Optimizing concrete for circularity: a comparative life cycle assessment of geopolymer and ordinary concrete.

Geopolymer concrete is a sustainable construction material developed with industrial by-products to eliminate the use of cement in concrete production. However, a cradle-to-cradle life cycle assessment (LCA) that accounts for the impact of service life is essential to comprehensively assess the environmental advantages of GPC. In this study, a comparative cradle-to-cradle LCA was performed for circular geopolymer concrete (CGPC), geopolymer concrete (GPC), and circular ordinary concrete (COC), as alternatives to Portland cement concrete (PCC). Also, the biases of common LCA resulted from ignoring service life and end-of-life scenarios were identified. Finally, the sustainability potentials of the alternative scenarios were evaluated. According to the cradle-to-cradle LCA using the adopted functional unit, GPC and CGPC significantly alleviated the environmental impact of cement production, such as global warming potential by about 53%. Ignoring the service life and end-of-life scenarios considerably changed the critical midpoint (ionizing radiation for CGPC and GPC) and endpoint indicators (resources for CGPC and GPC) and priority of alternative concretes. Finally, the CGPC and GPC showed a substantial increase of 213% and 276% in sustainability potential compared to PCC, respectively.

Analytical solution of nano-concrete-epoxy interaction area considering static equilibrium.

This research proposes an analytical solution of the nano-concrete-epoxy interaction area within nano crack region of the reinforced concrete beam by applying Newton's third law in static equilibrium. For deriving the governing equation, the imaginary beam with free ends (no support) is considered within nano crack region. This imaginary beam is acted along the imaginary line of concrete-epoxy interface. Newton's third law is applicable for deriving the governing equation because of assuming the absence of frictional and other external forces. The parametric study is performed for implementing the proposed formula of nano interactive area considering variable nano crack depths and thicknesses. The nano interactive area is increased gradually with the increment of depths and thicknesses based on the parametric study because of linear functionality of interactive area and geometry of nano crack region. The maximum interactive area is found to be 314 nm2 at 0.6 ratio of depths and thicknesses of the nano crack. The incremental differences in interactive area between the crack depth or thickness ratios of 0.1 and 0.6 are found to be 25.4% and 1.6% for variations of the crack depth and thickness ratios, respectively. So, the crack depth shows higher impact on the interaction area compared to the thickness of the crack. However, there is a scope for enhancing this research in future by deriving closed-formed analytical formulations to consider appropriate boundary conditions.

Activation technology of steel slag for concrete exposed to plateau climate: a state-of-the-art review.

As a byproduct of steelmaking, steel slag occupies significant land resources and poses potential environmental and safety challenges due to its extensive accumulation. Recently, steel slag has shown promising applications in the field of concrete. However, considering the complexity of the plateau environment, the utilization of steel slag is relatively lacking, and its low reactivity and poor volume stability remain the main factors restricting its application in plateau concrete. This paper reviews the research status of steel slag activation techniques for concrete, including wet grinding, chemi-excitation, high-temperature activation, and carbonation treatment. The effects of different treatment techniques on the mechanical and durability properties of concrete and the potential issues are discussed. Although different modification methods can improve the activity and volume stability of steel slag to varying degrees, a single modification technology is difficult to achieve the high-quality utilization of steel slag in concrete on the plateau. Based on this, a steel slag grading grinding-magnetic separation utilization technique suitable for high-altitude areas is proposed, which is beneficial for improving the added value and utilization rate of steel slag in concrete.

Axial compression performances and bearing capacity prediction of self-compacting fly ash concrete filled circle steel tube columns.

To solve the problem of a large amount of fly ash accumulation and study the axial compression and bearing capacity prediction of the self-compacting fly ash concrete filled circle steel tube (SCCFST) columns, eight specimens are designed to explore the impact of concrete strength grade, internal structural measures, and additional parameters. The stress, progression of deformation, and failure mode of each specimen are observed during the loading process. The load-displacement curves, load-strain curves, characteristic load and displacement, ductility, and stiffness degradation are analyzed. The findings revealed that shear deformation occurred predominantly in the middle and upper portions of the steel tubes. Enhancing the strength of the concrete or adopting internal structural measures could increase the bearing capacity and ductility of the specimens. The peak load and ductility could be increased by up to 17.6 and 53.6%, respectively. The proposed unified calculation equation for the axial compression bearing capacity of SCCFST columns demonstrates notable reliability and precision. Furthermore, these tests offer valuable references for the engineering application of various forms of SCCFST columns, which are of significant importance in practical engineering.

Evaluating the Influence of Nano-GO Concrete Pavement Mechanical Properties on Road Performance and Traffic Safety Using ANN-GA and PSO Techniques.

The burgeoning demand for durable and eco-friendly road infrastructure necessitates the exploration of innovative materials and methodologies. This study investigates the potential of Graphene Oxide (GO), a nano-material known for its exceptional dispersibility and mechanical reinforcement capabilities, to enhance the sustainability and durability of concrete pavements. Leveraging the synergy between advanced artificial intelligence techniques-Artificial Neural Networks (ANN), Genetic Algorithms (GA), and Particle Swarm Optimization (PSO)-it is aimed to delve into the intricate effects of Nano-GO on concrete's mechanical properties. The empirical analysis, underpinned by a comparative evaluation of ANN-GA and ANN-PSO models, reveals that the ANN-GA model excels with a minimal forecast error of 2.73%, underscoring its efficacy in capturing the nuanced interactions between GO and cementitious materials. An optimal concentration is identified through meticulous experimentation across varied Nano-GO dosages that amplify concrete's compressive, flexural, and tensile strengths without compromising workability. This optimal dosage enhances the initial strength significantly, and positions GO as a cornerstone for next-generation premium-grade pavement concretes. The findings advocate for the further exploration and eventual integration of GO in road construction projects, aiming to bolster ecological sustainability and propel the adoption of a circular economy in infrastructure development.

Experimental investigation of quarry rock dust incorporated fly ash and slag based fiber reinforced geopolymer concrete circular columns.

Manufacturing ordinary Portland cement (OPC) poses significant challenges for sustainable construction practices. OPC manufacturing emits substantial greenhouse gases into the atmosphere and demands extensive raw materials. In pursuit of greener alternatives, researchers explore geopolymer concrete (GPC), a revolutionary material that entirely replaces OPC, comprising industrial wastes/by-products activated through an alkaline solution. The study aims to investigate the feasibility of incorporating quarry rock dust (QRD) into GPC production for environmentally sustainable structural applications. Circular columns (200 mm diameter, 1000 mm length) were formulated using GPC blends with fly ash, slag (SG), and QRD as a partial SG replacement. The structural performance of these columns, with and without steel fiber reinforcement, was evaluated under varied loading conditions. Results show that QRD is a valuable ingredient in GPC for structural concrete elements, offering performance comparable to traditional OPC concrete. Furthermore, the incorporation of steel fibers significantly enhances the peak axial loads, displacement response, and overall performance of GPC columns with or without QRD. Fiber-reinforced GPC columns demonstrated approximately 8-10% higher ultimate load capacity than equivalent OPC columns. Eccentricity was found to significantly reduce ductility, but fiber reinforcement offers substantial ductility improvements (25-55%).

Establishment of quadratic exponential quality gain-loss function model and design of process mean.

Taking into account the fluctuation of the growth rate on the left and right sides of the classic QGLF, a quadratic exponential quality gain-loss function (QGLF) is created based on the asymmetric QGLF. The two scenarios of non-normal distribution (triangular distribution) and truncated normal distribution of quality characteristic values are optimized using the quadratic exponential quality gain-loss process mean. Through the case study approaches, the empirical validity and applicability of the quadratic exponential QGLF model are thoroughly assessed, confirming its effectiveness in improving quality management practices.

Designing a reliable machine learning system for accurately estimating the ultimate condition of FRP-confined concrete.

Precisely forecasting how concrete reinforced with fiber-reinforced polymers (FRP) responds under compression is essential for fine-tuning structural designs, ensuring constructions fulfill safety criteria, avoiding overdesigning, and consequently minimizing material expenses and environmental impact. Therefore, this study explores the viability of gradient boosting regression tree (GBRT), random forest (RF), artificial neural network-multilayer perceptron (ANNMLP) and artificial neural network-radial basis function (ANNRBF) in predicting the compressive behavior of fiber-reinforced polymer (FRP)-confined concrete at ultimate. The accuracy of the proposed machine learning approaches was evaluated by comparing them with several empirical models concerning three different measures, including root mean square errors (RMSE), mean absolute errors (MAE), and determination coefficient (R2). In this study, the evaluations were conducted using a substantial collection of axial compression test data involving 765 circular specimens of FRP-confined concrete assembled from published sources. The results indicate that the proposed GBRT algorithm considerably enhances the performance of machine learning models and empirical approaches for predicting strength ratio of confinement (f'cc/f'co) by an average improvement in RMSE as 17.3%, 0.65%, 66.81%, 46.12%, 46.31%, 46.87% and 69.94% compared to RF, ANNMLP, ANNRBF, and four applied empirical models, respectively. It is also found that the proposed ANNMLP algorithm exhibits notable superiority compared to other models in terms of reducing RMSE values as 9.67%, 11.29%, 75.11%, 68.83%, 73.64%, 69.49% and 83.74% compared to GBRT, RF, ANNRBF and four applied empirical models for predicting strain ratio of confinement (εcc/εco), respectively. The superior performance of the GBRT and ANNMLP compared to other methods in predicting the strength and strain ratio confinements is important in evaluating structural integrity, guaranteeing secure functionality, and streamlining engineering plans for effective utilization of FRP confinement in building projects.

Performance evaluation of indented macro synthetic polypropylene fibers in high strength self-compacting concrete (SCC).

Concrete is used worldwide as a construction material in many projects. It exhibits a brittle nature, and fibers' addition to it improves its mechanical properties. Polypropylene (PP) fibers stand out as widely employed fibers in concrete. However, conventional micro-PP fibers pose challenges due to their smooth texture, affecting bonding within concrete and their propensity to clump during mixing due to their thin and soft nature. Addressing these concerns, a novel type of PP fiber is proposed by gluing thin fibers jointly and incorporating surface indentations to enhance mechanical anchorage. This study investigates the incorporation of macro-PP fibers into high-strength concrete, examining its fresh and mechanical properties. Three different concrete strengths 40 MPa, 45 MPa, and 50 MPa, were studied with fiber content of 0-1.5% v/f. ASTM specifications were utilized to test the fresh and mechanical properties, while the RILEM specifications were adopted to test the bond of bar reinforcements in concrete. Test results indicate a decrease in workability, increased air content, and no substantial shift in fresh concrete density. Hardened concrete tests, adding macro-PP fibers, show a significant increase in splitting tensile strength, bond strength, and flexural strength with a maximum increase of 34.5%, 35%, and 100%, respectively. Concrete exhibits strain-hardening behavior with 1% and 1.5% fiber content, and the flexural toughness increases remarkably from 2.2 to 47.1. Thus, macro PP fibers can effectively improve concrete's mechanical properties and resistance against crack initiation and spread.

Effect of vibration on the interface properties of welded steel joints and filled concrete in steel pipes.

Concrete-filled steel tubes (CFSTs) have been increasingly utilized in engineering due to their excellent mechanical properties. Ensuring a solid bond between a steel tube and concrete is essential for optimizing their synergistic effect. This study introduces an internally welded steel bar structure within the inner wall of a steel tube to enhance the bond properties at the connection interface. The influence of various configurations of steel bars welded to the inner surface of the tube on the bond strength is investigated considering the impact of vibration on the load-bearing capacity of the component. This study comprises two groups of specimens, one with vibration and one without vibration, for a total of ten specimens. Each group included CFST members with five distinct internal welded steel bar structures. The experimental results, including load-displacement curves and strain data of the steel tube, were used to assess the impact of the internal welded steel bar configurations on the steel-concrete interface. The sliding process is described by correlating test data with curves and observed phenomena. To comprehensively compare the effects of structural dimensions on the bonding and slipping properties of the welded bars, finite element simulations replicating the experimental conditions were carried out using ABAQUS software, and the simulation results agreed with the experimental observations. The study demonstrated that incorporating internal welded steel bars substantially enhances the bond strength of steel pipe-concrete interfaces. While vibration weakens the bond strength in CFST members, internal welded steel bars mitigate this effect. These findings improve the structural performance of CFST structures and their resilience to external vibrations.

A study on the bond strength and durability characteristics of high-performance concrete modified with toughened glass waste aggregates.

Amidst rising natural aggregate consumption, recycling dumped waste for structural concrete effectively addresses resource scarcity and environmental contamination. Nevertheless, the adoption of toughened glass waste aggregate (TGWA) in construction remains relatively limited. This study explores the potential use of toughened glass waste (TGW) as a substitute for natural coarse aggregate (NCA) in high-performance concrete (HPC). This paper assesses the bond strength of deformed bars embedded in toughened glass waste high-performance concrete (TGW-HPC), considering different steel reinforcement diameters (8 mm and 12 mm) and various levels of TGW replacement (ranging from 0 % to 100 %). Various durability properties, including water absorption, water permeability, chloride ion penetration, and acid attack were examined. The study also investigated the microstructural characteristics of acid attacked specimens using techniques such as XRD, FTIR, and FESEM. Several important parameters, such as chloride diffusivity (D), hydraulic diffusivity (D (θ)), and permeability coefficients (K), were derived from the experimental data. The study found TGW50-HPC resulted in the highest bond strength, about 13.1 % more than the control mix. However, TGW100-HPC bond strength decreased by 17.51 % compared to the control mix. Notably, TGW100-HPC exhibited superior durability properties and showed the lowest coefficient of permeability, indicating reduced chloride ion, and water molecule transport through the interconnected pore structure. At 90 days, the TGW100-HPC mixture exhibited a strength reduction of 42.29 %, which closely resembled the 41.20 % reduction observed at 56 days. The formation of thenardite and basanite mitigate damage to the interfacial transition zone (ITZ) led to fewer micro-cracks and reduced acid ingress through the matrix. Incorporating TGWA in engineering projects can lead to cost savings through reduced raw material expenses and disposal fees, resulting in significant economic benefits and social well-being.

Development and systematic review of connection techniques for RC Precast structural elements: Beam and Column Connection.

Precast reinforcement concrete (RC) structures have attracted increasing attention in the global construction industry. They offer advantages such as reduced construction time, improved quality, and sustainability. However, their seismic performance and construction pose unique challenges. This study comprehensively reviewed and systematically analyzed the nodal connection techniques of RC precast structures. Using a data-driven approach combining quantitative and qualitative analyses, relevant literature was collected from the Web of Science database based on specific search criteria. Historical and recent trends in the scientific landscape were visualized, and citation networks were analyzed. In addition, the study reviewed different types of beam-column connections, which is a significant research focus. The results indicate that although various types of nodal connections demonstrate good seismic performance in experiments, they still face challenges of complexity and long-term maintenance in actual construction.

Dataset on early-age strength of ambient-cured geopolymer mortars from waste concrete and bricks with different alkaline activators.

The dataset presented here emanates from preliminary studies that compared the early-age compressive strengths of geopolymer mortars produced from construction and demolition wastes (CDW) commonly found in Qatar using different alkaline activators. Waste concrete, waste bricks and steel slag were used as aluminosilicate sources for the geopolymer mortars. Waste concrete was used as fine aggregate (75 µm to 4 mm), while solid or hollow red clay bricks were used together with steel slag as aluminosilicate powders. Solid red clay brick (75 µm to 1.4 mm) was also considered as fine aggregate. Different alkaline activators including solid powder or ground pellet forms of Ca(OH)2, CaO, and Ca(OH)2-NaOH, NaOH-CaCO3 and Na2SiO3-Na2CO3-Ca(OH)2 mixtures were employed by just adding water. Both solid powder Ca(OH)2 and viscous solutions of NaOH and NaOH-Na2SiO3 were also considered as alkaline activators. The geopolymer mortars included small amounts of some other additives such as gypsum, microsilica and aluminium sulfate to enhance the geopolymerization and hydration process. Random proportions of the materials were employed in the range-finding experiments, and the mortars produced were tested for compressive strength. The dataset shows the 7-day compressive strengths and densities of the 40 mixtures tested with mostly ambient temperature (20°C) curing. It also shows such data for mixtures in which variables such as curing at 40°C, mixing with hot water at 50 - 60°C temperature, grading of waste concrete aggregates, and collective grinding of the powdered materials were considered. The data indicates possible early-age compressive strengths of different geopolymer mortar mixture designs and the materials and mixture design methods that can be used to achieve desired early-age strengths from waste concrete and bricks.

Investigation on the mechanical properties of Bacillus subtilis self-healing concrete.

In the process of research and development of self-healing concrete, it is observed that there are three main factors controlling the self-healing effect of concrete: first, the bacteria with repair ability and strong vitality; Second, the carrying capacity of the carrier and the matching degree with concrete; The third is the concentration of bacteria. This paper focuses on the mechanical properties of Bacillus subtilis self-healing concrete with sisal fiber, PVA, and expanded perlite as the carrier. To better study the mechanical properties of self-healing concrete caused by the carrier, the experiment adopts the design parameters of C30 concrete and conducts experiments on compressive resistance, flexural resistance, freeze-thaw cycle, and sulfate corrosion resistance to analyze the influence of different carriers on the mechanical properties of self-healing concrete, and obtains the best carrier. The concentration gradients of three groups of bacterial solution were set as 2od, 2.5od, and 3od, respectively, for comparison to avoid the influence of bacterial concentration. It compared the impact of bacterial solution concentrations on the specimen's mechanical properties, and the effect of carriers was also analyzed. The experimental results show that the mechanical properties of the specimen using 2.5od bacterial liquid concentration with PVA as the carrier have peaked. With the increase in bacterial solution concentration, the specimens' comprehensive mechanical properties increased first and then decreased. The compression resistance of the specimen with PVA is higher than that of the specimen with sisal fiber and expanded perlite. At the same time, the frost resistance and corrosion resistance of the PVA carrier specimen is also higher than that of the specimen with sisal fiber and expanded perlite carrier.

Optimizing compressive strength prediction using adversarial learning and hybrid regularization.

The infrastructure industry consumes natural resources and produces construction waste, which has a detrimental impact on the environment. To mitigate these adverse effects and reduce raw material consumption, waste materials can be repurposed to achieve sustainability. However, recycled materials deteriorate the intrinsic properties of concrete. A suitable ratio of natural resources and recycled aggregates can produce the desired compressive strength. Compiling sufficient data in civil engineering laboratories to make reliable conclusions is time-consuming and costly. Therefore, this research proposes a novel approach for predicting compressive strengths using limited data. The generative adversarial network was employed to generate synthetic data. Hybrid training, utilizing either conventional loss or heuristic loss, prevents the model from overfitting by adaptively adjusting the regularization term. Random noise from a multivariate normal distribution is embedded heuristically into the training samples to capture intricate data variations. Sensitivity analysis indicated that the size of recycled coarse aggregate and water are the most significant features, aligning with their correlations. Interestingly, superplasticizer, density of recycled coarse aggregate, and water absorption ratio of recycled coarse aggregate contributed significantly to predictions despite their low correlations. The propounded method outperforms random forest, support vector regression, artificial neural network, and adaptive boosting by scoring a mean squared error of 7.97, a root mean squared error of 2.82, a mean absolute error of 2.13, and a coefficient of determination of 0.96. These results suggest that the proposed technique can effectively contribute to sustainable construction practices by accurately predicting compressive strengths.

Characterization of effective moisture diffusivity based on pore structure of concrete.

Concrete durability is greatly influenced by the transport rate of aggressive chemicals. Moisture diffusion plays a key role in the long-term performance of cementitious materials, as it facilitates the entry of aggressive chemicals into concrete. The pore size distribution plays a critical role in determining moisture diffusivity. However, the characteristics of the concrete pore structure have not been included comprehensively in the material models so far. In this paper, a theoretical model was developed to obtain the pore size volume fractions for each diffusion mechanism including Molecular, Knudsen and Surface diffusions. An effective moisture diffusivity in concrete was then obtained using the weighted average based on the diffusion mechanisms and pore size volume fractions. The model's validity was demonstrated by comparing model predictions with available experimental data. The findings of this study provide valuable insights into the behavior of the concrete pore structure and its impact on moisture diffusivity.

Enhancing intermediate temperature fracture resistance of stone matrix asphalt with untreated recycled concrete aggregate-Experimental dataset.

This data article presents details on the assessment of fracture parameters of laboratory asphalt mixtures produced using both natural and recycled concrete aggregates. The gap-graded stone matrix asphalt (SMA) is created by incorporating Trinidad Lake Asphalt (TLA) binder with carefully calibrated mixtures of recycled concrete aggregates (0 %, 10 %, 35 %, and 50 %) and natural aggregates (limestone and dust filler). The dataset variables were chosen based on the specifications of the single-edge notched beam (SENB) and semi-circular bending (SCB) tests, which are currently used for quality control and assurance (QC & QA) assessment of asphalt concrete mixtures. The data parameters provided include air void content, voids in mineral aggregates, voids filled with asphalt, density, Marshall Stability, Flow, test temperature, peak loads, RCA content, and notch depths. The fracture resistance of the mixes was studied by analysing the fracture energy, tensile strength, and fracture toughness for the collected dataset. The data shows that incorporating up to 10 % of RCA into SMA mixes, similar fracture properties can be achieved compared to traditional SMA mixtures. This presents a sustainable and environmentally advantageous option, however, it is important to exercise caution as the RCA content increases.

Experimental study on axial tensile properties of basalt fibre reinforced recycled aggregate concrete.

In order to investigate the tensile properties of basalt fibre reinforced recycled aggregate concrete (BFRAC), the axial tensile tests were carried out on BFRAC specimens using the concrete axial tensile testing device. The effects of basalt fibre (BF) content and recycled aggregate replacement rate on the tensile properties of BFRAC were quantitatively investigated, and the tensile damage mechanism of BFRAC was analysed. The following conclusions were drawn: The volume fraction of BF had the most prominent effect on the axial tensile properties of BFRAC. The axial tensile strength and peak tensile strain of BFRAC both showed the change rule of first increasing and then decreasing with the increase of BF volume fraction. The replacement rate of recycled aggregate is negatively correlated with the tensile properties of BFRAC. The larger the replacement rate, the worse the tensile properties of BFRAC. When the replacement rate of recycled aggregate is 30 % and the volume fraction of BF is 0.3 %, the tensile properties of BFRAC are better, as well as its economic and environmental performance. The axial tensile strength and peak tensile strain were 2.08 MPa and 114 × 10-6, respectively. BFRAC exhibits the toughening and crack arresting effect of BF, and the crack development is relatively slow, showing more obvious plastic damage characteristics.

Estimating the axial strain of circular short columns confined with CFRP under centric compressive static load using ANN and GRA techniques.

This investigation introduces advanced predictive models for estimating axial strains in Carbon Fiber-Reinforced Polymer (CFRP) confined concrete cylinders, addressing critical aspects of structural integrity in seismic environments. By synthesizing insights from a substantial dataset comprising 708 experimental observations, we harness the power of Artificial Neural Networks (ANNs) and General Regression Analysis (GRA) to refine predictive accuracy and reliability. The enhanced models developed through this research demonstrate superior performance, evidenced by an impressive R-squared value of 0.85 and a Root Mean Square Error (RMSE) of 1.42, and significantly advance our understanding of the behavior of CFRP-confined structures under load. Detailed comparisons with existing predictive models reveal our approaches' superior capacity to mimic and forecast axial strain behaviors accurately, offering essential benefits for designing and reinforcing concrete structures in earthquake-prone areas. This investigation sets a new benchmark in the field through meticulous analysis and innovative modeling, providing a robust framework for future engineering applications and research.

Seismic strategy of non-seismically designed reinforced concrete columns retrofitted with steel rods.

This paper presents experimental results of combined cyclic load testing on a reinforced concrete (RC) column that was retrofitted with newly designed steel rods. The steel rods were installed around the column longitudinally and then anchored. The proposed steel rods utilize simple components and installation to enhance both the strength and ductility of RC columns. Cyclic lateral load tests were conducted on three specimens: one unreinforced specimen as reference, one specimen with the entire length of the column retrofitted, and one specimen with only the plastic hinge region of the column retrofitted. All specimens were tested under eccentric constant axial load and incrementally increasing lateral loading cycles with eccentricity. The implementation of steel rods resulted in significant improvement in ductility and an up to 60% increase in ultimate loading capacity.