Evaluation of calcium carbide residue and fly ash as sustainable binders for environmentally friendly loess soil stabilization.

The incorporation of waste materials into cementitious binders serves as a strategy to diminish waste volume and lower carbon emissions. This study presents an in-depth evaluation of calcium carbide residue and coal fly ash as alternative binders. The assessment of raw materials emphasized their chemical composition and potential for pozzolanic reactions. Based on these factors, the optimal ratio of Ca/(SiO2 + Al2O3) in the raw materials was determined to be 1.5. Therefore, this study was designed to vary the raw material composition with a CaO/(SiO2 + Al2O3) ratio ranging from 1.7 to 0.9. Upon investigating the effect of the raw material proportion on the compressive strength of pastes and mortars, the composition yielding the highest compressive strength was selected for its potential application as a stabilizer for loess soil. A mixture of calcium carbide residue and coal fly ash with a Ca/(SiO2 + Al2O3) ratio of 1.5 resulted in the highest compressive strength at long curing periods in both pastes and mortars. Mineralogical and microstructural analyses revealed several products, beyond those formed from the pozzolanic reactions, that occurred and enhanced the compressive strength of samples. The highest performing mixture of carbide residue and coal fly ash was then used to stabilize loess soil at 10-25 wt%. The unconfined compressive strength, along with mass and strength loss due to wetting and drying cycles, was also studied. It was observed that the unconfined compressive strength of the stabilized soils remained consistent after six wet-dry cycles but decreased after twelve cycles due to microcracks. The findings suggest that carefully designed mixtures based on the chemical interactions of calcium carbide residue and coal fly ash can offer a sustainable, efficient approach for soil stabilization, potentially revolutionizing construction practices.

Load-Bearing Performance of Non-Prismatic RC Beams Wrapped with Carbon FRP Composites.

This study investigated the influence of CFRP composite wrapping techniques on the load-deflection and strain relationships of non-prismatic RC beams. A total of twelve non-prismatic beams with and without openings were tested in the present study. The length of the non-prismatic section was also varied to assess the effect on the behavior and load capacity of non-prismatic beams. The strengthening of beams was performed by using carbon fiber-reinforced polymer (CFRP) composites in the form of individual strips or full wraps. The linear variable differential transducers and strain gauges were installed at the steel bars to observe the load-deflection and strain responses of non-prismatic RC beams, respectively. The cracking behavior of unstrengthened beams was accompanied by excessive flexural and shear cracks. The influence of CFRP strips and full wraps was primarily observed in solid section beams without shear cracks, resulting in enhanced performance. In contrast, hollow section strengthened beams exhibited minor shear cracks alongside the primary flexural cracks within the constant moment region. The absence of shear cracks was reflected in the load-deflection curves of strengthened beams, which demonstrated a ductile behavior. The strengthened beams demonstrated 40% to 70% higher peak loads than control beams, whereas the ultimate deflection was increased up to 524.87% compared to that of the control beams. The improvement in the peak load was more prominent as the length of the non-prismatic section increased. A better improvement in ductility was achieved for the case of CFRP strips in the case of short non-prismatic lengths, whereas the efficiency of CFRP strips was reduced as the length of the non-prismatic section increased. Moreover, the load-strain capacity of CFRP-strengthened non-prismatic RC beams was higher than the control beams.

Prediction of Stress-Strain Curves for HFRP Composite Confined Brick Aggregate Concrete under Axial Load.

Recently, hemp-fiber-reinforced polymer (HFRP) composites have been developed to enhance the strength and ductility of normal and lightweight aggregate concrete along with recycled brick aggregate concrete. In addition, both experimental and analytical investigations have been performed to assess the suitability of the existing strength and strain models. However, the theoretical and analytical expressions to predict the stress-strain curves of HFRP-confined concrete were not developed. Therefore, the main objective of this study was to develop analytical expressions to predict the stress-strain curves of HFRP-confined waste brick aggregate concrete. For this purpose, a new experimental framework was conducted to examine the effectiveness of HFRP in improving the mechanical properties of concrete constructed with recycled brick aggregates. Depending on the strength of the concrete, two groups were formed, i.e., Type-1 concrete and Type-2 concrete. A total of sixteen samples were tested. The ultimate compressive strength and strain significantly increased due to HFRP confinement. Improvements of up to 272% and 457% in the ultimate compressive strength and strain were observed due to hemp confinement, respectively. To predict the ultimate compressive strength and strain of HFRP-confined concrete, this study investigated several existing analytical stress-strain models. Some of the strength models resulted in close agreement with experimental results, but none of the models could accurately predict the ultimate confined strain. Nonlinear regression analysis was conducted to propose expressions to predict the ultimate compressive strength and strain of HFRP-confined concrete. The proposed expressions resulted in good agreement with experimental results. An analytical procedure was proposed to predict the stress-strain curves of hemp-confined concrete constructed by partial replacement of natural coarse aggregates by recycled fired-clay brick aggregates. A close agreement was found between the experimental and analytically predicted stress-strain curves.

Low-Cost Fiber Chopped Strand Mat Composites for Compressive Stress and Strain Enhancement of Concrete Made with Brick Waste Aggregates.

Given the excessive demolition of structures each year, the issues related to the generated structural waste are striking. Bricks being a major constituent in the construction industry, also hold a significant proportion of the construction waste generated annually. The reuse of this brick waste in new constructions is an optimal solution considering cost-effectiveness and sustainability. However, the problems related to the substandard peak stress and ultimate strain of concrete constructed with recycled brick aggregates (CRAs) limit its use in non-structural applications. The present study intends to improve the unsatisfactory mechanical characteristics of CRAs by utilizing low-cost glass fiber chopped strand mat (FCSM) sheets. The efficacy of FCSM sheets was assessed by wrapping them around CRA specimens constructed with different concrete strengths. A remarkable increase in the peak compressive stress and the ultimate strain of the CRA specimens were observed. For low, medium, and high strength CRAs, the ultimate strain improved by up to 320%, 308%, and 294%, respectively, as compared to the respective control specimens. Several existing analytical models were utilized to predict the peak compressive stress and ultimate strain of the CRAs strengthened using FCSM sheets. None of the considered models reproduced experimental results accurately. Therefore, equations were formulated using regression predicting the peak stress and ultimate strain of the CRAs confined with FCSM sheets. The predicted values were found to correlate well with the experimental values.

Mechanical Experiments on Concrete with Hybrid Fiber Reinforcement for Structural Rehabilitation.

Reinforced concrete is used in the construction of bridges, buildings, retaining walls, roads, and other engineered structures. Due to seismic activities, a lot of structures develop seismic cracks. The rehabilitation of such structures is necessary for public safety. The overall aim of this research study was to produce a high-performance hybrid fiber-reinforced concrete (HPHFRC) with enhanced properties as compared to plain high-performance concrete and high-performance fiber-reinforced concrete (HPFRC) for the rehabilitation of bridges and buildings. Kevlar fibers (KF) and glass fibers (GF) with lengths of 35 mm and 25 mm, respectively, were added and hybridized to 1.5% by mass of cement to create hybrid fiber-reinforced concrete mixes. Eight mixes were cast in total. The compressive strength (f'c), flexural strength (fr), splitting tensile strength (fs), and other mechanical properties, i.e., energy absorption and toughness index values, were enhanced in HPHFRC as compared to CM and HPFRC. It was found that the concrete hybridized with 0.75% KF and 0.75% GF (HF-G 0.75 K 0.75) had the most enhanced overall mechanical properties, illustrating its potential to be utilized in the rehabilitation of bridges and structures.

Use of Natural and Synthetic Fiber-Reinforced Composites for Punching Shear of Flat Slabs: A Comparative Study.

Over the last two decades, considerable attention has been devoted to the strengthening of sub-standard flat-slab constructions. With the evolution of composite materials and an increasing emphasis on the economical and sustainable use of natural fibers, many researchers have utilized them in the strengthening of flat flabs mitigating punching failures. This study aims at investigating and comparing the behavior of flat slabs strengthened with post-installed composite and natural reinforcements. An experimental program was devised consisting of eight flat-slab specimens. One specimen was tested in as-built condition to provide a reference. The remaining specimens were strengthened with Carbon Fiber-Reinforced Polymer (CFRP), Aramid Fiber-Reinforced Polymer (AFRP), and sisal rods. The pattern of post-installed rods was varied as single line, double line, and star shapes around the column. The results indicated that the single-line pattern could only enhance the maximum sustained load by up to 6% compared to that of the reference specimen. On the contrary, double line and star shape configurations resulted in a substantial increase in the maximum sustained load. An analytical assessment of ACI 318-19 provisions resulted in an over-estimation of the shear strengths of CFRP- and AFRP-strengthened slabs. Furthermore, the same provisions led to lower yields than experimental shear strengths for sisal-strengthened slabs.

Predicting the Mechanical Properties of RCA-Based Concrete Using Supervised Machine Learning Algorithms.

Environment-friendly concrete is gaining popularity these days because it consumes less energy and causes less damage to the environment. Rapid increases in the population and demand for construction throughout the world lead to a significant deterioration or reduction in natural resources. Meanwhile, construction waste continues to grow at a high rate as older buildings are destroyed and demolished. As a result, the use of recycled materials may contribute to improving the quality of life and preventing environmental damage. Additionally, the application of recycled coarse aggregate (RCA) in concrete is essential for minimizing environmental issues. The compressive strength (CS) and splitting tensile strength (STS) of concrete containing RCA are predicted in this article using decision tree (DT) and AdaBoost machine learning (ML) techniques. A total of 344 data points with nine input variables (water, cement, fine aggregate, natural coarse aggregate, RCA, superplasticizers, water absorption of RCA and maximum size of RCA, density of RCA) were used to run the models. The data was validated using k-fold cross-validation and the coefficient correlation coefficient (R2), mean square error (MSE), mean absolute error (MAE), and root mean square error values (RMSE). However, the model's performance was assessed using statistical checks. Additionally, sensitivity analysis was used to determine the impact of each variable on the forecasting of mechanical properties.

Finite Element Analysis of Glass Fiber-Reinforced Polymer-(GFRP) Reinforced Continuous Concrete Beams.

Fiber-reinforced concrete (FRC) is a competitive solution for the durability of reinforced structures. This paper aims to observe the moment redistribution behavior occurring due to flexural and shear loading in Glass Fiber-Reinforced Polymer- (GFRP) reinforced continuous concrete beams. A rectangular cross-section was adopted in this study with dimensions of 200 mm in width and 300 mm in depth with a constant shear span-to-depth ratio of 3. The reinforcement ratio for the top and bottom were equal at sagging and hogging moment regions. A finite element model was created using Analysis System (ANSYS) and validated with the existing experimental results in the literature review. Based on the literature review, the parametric study was conducted on twelve beam specimens to evaluate the influence of concrete compressive strength, transversal GFRP stirrups ratio, and longitudinal reinforcement ratio on the redistribution of the moment in beams. Several codes and guidelines adopted different analytical models. The Canadian Standards Association (CSA) S806 adopted the modified compression field theory in predicting the shear capacity of the simply supported beams. Recently, various researchers encountered several factors and modifications to account for concrete contribution, longitudinal, and transverse reinforcement. A comparison between the predicting shear capacity of the generated finite element model, the analytical model, and the existing data from the literature was performed. The generated finite element model showed a good agreement with the experimental results, while the beam specimens failed in shear after undergoing significant moment redistribution from hogging to sagging moment region. The moment distribution observed about 21.5% from FEM of beam specimen GN-1.2-0.48-d, while the experimental results achieved 24% at failure load. For high strength concrete presented in beam specimen GH-1.2-0.63-d, the result showed about 20.2% moment distribution, compared to that achieved experimentally of 23% at failure load.

Computation of High-Performance Concrete Compressive Strength Using Standalone and Ensembled Machine Learning Techniques.

The current trend in modern research revolves around novel techniques that can predict the characteristics of materials without consuming time, effort, and experimental costs. The adaptation of machine learning techniques to compute the various properties of materials is gaining more attention. This study aims to use both standalone and ensemble machine learning techniques to forecast the 28-day compressive strength of high-performance concrete. One standalone technique (support vector regression (SVR)) and two ensemble techniques (AdaBoost and random forest) were applied for this purpose. To validate the performance of each technique, coefficient of determination (R2), statistical, and k-fold cross-validation checks were used. Additionally, the contribution of input parameters towards the prediction of results was determined by applying sensitivity analysis. It was proven that all the techniques employed showed improved performance in predicting the outcomes. The random forest model was the most accurate, with an R2 value of 0.93, compared to the support vector regression and AdaBoost models, with R2 values of 0.83 and 0.90, respectively. In addition, statistical and k-fold cross-validation checks validated the random forest model as the best performer based on lower error values. However, the prediction performance of the support vector regression and AdaBoost models was also within an acceptable range. This shows that novel machine learning techniques can be used to predict the mechanical properties of high-performance concrete.

Prediction of Geopolymer Concrete Compressive Strength Using Novel Machine Learning Algorithms.

The innovation of geopolymer concrete (GPC) plays a vital role not only in reducing the environmental threat but also as an exceptional material for sustainable development. The application of supervised machine learning (ML) algorithms to forecast the mechanical properties of concrete also has a significant role in developing the innovative environment in the field of civil engineering. This study was based on the use of the artificial neural network (ANN), boosting, and AdaBoost ML approaches, based on the python coding to predict the compressive strength (CS) of high calcium fly-ash-based GPC. The performance comparison of both the employed techniques in terms of prediction reveals that the ensemble ML approaches, AdaBoost, and boosting were more effective than the individual ML technique (ANN). The boosting indicates the highest value of R2 equals 0.96, and AdaBoost gives 0.93, while the ANN model was less accurate, indicating the coefficient of determination value equals 0.87. The lesser values of the errors, MAE, MSE, and RMSE of the boosting technique give 1.69 MPa, 4.16 MPa, and 2.04 MPa, respectively, indicating the high accuracy of the boosting algorithm. However, the statistical check of the errors (MAE, MSE, RMSE) and k-fold cross-validation method confirms the high precision of the boosting technique. In addition, the sensitivity analysis was also introduced to evaluate the contribution level of the input parameters towards the prediction of CS of GPC. The better accuracy can be achieved by incorporating other ensemble ML techniques such as AdaBoost, bagging, and gradient boosting.

Application of Advanced Machine Learning Approaches to Predict the Compressive Strength of Concrete Containing Supplementary Cementitious Materials.

The casting and testing specimens for determining the mechanical properties of concrete is a time-consuming activity. This study employed supervised machine learning techniques, bagging, AdaBoost, gene expression programming, and decision tree to estimate the compressive strength of concrete containing supplementary cementitious materials (fly ash and blast furnace slag). The performance of the models was compared and assessed using the coefficient of determination (R2), mean absolute error, mean square error, and root mean square error. The performance of the model was further validated using the k-fold cross-validation approach. Compared to the other employed approaches, the bagging model was more effective in predicting results, with an R2 value of 0.92. A sensitivity analysis was also prepared to determine the level of contribution of each parameter utilized to run the models. The use of machine learning (ML) techniques to predict the mechanical properties of concrete will be beneficial to the field of civil engineering because it will save time, effort, and resources. The proposed techniques are efficient to forecast the strength properties of concrete containing supplementary cementitious materials (SCM) and pave the way towards the intelligent design of concrete elements and structures.

Flexural Behavior of Natural Hybrid FRP-Strengthened RC Beams and Strain Measurements Using BOTDA.

Experimental and finite element analysis results of reinforced concrete beams under monotonic loading were presented in this study. In the experimental program, one beam was tested in an as-built condition. The other two beams were strengthened using natural hybrid FRP layers in different configurations. The natural hybrid FRP composite was developed by using natural jute FRP and basalt FRP. One of the most appealing advantages of natural fiber is its beneficial impact on the environment, which is necessary for the sustainability recognition as an alternative to synthetic FRP. The hybrid FRP was applied to the bottom concrete surface in one beam, while a U-shaped strengthening pattern was adopted for the other beam. The flexural behavior of each beam was assessed through strain measurements. Each beam was incorporated with conventional strain gages, as well as the Brillouin Optical Time Domain Analysis (BOTDA) technique. BOTDA has its exclusive advantages due to its simple system architecture, easy implementation, measurement speed, and cross-sensitivity. The experimental results revealed that the beam strengthened with the U-shaped hybrid FRP composite pattern had a better flexural response than the other counterpart beams did both in terms of peak loads and maximum bottom longitudinal steel bar strains. Beams B-01 and B-02 exhibited 20.5% and 28.4% higher energy dissipation capacities than the control beam did, respectively. The ultimate failure of the control beam was mainly due to the flexural cracks at very low loads, whereas the ultimate failure mode of FRP composite-strengthened beams was due to the rupture of the hybrid FRP composite. Further, strain measurements using BOTDA exhibited similar patterns as conventional strain gage measurements did. However, it was concluded that BOTDA measurements were substantially influenced by the bottom flexural cracks, ultimately resulting in shorter strain records than those of conventional strain gages. Nonlinear structural analysis of the beams was performed using the computer program ATENA. The analytical results for the control beam specimen showed a close match with the corresponding experimental results mainly in terms of maximum deflection. However, the analytical peak load was slightly higher than the corresponding experimental value.

Remediation of Punching Shear Failure Using Glass Fiber Reinforced Polymer (GFRP) Rods.

The results of an experimental program on shear-strengthening of flat slabs using Glass Fiber Reinforced Polymer (GFRP) rods are presented. A total of seven specimens were tested under an upward concentric monotonic loading until failure. One specimen served as a control and was tested without any modification. The remaining six specimens were strengthened with post-installed GFRP rods in single (SG), double (DB), and radial (RD) patterns within shear critical parameters around the centric column. The results of this experimental study suggest that GFRP rods are capable of enhancing both the peak load and deformation capacity. Furthermore, brittle failure associated with punching shear failure was successfully avoided by all strengthening patterns. Of all of the patterns, the RD pattern resulted in maximum peak load increase and corresponding deformation capacity while the lowest bound was created by the SG pattern. The results suggested that SG, DB and RD patterns enhanced ultimate loads up to 9.1, 11.3 and 15.7% while corresponding deflections increased up to 109, 136 and 154%. Strain measurement on flexural reinforcement suggested that all strengthened specimens were able to withstand higher longitudinal strains than yield. It was further shown that reducing the spacing between the GFRP rods efficiently enhanced peak loads, nevertheless, neither this change was proportional, nor did it result in an enhanced energy dissipation capacity. In the end, recommendations of American Concrete Institute (ACI) for the shear strength of two-way systems were modified to incorporate the contributions from GFRP rods. The results indicate that the proposed analytical approach provides an excellent match with the experimental results.

Structural Behavior of Large-Scale Hollow Section RC Beams and Strength Enhancement Using Carbon Fiber Reinforced Polymer (CFRP) Composites.

An experimental program was conducted to ascertain the efficiency of Carbon Fiber Reinforced Polymer (CFRP) in enhancing the flexural response of hollow section reinforced concrete (RC) beams. Nine beams were tested under four-point bending in three groups. Beams were categorized to reflect the presence or configuration of the CFRP sheet. Each group consisted of three beams: one with a solid section, one with a square 50×50  mm × mm opening and 1 with 100×100  mm × mm opening. Beams in 1st group were tested in as-built conditions. Beams in the 2nd group were strengthened with a single CFRP sheet bonded to their bottom sides. Configuration of CFRP sheet was altered to U-shape applied to the tension side of 3rd group beams. The inclusion of openings, regardless of their size, did not result in degradation of ultimate load and corresponding deflections. However, cracking loads were found to decline as the opening size increased. Regardless of the opening size and CFRP configuration, ultimate loads of beams increased with the application of CFRP. However, this improvement was limited to the debonding and rupture of CFRP in group 2 and 3 beams, respectively. A comparison in the behavior of group 2 and 3 beams revealed that the application of the U-shape CFRP sheet yielded better flexural performance in comparison with the flat-CFRP sheet bonded to the bottom of beams. In the end, In order to further evaluate the economic and performance benefits of these beams, the cost-benefit analysis was also performed. The analysis showed that the feasibility of the hollow section RC beams is more than the solid section RC beams.

Utilization of Several Industrial Wastes as Raw Material for Calcium Sulfoaluminate Cement.

The aim of this research was to study the production of calcium sulfoaluminate (CSA) cement from several industrial waste materials including with marble dust waste, flue gas desulfurization gypsum, ceramics dust waste, and napier grass ash. The chemical composition, microstructure, and phase composition of raw materials were examined using energy dispersive X-ray fluorescence (EDXRF), scanning electron microscopy (SEM), and X-ray diffraction (XRD), respectively. All raw wastes were analyzed using their chemical composition to assign proportion for raw mixture. The raw mixture is calcined at controlled calcination temperatures ranging from 1200 °C to 1300 °C for 30 min. Subsequently, with analysis, their phase composition is calculated by the Rietveld refinement technique. The results suggested that phase composition of clinker calcined at 1250 °C shows the closest composition when compared to target phases, and was selected to prepare CSA cement. The FTIR analysis was performed to study the hydration processes of CSA cement. The Ordinary Portland cement (OPC) based with adding CSA cement between 20 wt.% and 40 wt.% were investigated for the effect of CSA cement fraction on water requirement, setting times and compressive strength. The results showed that rapid setting and high early strength can be achieved by the addition of 20-40 wt.% CSA cement to OPC.