Annual Book Of Astm Standards

Confinement of high-strength concrete (HSC) columns with fiber reinforced polymer (FRP) composites has been receiving increasing research attention due to the advantageous engineering properties offered by the composite system. The use of silica fume as a concrete additive is a widely accepted practice in producing HSC. However, the influence of the presence and amount of silica fume on the efficiency of FRP confinement is not clearly understood. This paper presents the results of an experimental study on the influence of silica fume on the compressive behavior of FRP-confined HSC. 30 FRP-confined and 30 unconfined concrete cylinders containing different amounts of silica fume were tested under axial compression in two phases. In the first phase of the study, specimens with a constant water–cementitious binder ratio were tested. The results of this phase indicate that for a given water–cementitious binder ratio, the compressive strength of unconfined concrete increases with an increase in the amount of silica fume. It is found that this increase in strength leads to an increased concrete brittleness, which adversely affects the effectiveness of FRP confinement. In the second phase, water–cementitious binder ratios of the specimens were adjusted to attain a constant unconfined concrete strength for specimens containing different amounts of silica fume. The results of these tests indicate that for a given unconfined concrete strength, strength enhancement ratios of FRP-confined HSC specimens are not influenced by the silica fume content of the concrete mix. On the other hand, it is found that the silica fume content influences the axial strain enhancement ratios of these specimens. In addition, the transition zones of the stress–strain curves of FRP-confined HSC are observed to be sensitive to the amount of silica fume used in the mix.

https://researchbank.swinburne.edu.au/file/880c7328-3959-4ad6-8ae1-f240cd40229a/1/PDF (Published version).pdf

Influence of silica fume on stress-strain behavior of FRP-confined HSC

A scientometric review of waste material utilization in concrete for sustainable construction

Industrial waste has been rapidly increased day by day because of the fast-growing population which results environmental pollutions. It has been recommended that the disposal of industrial waste would be greatly reduced if it could be incorporated in concrete production. In cement concrete technology, there are many possibilities to use waste materials either as cement replacement or aggregate in concrete production. Two major industrials waste are glass and marble waste. The basic objective of this investigation is to examine the characteristics of concrete waste glass (WG) as binding material in proportions 10%, 20% and 30% by weight of cement. Furthermore, to obtain high strength concrete, waste marble in proportion of 40%, 50% and 60% by weight cement as fine aggregate were used as a filler material to fill the voids between concrete ingredients. Fresh properties were evaluated through slump cone test while mechanical performance was evaluated through compressive strength and split tensile strength which were performed after 7 days, 28 days and 56 days curing. Results show that, workability of concrete decreased with incorporation of waste glass and marble waste. Furthermore, mechanical performance improved considerably up 20% and 50% substitution of waste glass and waste marble respectively. Statistical approach of Response Surface Methodology (RSM) was used optimize both waste materials in concrete. Results indicate better agreement between statistical and experimental results.

Effects of waste glass and waste marble on mechanical and durability performance of concrete.

For the efficient and durable design of concrete, the role of fiber-reinforcements with mineral admixtures needs to be properly investigated considering various factors such as contents of fibers and potential supplementary cementitious material. Interactive effects of fibers and mineral admixtures are also needed to be appropriately studied. In this paper, properties of concrete were investigated with individual and combined incorporation of steel fiber (SF) and micro-silica (MS). SF was used at six different levels i.e., low fiber volume (0.05% and 0.1%), medium fiber volume (0.25% and 0.5%) and high fiber volume (1% and 2%). Each volume fraction of SF was investigated with 0%, 5% and 10% MS as by volume of binder. All concrete mixtures were assessed based on the results of important mechanical and permeability tests. The results revealed that varying fiber dosage showed mixed effects on the compressive (compressive strength and elastic modulus) and permeability (water absorption and chloride ion penetration) properties of concrete. Generally, low to medium volume fractions of fibers were useful in advancing the compressive strength and elastic modulus of concrete, whereas high fiber fractions showed detrimental effects on compressive strength and permeability resistance. The addition of MS with SF is not only beneficial to boost the strength properties, but it also improves the interaction between fibers and binder matrix. MS minimizes the negative effects of high fiber doses on the properties of concrete.

Effect of Varying Steel Fiber Content on Strength and Permeability Characteristics of High Strength Concrete with Micro Silica.

Recently, the addition of natural fibers to high strength concrete (HSC) has been of great interest in the field of construction materials. Compared to artificial fibers, natural fibers are cheap and locally available. Among all natural fibers, coconut fibers have the greatest known toughness. In this work, the mechanical properties of coconut fiber reinforced high strength concrete (CFR-HSC) are explored. Silica fume (10% by mass) and super plasticizer (1% by mass) are also added to the CFR-HSC. The influence of 25 mm-, 50 mm-, and 75 mm-long coconut fibers and 0.5%, 1%, 1.5%, and 2% contents by mass is investigated. The microstructure of CFR-HSC is studied using scanning electron microscopy (SEM). The experimental results revealed that CFR-HSC has improved compressive, splitting-tensile, and flexural strengths, and energy absorption and toughness indices compared to HSC. The overall best results are obtained for the CFR-HSC having 50 mm long coconut fibers with 1.5% content by cement mass.

https://www.mdpi.com/1996-1944/13/5/1075/pdf

Effect of Coconut Fiber Length and Content on Properties of High Strength Concrete.

Marble is currently a commonly used material in the building industry, and environmental degradation is an inevitable consequence of its use. Marble waste occurs during the exploitation of deposits using shooting technologies. The obtained elements most mainly often have an irregular geometry and small dimensions, which excludes their use in the stone industry. There is no systematic way of disposing of these massive mounds of waste, which results in the occurrence of landfills and environmental pollution. To mitigate this problem, an effort was made to incorporate waste marble powder into clay bricks. Different percentage proportions of marble powder were considered as a partial substitute for clay, i.e., 5–30%. A total of 105 samples were prepared in order to assess the performance of the prepared marble clay bricks, i.e., their water absorption, bulk density, apparent porosity, salt resistance, and compressive strength. The obtained bricks were 1.3–19.9% lighter than conventional bricks. The bricks with the addition of 5–20% of marble powder had an adequate compressive strength with regards to the values required by international standards. Their compressive strength and bulk density decreased, while their water absorption capacity and porosity improved with an increased content of marble powder. The obtained empirical equations showed good agreement with the experimental results. The use of waste marble powder in the construction industry not only lowers project costs, but also reduces the likelihood of soil erosion and water contamination. This can be seen to be a crucial factor for economic growth in agricultural production.

An Experimental and Empirical Study on the Use of Waste Marble Powder in Construction Material.

Research has focused on creating new methodologies such as supervised machine learning algorithms that can easily calculate the mechanical properties of fiber-reinforced concrete. This research aims to forecast the flexural strength (FS) of steel fiber-reinforced concrete (SFRC) using computational approaches essential for quick and cost-effective analysis. For this purpose, the SFRC flexural data were collected from literature reviews to create a database. Three ensembled models, i.e., Gradient Boosting (GB), Random Forest (RF), and Extreme Gradient Boosting (XGB) of machine learning techniques, were considered to predict the 28-day flexural strength of steel fiber-reinforced concrete. The efficiency of each method was assessed using the coefficient of determination (R2), statistical evaluation, and k-fold cross-validation. A sensitivity approach was also used to analyze the impact of factors on predicting results. The analysis showed that the GB and RF models performed well, and the XGB approach was in the acceptable range. Gradient Boosting showed the highest precision with an R2 of 0.96, compared to Random Forest (RF) and Extreme Gradient Boosting (XGB), which had R2 values of 0.94 and 0.86, respectively. Moreover, statistical and k-fold cross-validation studies confirmed that Gradient Boosting was the best performer, followed by Random Forest (RF), based on reduced error levels. The Extreme Gradient Boosting model performance was satisfactory. These ensemble machine learning algorithms can benefit the construction sector by providing fast and better analysis of material properties, especially for fiber-reinforced concrete.

/pdf/flexural-strength-prediction-of-steel-fiber-reinforced-14ty79gz.pdf

Flexural Strength Prediction of Steel Fiber-Reinforced Concrete Using Artificial Intelligence

Recently, research has centered on developing new approaches, such as supervised machine learning techniques, that can compute the mechanical characteristics of materials without investing much effort, time, or money in experimentation. To predict the 28-day compressive strength of steel fiber–reinforced concrete (SFRC), machine learning techniques, i.e., individual and ensemble models, were considered. For this study, two ensemble approaches (SVR AdaBoost and SVR bagging) and one individual technique (support vector regression (SVR)) were used. Coefficient of determination (R2), statistical assessment, and k-fold cross validation were carried out to scrutinize the efficiency of each approach used. In addition, a sensitivity technique was used to assess the influence of parameters on the prediction results. It was discovered that all of the approaches used performed better in terms of forecasting the outcomes. The SVR AdaBoost method was the most precise, with R2 = 0.96, as opposed to SVR bagging and support vector regression, which had R2 values of 0.87 and 0.81, respectively. Furthermore, based on the lowered error values (MAE = 4.4 MPa, RMSE = 8 MPa), statistical and k-fold cross validation tests verified the optimum performance of SVR AdaBoost. The forecast performance of the SVR bagging models, on the other hand, was equally satisfactory. In order to predict the mechanical characteristics of other construction materials, these ensemble machine learning approaches can be applied.

/pdf/compressive-strength-of-steel-fiber-reinforced-concrete-1u5sb932.pdf

Compressive Strength of Steel Fiber-Reinforced Concrete Employing Supervised Machine Learning Techniques

Accumulating vast amounts of pollutants drives modern civilization toward sustainable development. Construction waste is one of the prominent issues impeding progress toward net-zero. Pollutants must be utilized in constructing civil engineering structures for a green ecosystem. On the other hand, large-scale production of industrial steel fibers (ISFs) causes significant damage to the goal of a sustainable environment. Recycled steel fibers (RSFs) from waste tires have been suggested to replace ISFs. This research critically examines RSF’s application in the mechanical properties’ improvement of concrete and mortar. A statistical analysis of dimensional parameters of RSFs, their properties, and their use in manufacturing various cement-based composites are given. Furthermore, comparative assessments are carried out among the improvements in compressive, split tensile, and flexural strengths of plain and RSF-incorporated concrete and mortar. In addition, the optimum contents of RSF for each strength property are also discussed. The influence of RSFs parameters on various strength properties of concrete and mortars is discussed. The possible applications of RSF for various civil engineering structures are reviewed. The limitations and errors noticed in previous review papers are also outlined. It is found that the maximum enhancement in compressive strength (CS), split tensile strength (STS), and flexure strength (FS) are 78%, 149%, and 157%, respectively, with the addition of RSF into concrete. RSF increased cement mortars’ CS, STS, and FS by 46%, 50.6%, and 69%, respectively. The current study encourages the building sector to use RSFs for sustainable concrete.

/pdf/a-comprehensive-review-of-incorporating-steel-fibers-of-16cj02gs.pdf

Muhammad Sufian

Papers

Effect of Coconut Fiber Length and Content on Properties of High Strength Concrete.

An Experimental and Empirical Study on the Use of Waste Marble Powder in Construction Material.

Flexural Strength Prediction of Steel Fiber-Reinforced Concrete Using Artificial Intelligence

Compressive Strength of Steel Fiber-Reinforced Concrete Employing Supervised Machine Learning Techniques

A Comprehensive Review of Incorporating Steel Fibers of Waste Tires in Cement Composites and Its Applications