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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 (25 July 2022) | Viewed by 15587

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Special Issue Editor

Dr. Muntasir Billah

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Guest Editor

Department of Civil Engineering, Lakehead University, Thunder Bay, ON P7B 7E1, Canada
Interests: bridge engineering; smart structures; resilient infrastructure; structural dynamics; finite element modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Major natural hazard events around the world, along with the aging and deterioration of infrastructures, keep increasing the need for the development of innovative materials and the optimization of structures for improved infrastructure resiliency. These natural hazards cause not only physical damage, but cascading social, environmental, and economic impacts that impair community resilience. Innovative materials, alongside structural optimization, is an area that has seen major developments due to the availability of robust numerical simulation frameworks, large experimental facilities, development of advanced materials and construction techniques, optimization frameworks and tools. Despite progress being made, there are many challenges that have yet to be addressed.

This Special Issue invites papers presenting numerical and/or experimental research on innovative materials and structural optimization for resilient buildings and bridges. The purpose of this Special Issue is to promote a wider use of advanced materials and optimization technologies in the design industry and to improve the resilience of our infrastructures. We invite research and development on innovative and advanced materials for resilient infrastructure designs, as well as the use of numerical optimization techniques to design material-efficient or cost-effective structures. The main goal of this issue is to generate a forum for the current state of knowledge, as well as future research directions, in the overall area of innovative materials and structural optimization.

Dr. Muntasir Billah
Guest Editor

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Keywords

Innovative materials
Smart materials
High-performance materials
Structural optimization
Design optimization
Resilient infrastructure
Sustainable infrastructure
Reliability-based optimization

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Published Papers (6 papers)

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Research

20 pages, 39086 KiB

Open AccessArticle

Effective Hybrid Soft Computing Approach for Optimum Design of Shallow Foundations

by Mohammad Khajehzadeh, Suraparb Keawsawasvong and Moncef L. Nehdi

Sustainability 2022, 14(3), 1847; https://doi.org/10.3390/su14031847 - 6 Feb 2022

Cited by 22 | Viewed by 2900

Abstract

In this study, an effective intelligent system based on artificial neural networks (ANNs) and a modified rat swarm optimizer (MRSO) was developed to predict the ultimate bearing capacity of shallow foundations and their optimum design using the predicted bearing capacity value. To provide the neural network with adequate training and testing data, an extensive literature review was used to compile a database comprising 97 datasets retrieved from load tests both on large-scale and smaller-scale sized footings. To refine the network architecture, several trial and error experiments were performed using various numbers of neurons in the hidden layer. Accordingly, the optimal architecture of the ANN was 5 × 10 × 1. The performance and prediction capacity of the developed model were appraised using the root mean square error (RMSE) and correlation coefficient (R). According to the obtained results, the ANN model with a RMSE value equal to 0.0249 and R value equal to 0.9908 was a reliable, simple and valid computational model for estimating the load bearing capacity of footings. The developed ANN model was applied to a case study of spread footing optimization, and the results revealed that the proposed model is competent to provide better optimal solutions and to outperform traditional existing methods. Full article

(This article belongs to the Special Issue Innovative Materials and Structural Optimization for Resilient Infrastructure)

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17 pages, 6670 KiB

Open AccessEditor’s ChoiceArticle

Quantifying Crack Self-Healing in Concrete with Superabsorbent Polymers under Varying Temperature and Relative Humidity

by Ahmed R. Suleiman, Lei V. Zhang and Moncef L. Nehdi

Sustainability 2021, 13(24), 13999; https://doi.org/10.3390/su132413999 - 18 Dec 2021

Cited by 6 | Viewed by 2572

Abstract

During their service life, concrete structures are subjected to combined fluctuations of temperature and relative humidity, which can influence their durability and service life performance. Self-healing has in recent years attracted great interest to mitigate the effects of such environmental exposure on concrete structures. Several studies have explored the autogenous crack self-healing in concrete incorporating superabsorbent polymers (SAPs) and exposed to different environments. However, none of the published studies to date has investigated the self-healing in concrete incorporating SAPs under a combined change in temperature and relative humidity. In the present study, the crack width changes due to self-healing of cement mortars incorporating SAPs under a combined change of temperature and relative humidity were investigated and quantified using micro-computed tomography and three-dimensional image analysis. A varying dosage of SAPs expressed as a percentage (0.5%, 1% and 2%) of the cement mass was incorporated in the mortar mixtures. In addition, the influence of other environments such as continuous water submersion and cyclic wetting and drying was studied and quantified. The results of segmentation and quantification analysis of X-ray µCT scans showed that mortar specimens incorporating 1% SAPs and exposed to environments with a combined change in temperature and relative humidity exhibited less self-healing (around 6.58% of healing efficiency). Conversely, when specimens were subjected to cyclic wetting and drying or water submersion, the healing efficiency increased to 19.11% and 26.32%, respectively. It appears that to achieve sustained self-healing of cracks, novel engineered systems that can assure an internal supply of moisture are needed. Full article

(This article belongs to the Special Issue Innovative Materials and Structural Optimization for Resilient Infrastructure)

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14 pages, 5685 KiB

Open AccessEditor’s ChoiceArticle

Propagation of Mouth-Generated Aerosols in a Modularly Constructed Hospital Room

by Mutaz Suleiman, Ahmed Elshaer, Muntasir Billah and Mohammed Bassuony

Sustainability 2021, 13(21), 11968; https://doi.org/10.3390/su132111968 - 29 Oct 2021

Cited by 3 | Viewed by 1795

Abstract

Modular construction methods have been widely used in the civil engineering industry due to ease of assembly, the convenience of design, and allowing for flexibility in placement while making the construction more sustainable. With the increasing number of COVID-19 cases, the capacity of the hospital is decreasing as more intensive care units (ICU) are allocated to COVID-19 cases. This limited capacity can be addressed by using modular construction to provide field hospitals. This paper adopts transient Lagrangian computational fluid dynamics simulations to investigate the importance of having an appropriate ventilation system in place to ensure sustainable infection control against airborne viruses and pathogens within a modular room. The performance of having a ventilation system using 10, 20, and 40 air changes per hour (ACH) was examined. In addition, different room configurations were also compared to provide useful guidelines for air conditioning units placement. It was determined that as the ACH rate increases while maintaining a direct flow field between the inlet and outlet, the rate of aerosol removal increases. Furthermore, the flowfield in which can be controlled by the placement of the inlet and outlet can impact the removal of aerosols, as it dictates how far the droplets travel before being removed from the enclosure. Full article

(This article belongs to the Special Issue Innovative Materials and Structural Optimization for Resilient Infrastructure)

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18 pages, 2915 KiB

Open AccessFeature PaperArticle

Experimental Investigation on Axial Compression of Resilient Nail-Cross-Laminated Timber Panels

by Moncef L. Nehdi, Yannian Zhang, Xiaohan Gao, Lei V. Zhang and Ahmed R. Suleiman

Sustainability 2021, 13(20), 11257; https://doi.org/10.3390/su132011257 - 12 Oct 2021

Cited by 3 | Viewed by 2009

Abstract

Conventional cross-laminated timber is an engineered wood product consisting of solid-sawn lumber panels glued together. In this study, the structural behavior of solid wood panels of Nail-Cross-Laminated Timber (NCLT) panels connected with nails instead of glue was studied. The failure mode and nail deformation of the novel NCLT panels under axial compression load using eight full-scale NCLT panels was investigated. The effects of four key design parameters, namely, the nail type, number of nails, nail orientation angle, and nail slenderness ratio on axial compression performance of NCLT panels were also analyzed. In addition, a formula for predicting the axial compression bearing capacity of NCLT panels was developed. For calculation of the slenderness ratio, the moment of inertia of the full section or the effective section was determined based on the nail type, number of nails, angle of nail orientation and number of layers of the plate. Results showed that specimens connected by tapping screws had best compressive performance. Full article

(This article belongs to the Special Issue Innovative Materials and Structural Optimization for Resilient Infrastructure)

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26 pages, 12348 KiB

Open AccessArticle

CO₂ Emission Optimization of Concrete-Filled Steel Tubular Rectangular Stub Columns Using Metaheuristic Algorithms

by Celal Cakiroglu, Kamrul Islam, Gebrail Bekdaş, Sanghun Kim and Zong Woo Geem

Sustainability 2021, 13(19), 10981; https://doi.org/10.3390/su131910981 - 3 Oct 2021

Cited by 16 | Viewed by 2073

Abstract

Concrete-filled steel tubular (CFST) columns have been assiduously investigated experimentally and numerically due to the superior structural performance they exhibit. To obtain the best possible performance from CFST columns while reducing the environmental impact, the use of optimization algorithms is indispensable. Metaheuristic optimization techniques provide the designers of CFST members with a very efficient set of tools to obtain design combinations that perform well under external loading and have a low carbon footprint at the same time. That is why metaheuristic algorithms are more applicable in civil engineering due to their high efficiency. A large number of formulas for the prediction of the axial ultimate load-carrying capacity

(N_{u})

of CFST columns are available in design codes. However, a limitation of the usage of these design formulas is that most of these formulas are only applicable for narrow ranges of design variables. In this study a newly developed set of equations with a wide range of applicability that calculates

N_{u}

in case of rectangular cross-sections is applied. In order to optimize the cross-sectional dimensions, two different metaheuristic algorithms are used, and their performances are compared. The reduction in CO₂ emission is demonstrated as a function of cross-sectional dimensions while considering certain structural performance requirements. The outcome of the more recently developed social spider algorithm is compared to the outcome of the well-established harmony search technique. The objective of optimization was to minimize CO₂ emissions associated with the fabrication of CFST stub columns. The effects of varying the wall thickness as well as the concrete compressive strength on CO₂ emissions are visualized by using two different optimization techniques. Full article

(This article belongs to the Special Issue Innovative Materials and Structural Optimization for Resilient Infrastructure)

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23 pages, 9002 KiB

Open AccessArticle

CO₂ Emission and Cost Optimization of Concrete-Filled Steel Tubular (CFST) Columns Using Metaheuristic Algorithms

by Celal Cakiroglu, Kamrul Islam, Gebrail Bekdaş and Muntasir Billah

Sustainability 2021, 13(14), 8092; https://doi.org/10.3390/su13148092 - 20 Jul 2021

Cited by 20 | Viewed by 2839

Abstract

Concrete-filled steel tubular columns have garnered wide interest among researchers due to their favorable structural characteristics. To attain the best possible performance from concrete-filled steel tubular columns while reducing the cost, the use of optimization algorithms is indispensable. In this regard, metaheuristic algorithms are finding increasing application in structural engineering due to their high efficiency. Various equations that predict the ultimate axial load-carrying capacity (N_u) of concrete-filled steel tubular columns are available in design codes as well as in the research literature. However, most of these equations are only applicable within certain parameter ranges. To overcome this limitation, the present study adopts a recently developed set of equations for the prediction of Nu that have broader ranges of applicability. Furthermore, a newly developed metaheuristic algorithm, called the social spider algorithm, is introduced and applied in optimizing the cross-section of circular concrete-filled steel tubular columns. The improvement of the structural dimensioning under the Nu constraint is demonstrated. The objective underlying the optimization presented here is to minimize the CO₂ emission and cost associated with the fabrication of concrete-filled steel tubular stub columns. In this context, the relationships between the cross-sectional dimensioning of circular concrete-filled steel tubular columns and the associated CO₂ emissions and cost are characterized and visualized. Full article

(This article belongs to the Special Issue Innovative Materials and Structural Optimization for Resilient Infrastructure)

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