022, 7(11), 148; https://doi.org/10.3390/infrastructures7110148 - 26 Oct 2022

Cited by 25 | Viewed by 2892

Abstract

In this paper, Artificial Neural Networks (ANN) have been utilized to predict the stability of a planar tunnel heading in rock mass based on the well-defined Hoek-Brown (HB) yield criterion. The HB model was developed to capture the failure criterion of rock masses. [...] Read more.

In this paper, Artificial Neural Networks (ANN) have been utilized to predict the stability of a planar tunnel heading in rock mass based on the well-defined Hoek-Brown (HB) yield criterion. The HB model was developed to capture the failure criterion of rock masses. To provide the datasets for an ANN model, the numerical upper bound (UB) and lower bound (LB) solutions obtained from the finite element limit analysis (FELA) with the HB failure criterion for the problem of tunnel headings are derived. The sensitivity analysis of all influencing parameters on the stability of rock tunnel heading is then performed on the developed ANN model. The proposed solutions will enhance the dependability and preciseness of predicting the stability of rock tunnel heading. Note that the effect of the unlined length ratio has not been explored previously but has been found to be of critical importance and significantly contributes to the failure of rock tunnel heading. By utilizing the machine learning-aided prediction capability of the ANN approach, the numerical solutions of the stability of tunnel heading can be accurately predicted, which is better than the use of the classic linear regression approach. Thus, providing a better and much safer assessment of mining or relatively long-wall tunnels in rock masses. Full article

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18 pages, 4675 KiB

Open AccessArticle

Physical Model of Shallow Foundation under Dynamic Loads on Sands

by Diego F. Gil, Cristhian C. Mendoza, Luis R. Vásquez-Varela and Santiago Cano

Infrastructures 2022, 7(11), 147; https://doi.org/10.3390/infrastructures7110147 - 25 Oct 2022

Cited by 7 | Viewed by 2764

Abstract

Structures built on sands worldwide, with shallow foundations, have experienced damage and collapse during and after earthquakes. Two phenomena triggered the collapse: the liquefaction phenomenon and the P-Δ effects. However, current research and practice do not fully understand granular soil behavior during [...] Read more.

Structures built on sands worldwide, with shallow foundations, have experienced damage and collapse during and after earthquakes. Two phenomena triggered the collapse: the liquefaction phenomenon and the P-Δ effects. However, current research and practice do not fully understand granular soil behavior during liquefaction and P-Δ effects, as proven by the sum of investigations on physical models, constitutive models, and laboratory testing proposals about these topics. A question appears at this point: what is the relationship between excitation frequency, displacement amplitude, and the triggering of overturning? To cope with this issue, the authors propose to create a physical 1-g model composed of a single-degree-of-freedom oscillator (SDOFO) capable of transmitting cyclic loadings to the soil in rocking vibration mode. The measurement methodology was based on computer vision using OpenCV by Python, which allowed the “free movement” of the SDOFO. The authors use computer vision as a suitable way to obtain displacements and times without sensors placed directly in the physical model. According to the results, it was possible to define an inversely non-linear relationship between frequency, displacement amplitude, and the total cycles required to reach overturning for different effective grain-size (D₁₀). Full article

(This article belongs to the Special Issue Artificial Intelligence in Infrastructure Geotechnics)

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20 pages, 870 KiB

Open AccessArticle

Evaluation of Climate Change Resilience of Urban Road Network Strategies

by Siama Begum, Rachel S. Fisher, Emma J. S. Ferranti and Andrew D. Quinn

Infrastructures 2022, 7(11), 146; https://doi.org/10.3390/infrastructures7110146 - 25 Oct 2022

Cited by 2 | Viewed by 3498

Abstract

The impacts of the changing climate have caused extensive disruption to the road network in the United Kingdom in recent years. Roads are vital for economic growth and social wellbeing, and a disruption to the network can have disastrous consequences. Since the impacts [...] Read more.

The impacts of the changing climate have caused extensive disruption to the road network in the United Kingdom in recent years. Roads are vital for economic growth and social wellbeing, and a disruption to the network can have disastrous consequences. Since the impacts of climate change will be felt at regional and local levels, it is the responsibility of local highway authorities to establish effective policies to strengthen the resilience of their section of the road network. This report uses the West Midlands as a case study and aims to evaluate its regional highway network management strategies, to determine the extent to which they promote resilience to climate change. Recommendations and findings from other literature are used to establish a set of evaluation criteria to compare the maturity of highway network management strategies for the West Midlands region. The evaluation of the policy documents is used to rank the maturity of the strategies, and recommendations are made to local authorities to highlight where the strategies could be improved. The analysis highlights the fragmentation and disparity between highways strategies across the region and consequently the vulnerability of the region to climate change. Full article

(This article belongs to the Special Issue Critical Infrastructure Resilience Facing Extreme Weather Events)

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Infrastructures, Volume 7, Issue 11 (November 2022) – 13 articles

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