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The rising global cost of housing demands innovative solutions to improve construction materials and reduce expenses, making affordable housing more attainable. This study investigates the synergistic benefits of eco-friendly additives—kenaf fiber and glass powder—in masonry applications aimed at affordable housing solutions. The aim is to identify the effect of different kenaf fiber and glass powder proportions on lateritic brick. Kenaf fiber was incorporated into a cement-lateritic clay mix at varying percentages (0.5 %, 1.0 %, 1.5 %, and 2.0 %), while glass powder replaced cement at levels of 10 %, 20 %, 30 %, and 40 %. The reference mix was prepared as 20 % cement, 20 % sand, and 60 % laterite clay while the water/cement ratio was maintained at 0.4. Results indicate that kenaf fiber and glass powder significantly improve compressive, flexural, and splitting strengths compared to the reference mix. However, kenaf fiber exhibits a reduction in ultrasonic velocity. The dosage of kenaf fiber and glass powder profoundly influences the hybrid material properties. The study has revealed that 4 % of glass powder and 1 % of kenaf fiber highly improved the compressive strength, flexural strength and ultrasonic velocity of the mixes. On the other hand, 4 % of glass powder and 1.5 % of kenaf fiber highly improved the splitting strength of the material. These results were supported by a predictive model validated against experimental data. Optimization reveals an optimum mix with 20.44 % cement replacement (comprising 15.91 % cement, 4.08 % glass powder, and 1.19 % kenaf fiber), 20 % sand and 58.80 % clay, offering balanced performance for masonry bricks in affordable mass housing construction.

The strengthening of masonry infill wall panels (MIWPs) in reinforced concrete (RC) frame structures is of prime importance due to their failure in the in-plane and out-of-plane direction, as evidenced by past earthquakes. This research study applies an innovative approach of dual-strengthening materials to individual MIWPs in the RC frame structures to improve their seismic performance. Ferrocement overlay (FCO) and engineered cementitious composites (ECC) materials are applied to different MIWPs in a half-scaled two-story, two-by-two-bay reinforced concrete frame structure with different arrangements of infill walls. The strengthened masonry infill wall panels (SMIWPs) in the RC frame structure were tested using the quasi-static testing protocol. The testing results are compared with conventional masonry infill wall panels (CMIWPs) walls in RC frame structure in terms of damage pattern and backbone curve to evaluate the effect of the strengthening strategies applied to the MIWPs. The lateral Strength, stiffness, and ultimate ductility were enhanced by 166%, 40%, and 60%, respectively. The strengthening strategy effectively improved the damage propagations, lateral Strength, stiffness, and ductility.

AbstractThis paper reviews the application of artificial intelligence (AI)-based models in modeling vehicular road traffic noise. A computerized search method was used to conduct the literature search. Fifty published articles from 2007 to 2023 were reviewed regarding observation time, input data, countries where studies were performed, and modeling techniques. Sixty-three percent of the studies used an observation period of 60 min, and 29% used 15 min. All the reviewed papers considered traffic flow as the major input parameter, followed by average speed, with 95% of the researchers using it as an input parameter. It was found that using AI-based models for traffic noise prediction was popular in countries with no established empirical models. The primary input parameters for the AI-based models are traffic volume and speed. Traffic volume is used either as total traffic volume or classified into sub-categories, and each category is used as an independent input parameter. Although AI-based models have demonstrated reliable performance regarding prediction error and goodness of fit, the accuracy of the AI-based models’ performance should be compared with the results of the empirical models in countries with established models, such as the UK (CoRTN) and the USA (FHWA).

The use of back-to-back built-up channel beams in cold-formed steel (CFS) structures is steadily rising. The growing demand for CFS sections as a cost-effective design solution has driven the development of these CFS built-up sections. Despite this, there has been limited research on the performance of mild steel (MS) based CFS at high temperatures, particularly regarding its flexural behavior. This study thoroughly explores the behavior of MS-based CFS beams with different spans under high temperatures, followed by cooling with air or water. It assesses the impact of thermal loading and evaluates the effectiveness of these cooling methods. Experimental findings are validated and analyzed in conjunction with Finite Element Modeling (FEM) using ABAQUS and the Direct Strength Method (DSM). The study also conducts a parametric analysis to determine how the varying span that affects flexural capacity of beam. Among beams heated to the same temperature, those cooled with water exhibit slightly lower load capacities than those cooled with air. The maximum load observed is 91.21 kN for the reference specimen, while the minimum load is 39.82 kN for the specimen heated for 90 min and cooled with water, resulting in a 78.45% difference between these values. Additionally, as heating duration increases, ductility of beam also increases. Various failure modes are observed based on different heating and cooling conditions across different beam spans. This study offers valuable insights into the performance of MS-based CFS beams under thermal stress and different cooling conditions, providing important data for structural design and safety in construction.

The transportation industry is one of the greatest contributors to a growing carbon footprint. As the world increasingly prioritizes a greener and cleaner future, the transition from ICEs to EVS offers significant benefits as EVs are zero-emission vehicles. However, considering the production and disposal stages of EVs, they cannot be considered entirely emission-free. But in comparison to ICEs, they still have a much smaller carbon footprint. Moreover, studying EV technology is essential to bringing this to the lowest possible extent. However, these advancements come with challenges. In this review article, we have taken an in-depth look into the various challenges, namely the economic challenges, technological challenges, and environmental challenges, faced by EV technology today and the various solutions proposed by researchers, their limitations, and future potential in EV technology advancement. Within this context, we discuss the influence of governmental policies, accessibility and affordability of EVs to the masses, natural and man-made disasters, economic instability, technological limitations posed by the vehicle technology, and limitations posed by battery technology with batteries being the central element for EVs, limitations associated with the existing infrastructure and its ability to support widescale use of EVs, and environmental factors like carbon footprint, among other factors, on EVs technology and the opportunities this technology can make use of in the future. This paper discusses these concerns in detail and gives extensive insight into the challenges, solutions, and future trends pertaining to economic impacts, vehicle technology, battery technology, power grids and charging infrastructure, and environmental impact, of EVs and EV technology.

Cellular lightweight concrete (CLC) block masonry is an eco-friendly building material gaining popularity in both developed and developing countries. Despite its increasing use, the material's behavior under seismic loading remains insufficiently understood. This research involved quasi-static testing of two full-scale CLC blocks masonry walls strengthened with ferrocement overlay. One of the strengthened walls was subjected to confinement, while the other was unconfined. The aim was to assess their seismic performance by comparing force deformation curves, damping, stiffness degradation, and structural performance levels with non-strengthened walls. The findings indicate that the strengthened masonry outperformed the unreinforced version, suggesting that CLC block masonry exhibits potential for effective performance in low to moderate seismic zones.

The phosphate industry produces a hazardous byproduct called phosphogypsum (PG). A rising global stockpiling of PG poses severe threats to public health and the environment. Fortunately, recycling this material may be a risk-free and environmentally beneficial answer to this problem. It is necessary to examine its current application and future growth prospects in civil engineering to increase the PG utilization rate. This paper summarizes previous research on reusing PG in building materials. This review article is divided into four essential sections. Firstly, the chemical properties of PG and their treatment methods before using PG in any application are reviewed extensively. Secondly, the strength properties of bricks made with PG and their microstructural characteristics through scanning electron microscope (SEM) and X-ray diffraction (XRD) were reviewed. The third part of this article is about using PG as a substitution for cement and studies the setting time, compressive strength, SEM and XRD of cement mortar. The final section is PG-based concrete and studies concrete specimens' workability, compressive strength, SEM and XRD. The last three sections extensively focused on the microstructural characteristics of the building materials. Following a comprehensive literature search, it was determined that PG could be utilized in the construction industry. Several studies have been performed on using PG in building materials such as bricks, concrete and other materials. However, PG utilization in large-scale practical applications needs better social and political awareness. More money is needed for research and development to free the economy and technology from their shackles. The findings of this review will serve as a foundation for further research and practical applications of PG in environmentally friendly processes.

The transformational potential of 3D printing within the manufacturing industry has been widely recognized. However, its widespread adoption faces significant practical challenges that extend beyond the technology itself, encompassing political, economic, social, and technical (PEST) factors. This research investigates the external variables impacting the successful implementation of 3D printing and proposes strategies to overcome these barriers. Through exploratory factor analysis (EFA) and structural equation modeling (SEM), we identified key external factors, including governmental regulations, economic conditions, societal acceptance, and technical readiness, that significantly influence the success of 3D printing deployment. Notably, addressing technological barriers emerged as a crucial factor. To address these implementation challenges, we recommend increased public awareness and stakeholder participation. Our findings indicate that these strategies can enhance the prospects of 3D printing adoption. These results hold significant implications for policymakers, practitioners, and researchers in the 3D printing industry. Understanding and mitigating external obstacles are critical for harnessing the benefits of 3D printing within a dynamic environment. This research sheds light on the multifaceted challenges surrounding 3D printing implementation, emphasizing the importance of proactive measures to overcome these hurdles.

Commercial powder activators are commonly used to produce one-part alkali-activated binders (AAB) despite their manufacturing method using more energy and generating more CO2 emissions. To address this concern, the study employed a mechanical process to synthesize an agricultural waste-based powder activator, derived from rice husk ash (RHA) and NaOH powder at six different ratios. Paste samples were prepared by blending the derived activator with ground granulated blast furnace slag (GGBFS) precursor in a 1:4 ratio. Fresh properties and compressive strength (range of 33–77 MPa) was evaluated. Besides, microstructural analysis and ecological factors were estimated, including embodied CO2 emissions and energy analysis, and the approach employed in this investigation significantly reduced both embodied CO2 emissions and embodied energy requirements compared to conventional practices. The result indicates that the activator powder synthesized in this study can produce AAB with qualities comparable to Portland cement.

Blockchain technology provides a decentralized way of handling the data and supports the construction project's sustainability and performance. Small construction projects in Malaysia always need help adopting new technology like blockchain. This research aimed to investigate the challenges affecting the implementation of blockchain technology in small construction projects in Malaysia. The study examined Malaysian minor construction project blockchain implementation issues. A total of 17 challenges were found significant in affecting the implementation of Blockchain technology in small construction projects in Malaysia. Five constructs were seen: technological barriers, work environment barriers, economic and planning barriers, operational barriers, and privacy and regulation barriers. Structural equation modeling and these structures create a blockchain implementation model for modest building projects. The model's validity, dependability, and forecast accuracy for all obstacles and their potential influence on blockchain deployment in small construction projects in Malaysia are substantial. The model also has good convergent and discriminant validity, supporting it. Blockchain use in Malaysian small building projects could be improved mainly through economic and planning issues. The present study needs to highlight the Malaysian small construction sector's essential obstacles in integrating blocks and technology that are the basis for more creative technologies. This research will help the Malaysian construction sector concentrate on improvements and assess the effect of blockchain on modest projects.

The implementation of 3D laser scanning technology within the architecture, engineering, and construction (AEC) sector possesses the capability to enhance project efficacy and precision. Nevertheless, there exist various obstacles that impede their extensive adoption. This study investigates the key challenges affecting their adoption in the industry. The study employed a mixed-method methodology that involved exploratory factor analysis (EFA) and structural equation modeling (SEM) to examine survey data collected from professionals operating within the architecture, engineering, and construction (AEC) industry. The results reveal significant technical, operational, awareness, and economic challenges. Technical challenges include data processing complexity, limited resources, and compatibility issues. The integration of laser scanning data and perceived risks present operational challenges. Awareness challenges relate to legal factors and change aversion. Economic challenges encompass affordability and time-consuming data acquisition. The ramifications for the industry are significant. Managers should invest in resources, training programs, awareness campaigns, and cost-effective solutions. Future research should expand the sample size and examine long-term effects. Addressing these challenges will enable the AEC industry to fully leverage the potential of 3D laser scanners, enhancing project outcomes and efficiency in the built environment.

The growing importance of green building practices in addressing environmental concerns, with a focus on energy efficiency, resource conservation, and occupant well-being, necessitates innovative solutions. Building Information Modeling (BIM), a sophisticated digital platform facilitating real-time collaboration and construction process visualization, emerges as a promising tool to enhance efficiency in construction projects. This study explores the role of BIM in advancing sustainability in smaller-scale construction projects. The methodology encompasses a comprehensive literature review and a quantitative analysis, including Exploratory Factor Analysis (EFA) and Structural Equation Modeling (SEM), with a case study centered in Perak, Malaysia. The research aims to assess the impact of BIM on resource efficiency, energy performance, waste reduction, and collaborative decision-making in small-scale green buildings. The findings reveal significant positive correlations between BIM adoption and early-stage design optimization, energy efficiency analysis, material selection, life cycle assessment, waste reduction, and prefabrication. This study underscores the vital role of integrating BIM in smaller-scale construction to promote environmentally responsible practices and achieve sustainable outcomes. Future research avenues may explore strategies for optimized BIM integration and deeper insights into the financial aspects of BIM adoption.

This research discusses the behavior of ultra-high-performance concrete (UHPC) specimens made with dumped waste iron ore tailing (IOT) as a fine aggregate in the mix by 30% and 40% in volume fraction along with mono and hybrid fiber incorporation. Basalt fibers of 1%, 2%, and 3%, polypropylene fibers of 0.18%, 0.20%, and 0.22%, and glass fibers of 1%, 1.5%, and 2% of volume fractions were the non-metallic fibers used. Steel fibers as a metallic factor were kept 1% constant throughout the study. The water-to-binder ratio was maintained between 0.15 and 0.17 after sufficient trials. A high-range water reducer was utilized to improve the flowability of the mix. The experimental investigations confirmed that the SG2 mix with 1% steel and 1.5% glass fiber, and 30% IOT, exhibited improved tensile and impact strength compared to standard conventional concrete. This combination exposed an impact energy of 4.05 × 105 kJ for the first crack and 2.7 × 106 kJ for collapse. The energy taken by the specimen between the first crack and the collapse was about 2.3 × 106 kJ. The microstructure was analyzed using Scanning Electron Microscopy. The non–metallic fibers with dominant mechanical properties were thermogravimetrically analyzed.

AbstractThe current study focuses on the utilization of Marble Waste Powder (MWP) as a partial substitution of cement along with local sand instead of microsilica sand in Engineered Cementitious Composite (ECC). The aim was to reduce the environmental concerns of ECC by reducing the cement content without adversely affecting the desired properties. Four mixes were evaluated; the control mix which has no MWP and three test mixes having cement replacement with MWP by 10%, 15%, and 20% were used, respectively. The properties of ECC mixes were found in terms of compressive, tensile, and flexural characteristics. The trend of change in the basic properties of ECC with an increased percentage of MWP as partial substitution of cement was found along with the hypothesis test on the experimental data. From this study, it was concluded that the increased percentage of MWP reduces on the compressive strength of ECC. The maximum reduction in compressive strength of ECC was recorded as 49% with 20% replacement of cement with MWP, as compared to the control sample at 91 days of test age. The tensile strain of ECC increases with the increase in MWP content, while the tensile stress increases only with the increase of MWP content up to a specified limit. The ultimate load in the force–deflection curve first increases with the increase in MWP content up to a certain percentage, while upon further increase in MWP content from 15% to 20%, the ultimate load decreases. The study suggests that the properties do not vary significantly for the modified ECC samples containing MWP, especially the 10% and 15% MWP samples, and can be utilized instead of normal ECC, thus mitigating environmental concerns without compromising the ECC’s performance.

Many research works have already been made and are still in progress on metallic fibres, as their incorporation reduces the brittleness of the concrete and improves its resistance to the impact and crack propagation. But the use of such non-metallic fibres may induce corrosion which is a major problem to be addressed from the durability aspect. To overcome this problem, in the present research work, a non-metallic hybrid fibre combination was investigated with synthetic fibres like polypropylene and abaca fibres. Also, rather than using conventional cementitious materials such as silica fume, fly ash, and ground granulated blast furnace slag, a new generation of ultra-fine material namely alccofine was used as a partial replacement for the cement by 15%. Abaca fibre was utilised in a constant addition of 0.5% and blended with polypropylene fibre in a range varying from 0% to 2% with an increment of 0.5%. The fresh properties of self-compacting concrete (SCC) in mono and hybrid fibres combinations were assessed through slump flow, J-ring, and V-funnel tests. Water absorption and sorptivity tests were conducted to ensure the durability of the prepared mix. Further, impact tests were carried out on the prepared cylinder specimens to check the capability of the mix with the non-metallic hybrid combination. The main objective here was to check whether a high-strength durable SCC could be achieved using non-metallic fibres and natural fibres. From the obtained experimental results, it was observed that 15% alccofine as a partial substitute to the cement with the addition of 0.5% of abaca fibre and 2% of polypropylene fibre to SCC performed better than the control SCC.

Geopolymer (GMR) paste with micro-fibres and nanoparticles is an excellent alternative for reducing cement production for environmental sustainability. Therefore, the performance of fibre-reinforced (FR) GMR pastes containing nanoparticles must be further explored. The goal of this study is to incorporate varying amounts of nano titanium dioxide (NTD) into micro carbon-FR fly ash-based GMR pastes to increase microstructure, impact strength, toughness, fracture, and mechanical performance. Four different dosages of NTD, ranging from 1 to 4% by the weight of the mix to cast GMR mixes including a constant dosage of micro carbon fibre (CF) (0.5% by weight of mix). A reference mix with 0.5% micro-CF having no dosage of NTD was also manufactured. Scanning Electron Microscopy (SEM) was used to assess the internal structure of GMR. The average findings of six specimens from each paste were taken to determine the different features of GMR pastes. The outcomes of this investigation revealed that using 3% NTD in a carbon-FR-GMR mix produced the best results in terms of hardness, impact strength, and compressive stress while using 2% NTD produced the best results in terms of flexural stress and fracture toughness of pastes. The compressive and flexural strengths of GMR improved by 23% and 40% while the impact strength and hardness were improved by 53% and 10%, respectively.

In this article, the effect of local mechanical stress on the properties of monocrystalline and polycrystalline silicon-based p-n junctions under illumination is studied and analyzed experimentally and theoretically. Results from the experiments showed that when the local mechanical force was increased from 4 N to 20 N, the short-circuit current of the monocrystalline silicon-based p-n junction changed nonlinearly from 24 mA to 43 mA, and that of the polycrystalline silicon-based p-n junction changed linearly from 14.7 mA to 16.7 mA. Experimental results shows that the ideality coefficient of the p-n junction based on monocrystalline silicon decreased from 1.274 to 0.807 and that of polycrystalline from 1.274 to 1.102. Therefore, when the mechanical force applied on monocrystalline silicon increased, the dominant recombination changed from Shockley-Read-Hall to Auger. On the other hand, in polycrystalline silicon, the dominant Shockley-Read-Hall recombination did not change due to the grain boundaries. So, it means that mechanical force causes the narrowing of the band gap of the silicon not increasing of number of recombination centers. When mechanical force increases from 4 N to 12 N, fill factor of monocrystalline increased by 5.75% and that of polycrystalline decrease by 1.1%. In the range of 4 N and 20 N mechanical force, saturation current of monocrystalline and polycrystalline silicon p-n junction changed from $8~\mu \text{A}$ to $41~\mu \text{A}$ . and $22~\mu \text{A}$ to $97~\mu \text{A}$ , respectively.

The use of plastic waste as a partial or complete replacement for coarse aggregate in concrete mixtures has been studied in recent years. However, the quality and quantity of coarse plastic waste particles have been a challenge. This study aims to investigate the mechanical performance of concrete with Bakelite plastic waste as a partial replacement for coarse aggregate. Six different concrete mixtures with various Bakelite dosages, ranging from 0 % to 10 %, were tested. The results indicate that the addition of Bakelite plastic alters the behaviour of the concrete and reduces compressive and flexural strengths at lower dosages. The inclusion of Bakelite waste in concrete mixtures generally leads to a decrease in compressive and split tensile strength, with the exception of the mixture containing 6 % Bakelite, which showed increased strength. Although there is a slight reduction in flexural strength, Bakelite waste prevents sudden specimen breakage and maintains specimen integrity. The ultimate load capacity of reinforced concrete beams with Bakelite waste is generally lower compared to the control beam, except for the 8 % waste Bakelite beam which demonstrated a similar ultimate load capacity of 60 kN. Although managing Bakelite waste can be difficult because it can lead to the creation of microplastics in landfills over time, utilizing Bakelite waste in concrete can be a sustainable method of waste management. The innovative use of Bakelite waste as a partial replacement for coarse aggregate in concrete offers a sustainable solution to the problem of waste management and addresses the environmental concerns related to the disposal of non-biodegradable plastics. This research provides a practical solution for developing eco-friendly and cost-effective construction materials while promoting sustainable waste management practices.

The incorporation of dispersed fibres in the binder matrix is proven to be beneficial to the tensile performance of high-performance concrete (HPC). However, the insertion of new/virgin fibres in the ‘concrete matrix’ significantly adds to the final cost and embodied carbon of HPC. Therefore, the environment-friendly design of fibre-reinforced HPC remains the main challenge. In this study, the influence of different volume fractions (Vol.) of ‘jute fibre’ (JF) was examined on the engineering performance of HPC. The effect of micro-silica/silica fume (SF) inclusion as a secondary binder was also analysed on the performance of JF-reinforced HPC. To investigate the mechanical performance of designed mixes, compression, flexure, and splitting-tensile tests were conducted at 28 and 91 days. Non-destructive durability performance indicators, such as ‘water-absorption (WA)’, ‘rapid chloride-ion permeability (RCIP)’, ‘electrical-resistivity (ER)’, and ‘ultrasonic-pulse velocity (UPV)’ were also examined. It was found that the utilisation ratio/efficiency of JF addition improved with the ageing of samples. Moreover, the inclusion of SF proved to be beneficial in the strength gain due to JF addition. The combined use of 0.3% vol. of JF and SF improved the ‘compressive strength (CS)’ by 26–30%. The inclusion of 0.3% vol. of JF improved the ‘splitting-tensile strength (STS)’ of plain HPC by 43% and 23% with and without the SF inclusion, respectively. The JF incorporation showed a minor decrease in the imperviousness of HPC. SF incorporation helped minimise the damaging effect of JF incorporation on the ER, WA resistance, and UPV value of HPC. Owing to the addition of SF, the WA capacity of JF-reinforced mixes was decreased by up to 30% at 28 days and up to 50% at 91 days. While the RCIP values of JF-reinforced mixes were dropped by 40–60% (depending on the JF content) owing to the superior pozzolanic and filler effect of SF.

This research study is about the evaluation of mechanical properties of locally prepared Cored 6” self-interlocking blocks. Currently, all the construction practices, whether brick masonry, block masonry, or reinforced concrete, are time consuming, relatively energy inefficient, not eco-friendly, and non-sustainable. Another issue in masonry construction is that the strength and behavior of bricks or blocks masonry depend upon the properties of the binding material (mortar) used in masonry wall joints. Considering these issues, Eco Blocks are newly introduced interlocking blocks with different sizes and shapes. Construction with interlocking blocks is faster, economical, and easier, as they do not require binding material. The aim of this study was to obtain the mechanical properties such as the compressive strength (individual block and prism), diagonal tensile strength, shear parameters, modulus of elasticity, shear modulus, and flexural strength of Cored 6″ Eco Blocks through comprehensive experimental investigation. These showed encouraging results as compared with typical interlocking compressed earth blocks and also satisfied the threshold set forth by the international standards regulating earth construction. The compressive and flexural strengths of the blocks have been obtained as 6.03 MPa and 1.66 MPa, respectively. Based on the results outcomes, Cored 6” Eco Blocks can be utilized in load bearing walls.

Fibre-reinforced polymers (FRPs) have been effectively applied in various scientific and engineering applications. FRPs have several advantages over traditional construction materials, including high strength-to-weight ratio, corrosion resistance, and durability. They have been widely used in various applications such as aerospace, automotive, civil infrastructure, and marine structures. The properties of FRPs can be tailored by adjusting the type, volume, and orientation of the fibres, as well as the type of polymer matrix used. However, their long-term durability and behavior under different environmental conditions are still areas of research. This article reviews fundamental studies on FRPs, well-established ideas, and some discrepancies that authors have previously reported. The advantages of FRPs relate to their physical characteristics and flexible production techniques that can enhance their performance, durability, and life span. This article also provides information on the main processing parameters of fibre-reinforced polymers (FRPs) and their utilization in the oil and gas industry. The descriptions focus primarily on the many types of synthetic fibres and the qualities that come from their components. The findings show that basalt and aramid fibres are preferred over glass and carbon fibres, and thermoset matrices are more favorable than thermoplastic. The review also discusses the Reinforced thermoplastic (RTPs) used in the oil and gas industry, its processing parameters and failures in detail, and a future recommendation, particularly for drilling, refining, and production pipelines. Also, the scope for future studies.

The interconnection between the steel and concrete is frequently weakened by corrosion. Interestingly, it has been observed that nano pozalonic materials offer an economical approach for lowering the permeability of concrete by enhancing its morphological characteristics. This research discusses the impact of nano pozalonic materials on strengthening the corrosion resistance and pull-out behaviour of steel reinforcement in concrete. In order to treat concrete specimens with accelerated or immersion-based corrosion procedures, the cement is replaced with nanocement (NC) or nano fly ash (NFA).The performance of concrete is tested by evaluating its compressive strength, chloride ion penetration, corrosion potential, and water permeability. The steel reinforcement is examined to assess the residual yield strength and mass loss. In order to assess the bond-slip behaviour between concrete and the reinforcing steel, pull-out tests are performed. Our findings indicate that concrete with nano cement and nano fly ash exhibited excellent corrosion resistance by retaining the yield strength of reinforcement steel and corresponding bond strength.

This works promotes the idea of simultaneous incorporation of ground granulated blast furnace slag (GGBS) and jute fiber (JF) to develop eco-friendly and ductile concrete. For this purpose, an experimental investigation was conducted, where two concrete families were produced using 0% and 25% GGBS as partial replacements for cement. JF was incorporated as 0%, 0.25%, and 0.5% by volume fractions. Effect of plasticizer was also studied on behavior of jute fiber reinforced concrete (JFRC) with GGBS. Compressive strength-CS, splitting tensile strength-STS, flexural strength-FS, water absorption-WA, chloride ion penetration depth-CIPD, and electrical resistivity-ER were studied. The results showed that with the increasing JF content the CS of concrete declined and STS and FS improved. However, the positive effect of JF on CS was observed in mixes containing GGBS with or without a plasticizer. Incorporation of 0.5% JF without plasticizer improved the STS and FS of concrete by 11% and 17%, respectively. However, after achieving the target workability using plasticizer, the net gains in STS and FS due to the 0.5% addition of JF were 24.3% and 29%, respectively. The negative effects of hydrophilic nature of JF on WA and CIPD resistance of concrete were minimized by using GGBS and controlling workability.

High-strength concrete (HSC) is vulnerable to strength loss when exposed to high temperatures or fire, risking the structural integrity of buildings and critical infrastructures. Predicting the compressive strength of HSC under high-temperature conditions is crucial for safety. Machine learning (ML) techniques have emerged as a powerful tool for predicting concrete properties. Accurate prediction of the compressive strength of HSC is important as HSC can experience strength losses of up to 80% after exposure to temperatures of 800°C–1000°C. This study evaluates the efficacy of ML techniques such as Extreme Gradient Boosting, Random Forest (RF), and Adaptive Boosting for predicting the compressive strength of HSC. The results of this study demonstrate that the RF model is the most efficient for predicting the compressive strength of HSC, exhibiting the R2 value of 0.98 and lower mean absolute error and root mean square error values than the other applied models. Furthermore, Shapley Additive Explanations analysis highlights temperature as the most significant factor influencing the compressive strength of HSC. This article provides valuable insights into the timely and effective determination of the compressive strength of HSC under high-temperature conditions, benefiting both the construction industry and academia. By leveraging ML techniques and considering the critical factors that influence the compressive strength of HSC, it is possible to optimize the design and construction process of HSC and enhance its resilience to high-temperature exposure.

Geopolymer concrete is a sustainable substitute for traditional Portland cement concrete. In addition, rising carbon taxes on carbon emissions and energy-intensive materials like cement and lime, impacts the cost of industrial by-products due to their pozzolanic nature. This research evaluates the compressive strength and flexural strength of geopolymer concrete, and the compressive strength of geopolymer mortar. Geopolymer mortar data were used for the strength assessment employing an analytical approach, and geopolymer concrete data were utilized for the strength and sustainability performances. Using artificial neural networks (ANNs), multi-linear regression (MPR) analysis, and swarm-assisted linear regression, compressive strength models were created based on experimental datasets of geopolymer mortar mixes with variable precursors, alkali-activator percentages, Si/Al, and Na/Al ratios. The strength and sustainability performances of geopolymer concrete blends with various precursors were assessed by considering cost-efficiency, energy efficiency, and eco-efficiency. The work’s originality comes from enhancing sustainable high-performance concrete without overestimating or underestimating precursors. Extensive experimental work was done in the current study to determine the best mix of geopolymer concrete by varying silica fume, ground granulated blast furnace slag (GGBS), and rice husk ash (RHA). A scanning electron microscopic study was conducted to understand the geopolymer matrix’s microstructure further. A comprehensive discussion section is presented to explain the potential role of RHA. The replacement of conventional concrete in all its current uses may be made possible by this sustainable high-performance concrete utilizing RHA.

The most often utilized material in construction is concrete. High plasticity, good economy, safety, and exceptional durability are a few of its characteristics. Concrete is a type of structural material that needs to be strong enough to withstand different loads. The compressive strength of the concrete members is the most crucial mechanical characteristic of concrete because of its brittleness. Furthermore, concrete with ternary blended cementitious materials is a sophisticated composite material. The present study explores the binary and ternary blended concrete mixes with silica fume, ceramic powder, bagasse ash, and alccofine, to determine the compressive and flexural strength. Results of compression strength tests show that mixes, including ultra-fine alccofine, have higher strength. Furthermore, the impact of additional cementitious materials on the surface morphology was examined using scanning electron microscopy on the various mixes. This study investigates using linear regression, KNearest Neighbors (KNN), and Bayesian-optimized extreme gradient boosting to estimate the compressive strength of ternary blended concrete (BO-XGBoost). Using the coefficient of determination (R2), mean absolute error (MAE), and mean square error (MSE), the prediction results are further validated. In comparison, the linear regression and BO-XGBoost models show high accuracy towards the prediction of the outcome as indicated by its high R2 value equal to 0.883 and 0.880, respectively, while the R2 value for KNN is 0.736. Additionally, normalized feature importance was included in determining the input variables that significantly influenced compressive strength. The sensitivity of the model indicates CaO and SiO2 shows significant importance to predict ternary blended concrete compressive strength.

Earthquakes can significantly affect long-span structures such as Single Layer Diamatic Space Frame Domes, particularly; when exposed to non-symmetric snow loads. The structural system and structure geometry of this lightweight frame structure in combination with non-symmetrical loading conditions may lead to the instability of structural members. There are several relevant effective structural characteristics such as connecting joint systems, member specifications, support conditions and whole structure systematic configuration which can affect the deformability of a structure under earthquake loading. A numerical investigation has been conducted to investigate the earthquake effects on this structure under different loading conditions. Based on the conducted numerical investigation concerning structure deformability, the structure of the system and geometry had lesser influence than parameters such as the structure's natural period, base shear and behaviour coefficient. Six domes with different geometrical form types were considered in the modelling process. It seems that the stability of a dome with non-symmetrical snow loading is more critical while earthquake shaking takes place. The dynamic deformability of most of the dome types was higher when symmetrical snow load under different earthquake acceleration time histories was applied however for a few of the dome types the deformability was higher under non-symmetrical snow loading conditions.

The continuous increase in population, advancement in technology, and affluence have influenced the amount of biodegradable and nonbiodegradable waste generated. Studies have shown that the utilization of different wastes in concrete is imperative to reduce the long-term environmental problems associated with their handling and management. This study evaluates the performance of concrete incorporating polyethene terephthalate powder (PETp) and rice husk ash (RHA) as supplementary cementitious materials varied at 0%, 7.5%, and 15%. Results indicated that the presence of PETp reduces workability while increasing the content of both PETp and RHA decreased the compressive and flexural strengths. A few studies have demonstrated the prediction and optimization of PETp as a fine aggregate. This study explores the central composite design of response surface methodology in optimizing the fresh and hardened properties of concrete incorporating PETp and RHA. The results indicate that workable concrete can be achieved with an RHA content higher than the PETp content. The analysis of variance provided effective models with good prediction capabilities. The simulated values from the models were close to those obtained experimentally. An optimal percentage of 5.76% PETp and 9.45% RHA was obtained for predicted responses and validated with a good level of accuracy. An overview of the different combinations of RHA and PETp indicates that concrete incorporating only RHA had the tendency to absorb the least water and exhibit low voids. However, the combination of 7.5% RHA and 7.5% PETp had a reduced water absorption when compared with a concrete mix containing 15% of either supplementary cementitious material. In general, eco-friendly concrete with improved durability can be produced by incorporating PETp and RHA.

Geopolymers (GOPL) can play a vital role in the sustainability of concrete construction. The addition of nanoparticles and micro-fibers to GOPL can improve the mechanical and microstructural performance by densifying the matrix and providing the bridging effect against the internal cracking mechanism. Therefore, an extensive investigation on the improvement of the various characteristics of the GOPL is required to make it feasible for practical applications. Moreover, the combined effect of nanoparticles and micro-fibers on various features of GOPL needs further insights. This study investigates the microstructural, mechanical, fracture, and toughness performance of micro-basalt fiber (MBF)-reinforced coal ash-made GOPL using different proportions of nano-sodium oxide at ambient curing conditions. The percentage of nano-sodium oxide examined in the present study varied from 0% to 4% by weight. The MBF amount is kept the same for all fabricated samples at 0.5% by weight. Scanning electron microscopy is used for assessing the microstructural cracking and failure behavior of GOPL pastes. The findings of the present study divulged that the usage of 3% nano-sodium oxide in MBF-reinforced GOPL mix presented the highest increase of 29%, 55%, 24%, and 60% for the compression strength, flexure strength, fracture toughness, and impact strength, respectively. Further increase in the content of nano-sodium oxide prompted the agglomeration of nanoparticles leading to a reduction in the performance of the GOPL. The outcomes of scanned electron microscopy delineated that the addition of nano-sodium oxide refined the interfacial regions and promoted the polymerization process of the GOPL which enriched the microstructure and fabricated a highly densified GOPL paste.

In this research, the influence of micro-silica (MS) was studied on the tensile and flexural behavior of micro-carbon fiber (MCF) reinforced HPC. For this purpose, a total of twelve concrete mixes were designed incorporating six different doses of MCF (at 0%, 0.15%, 0.25%, 0.5%, 0.75% and 1%) with and without MS.The examined properties included compressive strength, splitting tensile strength, load-deflection behavior, ultrasonic pulse velocity, and water absorption. It was found that without MS inclusion, MCF shows a nominal contribution to the mechanical properties. However, the efficiency of MCF incorporation improved phenomenally due to MS addition. The incorporation of MCF at an optimum dose (0.5–0.75% volume fraction) showed 32% and 6% net improvements in modulus of rupture with and without MS, respectively. The micro-filler and pozzolanic effect of MS particles enhanced the bond strength and efficiency of micro-filaments of MCF. MS incorporation delayed the fracture of fiber-reinforced HPC under flexural loading.

The use of coarse recycled aggregates (CRA) as the replacement for natural aggregates is an eco-friendly solution to alleviate the extraction of natural resources and the harmful effects of demolition wastes on the environment. However, the mechanical and durability characteristics of CRA concrete are generally inferior compared to ordinary concrete. The performance of CRA concrete can be supplemented using different fibers and secondary binder materials. This study encourages the idea of using recycled nylon fiber (RNF) to upgrade the ductility of high-performance concrete (HPC) made with CRA. For this purpose, the effect of RNF on HPC properties was explored. RNF was introduced in HPC at four different volume fractions i.e., 0.1 %, 0.25 %, 0.5 % and 1 %. The experiments showed that RNF is generally harmful to the compressive strength and density of HPC. However, at 0.1 % volume, RNF showed a nominally positive effect on compressive strength. RNF addition was highly useful in enhancing the splitting tensile strength and crack resistance of HPC. The tensile strength loss of HPC due to 50 % and 100 % CRA incorporation can also be balanced using 0.25–0.5 % RNF. Water absorption and chloride permeability of HPC were marginally reduced at the incorporation of 0.1–0.25 % RNF. The recommended dosage of RNF is 0.25 %, considering the maximum tensile strength and low permeability of HPC. Owing to the addition of 0.5 % RNF, a CRA-based HPC can attain tensile strength higher than ordinary HPC. Thus, for tensile-loading applications, CRA-RNF-based HPC provides a ductile, and eco-friendly alternative to an ordinary plain HPC.

The estimation of concrete characteristics through artificial intelligence techniques is come out to be an effective way in the construction sector in terms of time and cost conservation. The manufacturing of Ultra-High-Performance Concrete (UHPC) is based on combining numerous ingredients, resulting in a very complex composite in fresh and hardened form. The more ingredients, along with more possible combinations, properties and relative mix proportioning, results in difficult prediction of UHPC behavior. The main aim of this research is the development of Machine Learning (ML) models to predict UHPC flowability and compressive strength. Accordingly, sophisticated and effective artificial intelligence approaches are employed in the current study. For this purpose, an individual ML model named Decision Tree (DT) and ensembled ML algorithms called Bootstrap Aggregating (BA) and Gradient Boosting (GB) are applied. Statistical analyses like; Determination Coefficient (R2), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) are also employed to evaluate algorithms' performance. It is concluded that the GB approach appropriately forecasts the UHPC flowability and compressive strength. The higher R2 value, i.e., 0.94 and 0.95 for compressive and flowability, respectively, of the DT technique and lesser error values, have higher precision than other considered algorithms with lower R2 values. SHAP analysis reveals that limestone powder content and curing time have the highest SHAP values for UHPC flowability and compressive strength, respectively. The outcomes of this research study would benefit the scholars of the construction industry to quickly and effectively determine the flowability and compressive strength of UHPC.

Self-compacting concrete (SCC) was developed to overcome the challenges of concrete placement in dense or congested reinforcement structure, where the concrete can flow under its own weight to fill the densely reinforced structure. However, production of SCC mostly involves the use of high cement to achieve the desired strength. Therefore, to reduce the needed amount of cement, pozzolanic materials such as fly ash can be used to partially replace cement. However, fly ash has been reported to decrease the strengths of concrete especially at early ages. In this study, a self-compacting concrete (SCC) was developed with fly ash as a basic replacement material considering the efficiency of fly ash and incorporating graphene oxide (GO) as a cement additive to counteract the negative effect of fly ash. Response surface methodology (RSM) was utilized for designing the experiments, investigating the effects of fly ash and GO on SCC properties, and developing mathematical models for predicting mechanical properties of SCC. The ranges of fly ash and graphene oxide were 16.67 to 35% and zero to 0.05%, respectively. Statistical analysis was performed by using Design Expert software (version 11.0, Stat Ease Inc., Minneapolis, MS, USA). The results showed that fly ash had a positive effect while GO had a negative effect on the workability of SCC. The incorporation of fly ash alone decreased the compressive strength (CS), splitting tensile strength (STS) and flexural strength (FS), and additionally, increased the porosity of SCC. The addition of GO to fly ash-based SCC reduced its porosity and enhanced its mechanical strengths which was more pronounced at early ages. The developed models for predicting the mechanical strengths of fly ash-based SCC containing GO have a very high degree of correlation. Therefore, the models can predicts the strengths of SCC using fly ash and GO as the variables with a high level of accuracy. The findings show that based on the EFNARC guidelines, up to 35% of fly ash can be used to replace cement in SCC to achieve a mix with satisfactory flowability and deformability properties

This study presents a cost-based optimization model for the design of isolated foundations in cohesive soils. The optimization algorithm not only incorporates safety requirements in the form of ultimate limit state (ULS) and serviceability limit state (SLS) criteria but also deals with the economics simultaneously. In that regard, the generalized reduced gradient (GRG) method is used for the optimization purpose to achieve the least construction cost of an isolated foundation along with the integration of design parameters as optimization variables. The optimization technique is elaborated using a design example in silty clayey soil and the results of the optimized design are compared with those of the conventional design. The optimization model shows that the optimized design can reduce the construction cost by up to 44% as compared to the conventional design cost for the particular example. Moreover, a sensitivity analysis is also performed to evaluate the quantitative impact of cohesive soil properties, design load, and groundwater table on the construction cost. The results indicate that the construction cost majorly depends on the combined effect of four key parameters: Young’s modulus, recompression index, design load, and groundwater table.

This study has endeavored to produce eco-friendly coal ash-incorporated recycled aggregate concrete (FRAC) by utilizing wastewater effluents for environmental sustainability. The mechanical and durability efficiency of the FRAC manufactured were explored using different kinds of effluent by performing a series of tests at various ages. The considered kinds of effluent for the mixing of FRAC were collected from a service station, as well as fertilizer, textile, leather, and sugar factories. Scanning electron microscopy (SEM) was utilized to judge the microstructural behavior of the constructed concrete compositions. The outcomes revealed that using textile factory effluent in the manufacturing of FRAC depicted peak compressive and split tensile strength improvements of 24% and 16% compared to that of the FRAC manufactured using potable water. The application of leather factory effluent for the manufacturing of FRAC portrayed the highest water absorption (13% better than the control mix). The application of fertilizer effluent in the manufacture of FRAC presented the greatest mass loss (19% enhanced than the control mix) due to H2SO4 solution intrusion and the ultimate chloride ion migration (16 mm at twenty-eight days of testing). The summation of coal ash improved the mechanical behavior of the concrete and also caused a reduction in its durability loss of. The SEM analysis depicted that the textile factory effluent presented the most densified microstructure with the development of ettringite needles and CSH gel having refined the ITZ.

The liquid limit (LL) is considered the most fundamental parameter in soil mechanics for the design and analysis of geotechnical systems. According to the literature, the LL is governed by different particle sizes such as sand content (S), clay content (C), and silt content (M). However, conventional methods do not incorporate the effect of all the influencing factors because traditional methods utilize material passing through a # 40 sieve for LL determination (LL40), which may contain a substantial number of coarse particles. Therefore, recent advancements suggest that the LL must be determined using material passing from a # 200 sieve. However, determining the liquid limit using # 200 sieve material, referred to as LL200 in the laboratory, is a time-consuming and difficult task. In this regard, artificial-intelligence-based techniques are considered the most reliable and robust solutions to such issues. Previous studies have adopted experimental routes to determine LL200 and no such attempt has been made to propose empirical correlation for LL200 determination based on influencing factors such as S, C, M, and LL40. Therefore, this study presents a novel prediction model for the liquid limit based on soil particle sizes smaller than 0.075 mm (# 200 sieve) using gene expression programming (GEP). Laboratory experimental data were utilized to develop a prediction model. The results indicate that the proposed model satisfies all the acceptance requirements of artificial-intelligence-based prediction models in terms of statistical checks such as the correlation coefficient (R2), root-mean-square error (RMSE), mean absolute error (MAE), and relatively squared error (RSE) with minimal error. Sensitivity and parametric studies were also conducted to assess the importance of the individual parameters involved in developing the model. It was observed that LL40 is the most significant parameter, followed by C, M, and S, with sensitivity values of 0.99, 0.93, 0.88, and 0.78, respectively. The model can be utilized in the field with more robustness and has practical applications due to its simple and deterministic nature.

Perovskite solar cells (PSCs) are a promising area of research among different new generations of photovoltaic technologies. Their manufacturing costs make them appealing in the PV industry compared to their alternatives. Although PSCs offer high efficiency in thin layers, they are still in the development phase. Hence, optimizing the thickness of each of their layers is a challenging research area. In this paper, we investigate the effect of the thickness of each layer on the photoelectric parameters of n-ZnO/p-CH3NH3PbI3/p-NiOx solar cell through various simulations. Using the Sol–Gel method, PSC structure can be formed in different thicknesses. Our aim is to identify a functional connection between those thicknesses and the optimum open-circuit voltage and short-circuit current. Simulation results show that the maximum efficiency is obtained using a perovskite layer thickness of 200 nm, an electronic transport layer (ETL) thickness of 60 nm, and a hole transport layer (HTL) thickness of 20 nm. Furthermore, the output power, fill factor, open-circuit voltage, and short-circuit current of this structure are 18.9 mW/cm2, 76.94%, 1.188 V, and 20.677 mA/cm2, respectively. The maximum open-circuit voltage achieved by a solar cell with perovskite, ETL and HTL layer thicknesses of (200 nm, 60 nm, and 60 nm) is 1.2 V. On the other hand, solar cells with the following thicknesses, 800 nm, 80 nm, and 40 nm, and 600 nm, 80 nm, and 80 nm, achieved a maximum short-circuit current density of 21.46 mA/cm2 and a fill factor of 83.35%. As a result, the maximum value of each of the photoelectric parameters is found in structures of different thicknesses. These encouraging results are another step further in the design and manufacturing journey of PSCs as a promising alternative to silicon PV.

Full-scale testing of multiple span girders is scarce in the literature, often related to the complexity of loading setup and time constraints. The importance of full-scale tests is manifested in the fact that useful information regarding failure mechanisms can be obtained. In addition, important guidelines can be established for structural designers. Further, results from full-scale tests can help establish constitutive laws for various mechanisms involved in the response of actual structures. The structural performance of individual members can be assessed by monitoring their strains at service and ultimate loads. This study presents a comparison of experimentally monitored strains on longitudinal steel bars, stirrups, and prestressing tendons embedded in single and multi-span full-scale precast pre-tensioned girders. These girders were constructed and detailed to simulate the response of newly proposed straddle-type monorail girders. Single-span girders were tested under monotonic two-point service and ultimate loads, whereas multi-span girders were tested under both two- and four-point service and ultimate load. It was revealed that longitudinal steel and prestressing tendon strains monitored within single-span girders at service and ultimate loads were significantly higher than those recorded at corresponding locations in multi-span girders.

This research work is devoted to the experimental investigation of both rheological and mechanical properties of self-compacting concrete (SCC) produced with waste galvanized copper wire fiber and rice husk ash (RHA). In the study, three different volume fractions of 0.5 p to 0.75 percent, 1 percent of scrap copper wire fiber as reinforcing material, and 2 percent RHA as cement replacement were used. To evaluate the fresh characteristics of SCC, the slump flow, J-ring, and V-funnel experiments were conducted for this investigation. Compressive strength, splitting tensile strength, and flexural strength of the concrete were conducted to assess the hardened properties. The test was carried out to compare each characteristic of plain SCC with this modified SCC mixture, containing RHA as pozzolanic materials and copper fiber as reinforcing material. Incorporating copper fiber in the SCC leads to a drop in fresh properties compared to plain SCC but remains within an acceptable range. On the other hand, the inclusion of 2% RHA makes the SCC more viscous. Although adding 2% RHA and 1% copper wire in SCC provide the highest strength, this mix has an unacceptable passing ability. The SCC mix prepared with 2% RHA and 0.75% copper fiber is suggested to be optimum in terms of the overall performance. According to this study, adding metallic fiber reinforcement like copper wire and mineral admixture like RHA can improve the mechanical properties of SCC up to a certain level.

The utilization of waste industrial materials such as Blast Furnace Slag (BFS) and Fly Ash (F. Ash) will provide an effective alternative strategy for producing eco-friendly and sustainable concrete production. However, testing is a time-consuming process, and the use of soft machine learning (ML) techniques to predict concrete strength can help speed up the procedure. In this study, artificial neural networks (ANNs) and decision trees (DTs) were used for predicting the compressive strength of the concrete. A total of 1030 datasets with eight factors (OPC, F. Ash, BFS, water, days, SP, FA, and CA) were used as input variables for the prediction of concrete compressive strength (response) with the help of training and testing individual models. The reliability and accuracy of the developed models are evaluated in terms of statistical analysis such as R2, RMSE, MAD and SSE. Both models showed a strong correlation and high accuracy between predicted and actual Compressive Strength (CS) along with the eight factors. The DT model gave a significant relation to the CS with R2 values of 0.943 and 0.836, respectively. Hence, the ANNs and DT models can be utilized to predict and train the compressive strength of high-performance concrete and to achieve long-term sustainability. This study will help in the development of prediction models for composite materials for buildings.

Geotechnical investigation, in hilly areas, for high-rise projects, becomes a problematic issue and costly process due to difficulties in mobilization and assembling the drilling equipment on mountainous terrains. The objective of this study is to map soil properties of study areas, especially at inaccessible sites, for reconnaissance. Digital soil maps for Tehsil Murree, Pakistan, have been developed using the emerging Geographical Information System (GIS). The research work involved the creation of an exhaustive database, by collecting and rectifying geotechnical data, followed by the digitization of the acquired data through integration with GIS, in an attempt to visualize, analyze and interpret the collected geotechnical information spatially. The soil data of 205 explanatory holes were collected from the available geotechnical investigation (GI) reports. The collection depth of soil samples, which were initially used for the design of deep and shallow foundations by different soil consultancies in the Murree area, was approximately 50 ft. below ground level. Appropriate spatial interpolation methods (i.e., the Kriging) were applied for the preparation of smooth surface maps of soil standard penetration tester number values, soil type and plasticity index. The accuracy of developed SPT N value and plasticity maps were then evaluated using the linear regression method, in which the predicted values of soil characteristics from developed maps and actual values were compared. SPT N value maps were developed up to a depth of 9.14 m below ground level and at every 1.52 m interval. The depth of refusal was considered in the developed maps. Soil type and plasticity maps were generated up to 15.24 m depth, again at every 1.52 m intervals, using color contours, considering the maximum predicted foundation depth for high-rise projects. The study has implications for academics and practitioners to map the soil properties for inaccessible sites using GIS, as the resulting maps have high accuracy.

Several past studies have shown the use of glass fibre-reinforced polymer (GFRP) bars to alleviate the reinforced steel rusting issue in different concrete structures. However, the practise of GFRP bars in concrete columns has not yet achieved a sufficient confidence level due to the lack of a theoretical model found in the literature. The objective of the current study is to introduce a novel prediction model for the axial capability of concrete columns made with bars of GFRP. For this purpose, two different approaches, such as data envelopment analysis (DEA) and artificial neural networks (ANNs) modelling, are used on a collected dataset of 266 concrete column specimens made with GFRP bars from previous literature works. Eight parameters were used to predict the axial performance of GFRP-based RC columns. The proposed DEA and ANNs predictions demonstrated a good correlation with the testing dataset, having R2 values of 0.811 and 0.836, respectively. A comparative analysis of the DEA and ANNs models is undertaken, and it was found that the suggested models are capable of accurately forecasting the structural response of GFRP-made RC column structures. Then, a comprehensive parametric analysis of 266 GFRP-based columns was performed to study the effect of different materials and their geometrical shape.