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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 14634

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Special Issue Editors

Prof. Dr. Wenwei Wang

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Guest Editor

Department of Bridge Engineeing, Southeast University, Nanjing, China
Interests: bridge engineering; composite material; structure retrofitting; disaster mitigation
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Prof. Dr. Shan Li

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Guest Editor

School of Civil Engineering, Wuhan University, No.8 Donghu South Road, Wuhan 430072, China
Interests: bridge engineering; high performance composite materials; corrosion of steel reinforcement in concrete structures
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Dr. Yi Bao

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Department of Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA
Interests: structural health monitoring; distributed sensing; machine learning; advanced cementitious composites
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Dr. Yazhou (Tim) Xie

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Guest Editor

Department of Civil Engineering and Applied Mechanics, McGill University, Montreal, QC H3A 0G4, Canada
Interests: bridge engineering; performance-based earthquake engineering; soil-structure interaction; smart material and device; statistical and machine learning; regional risk assessment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Physical infrastructures, such as bridges, tunnels, and retaining walls, are prone to damage from disaster hazards, such as earthquakes, hurricanes, fires, impacts, and blast loadings. Failure of such infrastructures could lead to direct and indirect costs for the economy and society. Therefore, there is an urgent need to provide innovative and intelligent solutions for structural sustainability. An important theme under investigation is that of improving the structure resistance to disasters with innovative materials, such as shape memory alloys (SMAs) and high-performance cementitious composites. Additionally, engaging intelligent solutions, such as smart health monitoring systems based on machine learning and computer vision, is also a promising approach for the maintenance of bridges and other infrastructures.

This Special Issue is a gathering for innovative ideas on various aspects of sustainable structures and aims to explore the future of intelligent solutions especially for the design, construction, and maintenance of bridges and other physical infrastructures.

In this context, we are pleased to announce this Special Issue with the general theme of “Intelligent Solutions for the Sustainability of Bridges and Structures”. Possible topics include, but are not limited to, the following:

Reinforced concrete structures;
Disaster hazards;
Structural safety;
Structural dynamics;
Innovative retrofitting materials;
Computational dynamic simulation;
Smart structural health monitoring solutions;
Machine learning;
Computer vision.

We invite researchers and experts to submit original research and review articles that describe the state of the art and further stimulate innovations in the relevant fields.

Prof. Dr. Wenwei Wang
Prof. Dr. Shan Li
Dr. Yi Bao
Dr. Yazhou (Tim) Xie
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. Sustainability 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

structural reliability
structural retrofitting
structural dynamics
structural health monitoring
artificial intelligence

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Published Papers (9 papers)

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Research

19 pages, 7285 KiB

Open AccessArticle

Experimental Study on the Static Behavior and Recovery Properties of CFRP/SMA Composites

by Chu-Sheng He, Wen-Wei Wang, Yi-Xing Tang and Yan-Jie Xue

Sustainability 2023, 15(17), 13078; https://doi.org/10.3390/su151713078 - 30 Aug 2023

Cited by 2 | Viewed by 1199

Abstract

Strengthening reinforced concrete elements with externally bonded prestressed fiber reinforced polymer (FRP) sheets has become a popular reinforcement technology in recent years. However, in practical engineering applications, due to the limitations of construction operation space and the need for specialized design of tensioning and anchoring devices, it is very cumbersome to apply prestressing force to FRP sheets. Therefore, using the recovery effect of shape memory alloys (SMA) to introduce prestressing into FRP sheets can innovate a new approach by combining FRP sheets and SMA wires. In order to study the basic mechanical properties of FRP/SMA composites, carbon fiber reinforced polymer and shape memory alloys were used to make the composite specimens, and uniaxial tensile tests were carried out on them. The mechanical properties such as the stress-strain curve, failure mode, ultimate tensile strength and fracture strain were obtained. The test results show that CFRP sheet exhibits obvious linear elastic behavior in tensile tests. The stress-strain curve of SMA wire can be divided into four stages: the linear elastic stage, yield stage, strengthening stage and failure stage. The fracture strain at failure can reach 7%, which indicates excellent deformation properties. The loading and unloading cycles have little effect on the mechanical properties of SMA wire. With the increase in the loading rate, the ‘stress plateau’ section of the phase transformation section of the SMA wire hysteresis curve gradually transits to an oblique upward curve. Increasing the pre-strain value within a certain range can improve the resilience of SMA wires. SMA wires with a pre-strain value of 8% can provide a maximum resilience of 514 MPa after heating to the austenitic state. A prediction model for the number of temperature cycles and maximum recovery force of SMA was proposed and validated. According to this model, the SMA wires can still provide stable resilience after 30 cycles. Increasing the amount of wire (volume ratio) can improve the maximum fracture strain and ultimate tensile strength of CFRP/SMA composite specimens, and the more wire is added, the greater the residual strength after fracture. The diameter of the fiber can significantly reduce the maximum fracture strain and ultimate tensile strength of the FRP/SMA composite specimen. Full article

(This article belongs to the Special Issue Intelligent Solutions for the Sustainability of Bridges and Structures)

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17 pages, 5084 KiB

Open AccessArticle

Energy-Based Evaluation on Soil–Structure-Interaction-Related Damping of Inelastic Bridge Pier Structure Subjected to Pulse-like Velocity Ground Motion

by Kuo-Hung Chao, Yu-Chi Sung, Xiao-Qin Liu and Chin-Kuo Su

Sustainability 2023, 15(9), 7401; https://doi.org/10.3390/su15097401 - 29 Apr 2023

Cited by 1 | Viewed by 1282

Abstract

This study proposed a procedure of using the energy method to evaluate the SSI-related damping effect when the soil–structure interaction (SSI) was considered in a bridge pier system, which can thus be deemed a soil–foundation–superstructure (SFS) inelastic system. Firstly, the SSI is implemented by adopting a discrete-time recursive filter approach as well as frequency-dependent foundation–soil impedance functions to solve for the external soil forces exerted onto the foundation. Then, by integrating such external soil forces into the motion equations of the SSI-based SFS system, the energy equations can be formulated during the ground motions. To demonstrate the proposed procedure, an implementation study involving a bridge pier was carried out, considering two earthquake recordings. The resultant energy quantities and SSI-related damping ratio shed light on how the aspects of earthquake characteristics affected the energy dissipation mechanism of the bridge pier SSI-based SFS system. This proposed procedure renders a promising solution for quantifying the soil role in the seismic energy dissipation of arbitrary single- and multiple-degree-of-freedom systems considering the SSI effect. The results obtained show that the SSI effect was suppressed when the SFS system underwent near-fault earthquakes, which illustrated that the stiffness and damping contribution from the soil was not pronounced. Furthermore, near-fault earthquakes with large incremental velocities may lead to a low SSI-related damping ratio (SSIDR). Full article

(This article belongs to the Special Issue Intelligent Solutions for the Sustainability of Bridges and Structures)

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16 pages, 1949 KiB

Open AccessArticle

Modeling the Cause-and-Effect Relationships between the Causes of Damage and External Indicators of RC Elements Using ML Tools

by Roman Trach, Galyna Ryzhakova, Yuliia Trach, Andrii Shpakov and Volodymyr Tyvoniuk

Sustainability 2023, 15(6), 5250; https://doi.org/10.3390/su15065250 - 15 Mar 2023

Cited by 5 | Viewed by 1744

Abstract

Reinforced concrete (RC) structures are used in a wide range of applications, including high-rise buildings, nuclear power plants, oil and gas platforms, bridges, and other infrastructure. However, over time, RC structures can be subject to deterioration and damage, particularly from exposure to weather and environmental conditions, heavy traffic loads, and other factors. Regular inspections, diagnosing the condition, maintenance, and repair can help to mitigate the effects of degradation and extend the life of the structure. The task of this study was to determine the possible causes of the defects of the RC elements based on the identification of external indicators using the ML tools. This study created and compared the performance of four ML models, namely, Support Vector Regression (SVR), decision trees (DTs), random forest (RF), and Artificial Neural Networks (ANNs). The first comparison showed a rather low performance of all models, with a slight advantage of the ANN model. Later, six ANN models were optimized to obtain a higher level of performance. The next step of this study was the training, validation, and testing of ANN models. Analysis of MAPE and R2 metrics showed that the ANN model with an Adaptative Moment (ADAM) loss function and sigmoid activation had the best results (MAPE 3.38%; R² 0.969). The novelty of the study consisted of the development of the ML model, which is based on the use of ANNs, and allows for the establishment of cause-and-effect relationships in the diagnosis of the technical condition of the RC elements. The advantage of using ANN to solve this problem is the possibility to obtain a forecast in the form of continuous values. Moreover, the model can be used further without retraining, and it can make predictions on datasets it has not yet “seen”. The practical use of such a model will allow for the diagnosis of some causes of defects during a visual inspection of structures. Full article

(This article belongs to the Special Issue Intelligent Solutions for the Sustainability of Bridges and Structures)

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12 pages, 4097 KiB

Open AccessArticle

Flexural Wave Bandgaps in a Prestressed Multisupported Timoshenko Beam with Periodic Inerter-Based Dynamic Vibration Absorbers

by Wenwen Han and Shui Wan

Sustainability 2023, 15(4), 3680; https://doi.org/10.3390/su15043680 - 16 Feb 2023

Viewed by 1552

Abstract

Locally resonant (LR) metamaterial structures possess bandgaps in which wave propagation is significantly attenuated. In this paper, we discuss flexural wave bandgaps in an LR beam subjected to a global axial force and multiple vertical elastic supports. An array of inerter-based dynamic vibration absorbers (IDVAs) was periodically attached to the LR beam. The flexural wave band structure of this prestressed multisupported LR beam was first derived using the transfer matrix method (TMM) and then explicitly illustrated through a numerical example. Four bandgaps were identified: a bandgap located in the low-frequency zone, a Bragg band generated by Bragg scattering, and two LR bands generated by the local resonance of the IDVAs. The effects of the IDVA parameters, axial force, and vertical elastic support on the properties of the bandgaps were evaluated. In particular, the bandgaps merged accompanied by an exchange of their edge frequencies. The bandwidth of the merged bandgap was nearly equal to the sum of the bandwidths of the bandgaps involved, indicating a method for controlling broadband flexural vibration through the bandgap splicing mechanism. Full article

(This article belongs to the Special Issue Intelligent Solutions for the Sustainability of Bridges and Structures)

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13 pages, 4717 KiB

Open AccessArticle

Optimized Design of a Squeezed-Branch Pile Group Based on an Improved Particle Swarm Algorithm

by Jiawei Chen and Yingxin Hui

Sustainability 2023, 15(3), 2060; https://doi.org/10.3390/su15032060 - 21 Jan 2023

Cited by 3 | Viewed by 1349

Abstract

To reduce the differential settlement of pile group foundations, a squeezed-branch pile group optimization method based on an improved particle swarm algorithm is proposed in this paper. This method translates the problems of optimization design in the squeezed-branch pile group into the pile-bearing-plate distribution using the theory of variable-stiffness leveling. In the optimization process, the pile group is divided into groups according to the top axial force of the pile. The finite element analysis software is used to solve the pile group under the control of the particle swarm optimization algorithm, with the objective functions of bearing-plate number, vertical bearing capacity, settlement value and settlement difference as the constraint conditions. An engineering example is used to verify this method. The results show that the optimized design can reduce the settlement difference by 39%, while the number of the bearing plate is reduced by 56%, which makes the deformation and force of the pile group more uniform and is conducive to the normal use of the structure. Full article

(This article belongs to the Special Issue Intelligent Solutions for the Sustainability of Bridges and Structures)

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19 pages, 3915 KiB

Open AccessArticle

Investigation on Effect of Reflective Coating on Temperature Field of CRTS Ⅱ Slab Ballastless Track under Sunlight

by Xiankai Quan, Wenhua Guo, Jun Tian and Weiguo Zhang

Sustainability 2023, 15(2), 915; https://doi.org/10.3390/su15020915 - 4 Jan 2023

Cited by 3 | Viewed by 1595

Abstract

The internal temperature variation of ballastless track is very complicated under the effect of a sunlit environment, and there are serious transverse and vertical temperature gradients, which will cause cracking and deformation of the structure. In this paper, an ANSYS temperature effect analysis model for ballastless track, considering box girder structure, is established based on the environmental information of the bridge and the characteristics of the structural system. The model considers the influence of solar radiation intensity, wind speed, air temperature, geographical location, bridge orientation, material parameters, and other factors on the boundary conditions, and can meet the needs of the daylight temperature response analysis and calculation of any complex bridge structure. On this basis, the effect and applicability of a solar reflective coating on ballastless track cooling are studied. The results showed that the calculated results of the finite element model agree well with the measured results. Under the high-temperature conditions in summer, sunlight and ambient temperature mainly have significant effects on the temperature and temperature gradient of the track slab, and the maximum vertical temperature gradient reaches 74.48 °C/m. The reflective coating can significantly reduce the track slab’s temperature and vertical temperature gradient, with a maximum temperature gradient reduction of 34%. The transverse temperature gradient of the track slab can be reduced by up to 54% by further application of the side reflective coating. This study can promote the application of reflective coatings on high-speed railway track structures. Full article

(This article belongs to the Special Issue Intelligent Solutions for the Sustainability of Bridges and Structures)

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19 pages, 1676 KiB

Open AccessArticle

Modeling the Quantitative Assessment of the Condition of Bridge Components Made of Reinforced Concrete Using ANN

by Roman Trach, Victor Moshynskyi, Denys Chernyshev, Oleksandr Borysyuk, Yuliia Trach, Pavlo Striletskyi and Volodymyr Tyvoniuk

Sustainability 2022, 14(23), 15779; https://doi.org/10.3390/su142315779 - 27 Nov 2022

Cited by 8 | Viewed by 1698

Abstract

Bridges in Ukraine are one of the most important components of the infrastructure, requiring attention from government agencies and constant funding. The object of the study was the methodology for quantifying the condition of bridge components. The Artificial Neural Network-based (ANN) tool was developed to quantify the technical condition of bridge components. The literature analysis showed that in most cases the datasets were obtained during the inspection of bridges to solve the problems of assessing the current technical condition. The lack of such a database prompted the creation of a dataset on the basis of the Classification Tables of the Operating Conditions of the Bridge Components (CT). Based on CTs, five datasets were formed to assess the condition of the bridge components: bridge span, bridge deck, pier caps beam, piers and abutments, approaches. The next step of this study was creating, training, validating and testing ANN models. The network with ADAM loss function and softmax activation showed the best results. The optimal values of MAPE and R² were achieved at the 100th epoch with 64 neurons in the hidden layer and were equal to 0.1% and 0.99998, respectively. The practical application of the ANN models was carried out on the most common type of bridge in Ukraine, namely, a road beam bridge of small length, made of precast concrete. The novelty of this study consists of the development of a tool based on the use of ANN model, and the proposal to modify the methodology for quantifying the condition of bridge components. This will allow minimizing the uncertainties associated with the subjective judgments of experts, as well as increasing the accuracy of the assessment. Full article

(This article belongs to the Special Issue Intelligent Solutions for the Sustainability of Bridges and Structures)

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14 pages, 7754 KiB

Open AccessArticle

Bond Performance of CFRP/Steel Double Strap Joint at Elevated Temperatures

by Yuwen Liu, Wei Chen, Chun Liu and Na Li

Sustainability 2022, 14(23), 15537; https://doi.org/10.3390/su142315537 - 22 Nov 2022

Cited by 2 | Viewed by 1456

Abstract

Carbon fiber-reinforced polymer (CFRP) has been used widely in the strengthening of steel structures. Steel/CFRP systems being subjected to elevated temperatures is realistic in summer climate events in many countries, which leads to the degradation of the bond performance between CFRP and steel. Therefore, it is critical to study the bond behavior of the CFRP/steel system under elevated temperature. This paper investigates the mechanical performance of CFRP/steel adhesively bonded double strap joints under different temperatures. Thirty CFRP/steel double strap joints were tested to failure under temperatures between 10 °C and 90 °C. It was found that the joint failure mode changed from adherend failure to debonding failure as the temperature was approaching glass transition temperatures. In addition, the ultimate load and joint stiffness decreased significantly under temperatures near to and higher than glass transition temperatures. Based on the experimental results, a model is proposed to predict the bond stress of the CFRP/steel under different temperatures. Full article

(This article belongs to the Special Issue Intelligent Solutions for the Sustainability of Bridges and Structures)

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16 pages, 3761 KiB

Open AccessArticle

Design and Experimental Evaluation of Composite Magnesium Phosphate Cement-Based Coating with High Cooling Effect

by Xiankai Quan, Wenhua Guo, Binxin Duan, Jun Tian and Xiaowei Wu

Sustainability 2022, 14(17), 10790; https://doi.org/10.3390/su141710790 - 30 Aug 2022

Cited by 1 | Viewed by 1588

Abstract

The application of surface heat reflective coatings is one of the effective measures to solve the temperature disease of concrete structures in sunlit environments. To achieve strong bonding, high durability, and good cooling characteristics, a novel inorganic reflective thermal insulation coating was prepared using magnesium phosphate cement (MPC) as the binder and reflective matrix, and titanium dioxide and glass beads as the reflective thermal insulation reinforcement functional additives. The optimum ratio of the new reflective thermal insulation coating was preferred through laboratory irradiation test, thermal conductivity test, and spectral reflectance test. The results show that MPC itself was a good reflection cooling material, and the surface and internal temperatures of concrete blocks were reduced by 7.6 °C and 6.6 °C, respectively, after using MPC as the cooling coating. When 2% titanium dioxide was added to MPC, the surface and internal temperatures were further reduced by 6.0 °C and 4.9 °C, respectively. On top of this, the surface and internal temperatures of the concrete were reduced by a further 3.9 °C and 2.2 °C when 8% glass beads were added. The bond strength of the MPCTG coating to the concrete matrix reached 2.1 MPa. Finally, the microscopic characteristics and the reflective thermal insulation mechanism of the MPCTG coating were investigated with the aid of SEM, thermo gravimetric analysis, and XRD analysis. The results show that the MPC in the MPCTG coating was well hydrated, and a large number of hydration products encapsulated the unreacted MgO particles, titanium dioxide, and glass beads, forming a dense whole with high reflection and low thermal conductivity, and the coating effectively prevented the entry of radiant heat. At the same time, the MPCTG coating was thermally stable below 70 °C. The magnesium phosphate cement-based reflective thermal insulation coating developed in this study has potential application prospects in concrete structure cooling coatings. Full article

(This article belongs to the Special Issue Intelligent Solutions for the Sustainability of Bridges and Structures)

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