Up-scaling of fly ash-based geopolymer concrete to investigate the binary effect of locally available metakaolin with fly ash.

Owing to the increasing threat to environment due to the emission of greenhouse gases from cement industry globally, various promising solutions has been introduced in the past decades. The development of geoplymer concrete (GPC) is one of the contribution by the researches towards ecofriendly and sustainable construction. In this research, geopolymer concrete (GPC) is optimized by adding fixed amount of fly Ash (FA) and alkali activator to fine aggregate ratio as 0.5 with varying Molarity from 12 M to 16 M and Na2SiO3/NaOH ratio from 1.5 to 2.5. Physical and mechanical properties along with effect of heat and ambient curing conditions were investigated at various ages. The optimized mixture of fly ash based geopolymer concrete was then up scaled by blending with locally available Metakaolin (MK) with different dosages (i.e., 10%, 20%, 30%, 40%). The aim of the study is to identify the binary effect of FA and MK on overall performance of geopolymer concrete. Results showed that 30% FA-MK based GPC depicted 21%, 19% and 26% more compressive strength, split tensile strength and flexural strength respectively than Fly Ash based GPC alone at heat cured condition. This can be explained mainly due to two facts namely binary action of metakaolin that enhances compaction of GPC and pozzolanic activity of MK that expedite geopolymeric strength causing phases. The results were further verified by Modified Chapelle test and FTIR. Morphology of the developed GPC is also examined from SEM images. The work is an effort to utilize the fly ash produced by coal power plants to effectively address UN sustainable development goal related to sustainable cities and communities.

Flexure Performance of Ferrocement Panels Using SBR Latex and Polypropylene Fibers with PVC and Iron Welded Meshes.

Ferrocement panels are thin-section panels that are widely used in lightweight construction. Due to lesser flexural stiffness, they are susceptible to surface cracking. Water may penetrate through these cracks and may cause corrosion of conventional thin steel wire mesh. This corrosion is one of the major factors which affect the load-carrying and durability of ferrocement panels. There is a need to improve the mechanical performance of ferrocement panels either through using some non-corrodible reinforcing mesh or through improving the cracking behavior of the mortar mix. In the present experimental work, PVC plastic wire mesh is employed to address this problem. SBR latex and polypropylene (PP) fibers are also utilized as admixtures to control the micro-cracking and improve the energy absorption capacity. The main idea is to improve the structural performance of ferrocement panels that may be utilized in lightweight, low-cost house construction and sustainable construction. The ultimate flexure strength of ferrocement panels employing PVC plastic wire mesh, welded iron mesh, SBR latex, and PP fibers is the subject of the research. Test variables are the type of mesh layer, the dosage of PP fiber, and SBR latex. Experimental tests are conducted on 16 simply supported panels of size 1000 × 450 mm and subjected to four-point bending test. Results indicate that the addition of latex and PP fibers only controls the initial stiffness and does not have any significant effect on ultimate load. Due to the increased bonding between cement paste and fine aggregates, the addition of SBR latex improves the flexural strength by 12.59% and 11.01% for iron mesh (SI) and PVC plastic mesh (SP), respectively. The results also indicate an improvement in the flexure toughness of specimens with PVC mesh as compared to specimens with iron welded mesh; however, a smaller peak load is observed (i.e., 12.21% for control specimens) compared with the specimen with welded iron mesh. The failure patterns of the specimens with PVC plastic mesh exhibit a smeared cracking pattern that shows that they are more ductile compared to samples with iron mesh.

Impact Resistance of Styrene-Butadiene Rubber (SBR) Latex-Modified Fiber-Reinforced Concrete: The Role of Aggregate Size.

Improvements in tensile strength and impact resistance of concrete are among the most researched issues in the construction industry. The present study aims to improve the properties of concrete against impact loadings. For this purpose, energy-absorbing materials are used along with fibers that help in controlling the crack opening. A polymer-based energy-absorbing admixture, SBR latex, along with polypropylene fibers are used in this study to improve the impact resistance. Along with fibers and polymers, the effect of the size of aggregates was also investigated. In total, 12 mixes were prepared and tested against the drop weight test and the Charpy impact test. Other than this, mechanical characterization was also carried out for all the 12 concrete mixes. Three dosages of SBR latex, i.e., 0%, 4%, and 8% by weight of cement, were used along with three aggregates sizes, 19 mm down, 10 mm down, and 4.75 mm down. The quantity of polypropylene fibers was kept equal to 0.5% in all mixes. In addition to these, three control samples were also prepared for comparison. The mix design was performed to achieve a normal-strength concrete. For this purpose, a concrete mix of 1:1.5:3 was used with a water to a cement ratio of 0.4 to achieve a normal-strength concrete. The experimental study concluded that the addition of SBR latex improves the impact resistance of concrete. Furthermore, an increase in impact resistance was also observed for a larger aggregate size. The use of fibers and SBR latex is encouraged due to their positive results and the fact that they provide an economical solution for catering to impact strains. The study concludes that 4% SBR latex and 0.5% fibers with a larger aggregate size improve the resistance against impact loads.

Scientometric Analysis and Research Mapping Knowledge of Coconut Fibers in Concrete.

Biodegradable materials are appropriate for the environment and are gaining immense attention worldwide. The mechanical properties (such as elongation at break, density, and failure strain) of some natural fibers (such as Coir, Hemp, Jute, Ramie, and Sisal) are comparable with those of some synthetic fibers (such as E glass, aramid, or Kevlar). However, the toughness of coconut fibers is comparatively more than other natural fibers. Numerous studies suggest coconut fibers perform better to improve the concrete mechanical properties. However, the knowledge is dispersed, making it difficult for anyone to evaluate the compatibility of coconut fibers in concrete. This study aims to perform a scientometric review of coconut fiber applications in cementitious concrete to discover the various aspects of the literature. The typical conventional review studies are somehow limited in terms of their capacity for linking different literature elements entirely and precisely. Science mapping, co-occurrence, and co-citation are among a few primary challenging points in research at advanced levels. The highly innovative authors/researchers famous for citations, the sources having the highest number of articles, domains that are actively involved, and co-occurrences of keywords in the research on coconut-fiber-reinforced cementitious concrete are explored during the analysis. The bibliometric database with 235 published research studies, which are taken from the Scopus dataset, are analyzed using the VOSviewer application. This research will assist researchers in the development of joint ventures in addition to sharing novel approaches and ideas with the help of a statistical and graphical description of researchers and countries/regions that are contributing. In addition, the applicability of coconut fiber in concrete is explored for mechanical properties considering the literature, and this will benefit new researchers for its use in concrete.

Coupled Effect of Polypropylene Fibers and Slag on the Impact Resistance and Mechanical Properties of Concrete.

The disposal of steel slag leads to the occupation of large land areas, along with many environmental consequences, due to the release of poisonous substances into the water and soil. The use of steel slag in concrete as a sand-replacement material can assist in reducing its impacts on the environment and can be an alternative source of fine aggregates. This is the very first paper that seeks to experimentally investigate the cumulative effect of steel slag and polypropylene fibers, particularly on the impact resistance of concrete. Various concrete mixes were devised by substituting natural sand with steel slag at volumetric replacement ratios of 0%, 10%, 20%, 30%, and 40%, with and without fibers. Polypropylene fibers of 12 mm length were introduced into the steel slag concrete at 0%, 0.5%, and 1.0% by weight of cement as a reinforcing material. Performance evaluation of each mix through extensive experimental testing indicated that the use of steel slag as partial substitution of natural sand, up to a certain optimum replacement level of 30%, considerably improved the compressive strength, flexural strength, and tensile strength of the concrete by 20.4%, 23.8%, and 17.0%, respectively. Furthermore, the addition of polypropylene fibers to the steel slag concrete played a beneficial role in the improvement of strength characteristics, particularly the flexural strength and final drop weight impact energy, which had a maximum rise of 48.1% and 164%, correspondingly. Moreover, integral structure and analytical analyses have also been performed in this study to validate the experimental findings. The results obtained encourage the use of fiber-reinforced steel slag concrete (FRSLC) as a potential impact-resistant material considering the environmental advantages, with the suggested substitution, of an addition ratio of 30% and 1.0% for steel slag and polypropylene fibers, respectively.

Predicting Compressive and Splitting Tensile Strengths of Silica Fume Concrete Using M5P Model Tree Algorithm.

Compressive strength (CS) and splitting tensile strength (STS) are paramount parameters in the design of reinforced concrete structures and are required by pertinent standard provisions. Robust prediction models for these properties can save time and cost by reducing the number of laboratory trial batches and experiments needed to generate suitable design data. Silica fume (SF) is often used in concrete owing to its substantial enhancements of the engineering properties of concrete and its environmental benefits. In the present study, the M5P model tree algorithm was used to develop models for the prediction of the CS and STS of concrete incorporating SF. Accordingly, large databases comprising 796 data points for CS and 156 data records for STS were compiled from peer-reviewed published literature. The predictions of the M5P models were compared with linear regression analysis and gene expression programming. Different statistical metrics, including the coefficient of determination, correlation coefficient, root mean squared error, mean absolute error, relative squared error, and discrepancy ratio, were deployed to appraise the performance of the developed models. Moreover, parametric analysis was carried out to investigate the influence of different input parameters, such as the SF content, water-to-binder ratio, and age of the specimen, on the CS and STS. The trained models offer a rapid and accurate tool that can assist the designer in the effective proportioning of silica fume concrete.

Application of Machine Learning Techniques for Predicting Compressive, Splitting Tensile, and Flexural Strengths of Concrete with Metakaolin.

The mechanical properties of concrete are the important parameters in a design code. The amount of laboratory trial batches and experiments required to produce useful design data can be decreased by using robust prediction models for the mechanical properties of concrete, which can save time and money. Portland cement is frequently substituted with metakaolin (MK) because of its technical and environmental advantages. In this study, three mechanical properties of concrete with MK, i.e., compressive strength (f'c), splitting tensile strength (fst), and flexural strength (FS) were modelled by using four machine learning (ML) techniques: gene expression programming (GEP), artificial neural network (ANN), M5P model tree algorithm, and random forest (RF). For this purpose, a comprehensive database containing detail of concrete mixture proportions and values of f'c, fst, and FS at different ages was gathered from peer-reviewed published documents. Various statistical metrics were used to compare the predictive and generalization capability of the ML techniques. The comparative study of ML techniques revealed that RF has better predictive and generalization capability as compared with GEP, ANN, and M5P model tree algorithm. Moreover, the sensitivity and parametric analysis (PA) was carried out. The PA showed that the most suitable proportions of MK as partial cement replacement were 10% for FS and 15% for both f'c and fst.