The paper intends to analyze and study the features of steel fiber reinforced concrete (SFRC) and plain concrete that contains combined fibers of various aspect ratios. Experiments on works are held to examine the features of the new combination of concretes. Simultaneously, the characteristics of the concretes that are hardened are examined by performing tests on compressions, flexural strength tests, and split tensile strength (STS). It further verifies the effects of fibers when they are distributed in the hinged zone of structural components to obtain financial benefits by minimizing the ingredients in steel fiber in the concrete mix. The result shows that the combined reinforced concrete steel fiber can be employed as the better combination to be applied in SFRC for achieving strength in STS, and flexure. Anyhow, enhanced ability for working was achieved as more amounts of microfibers in mixed with concrete. And there is slight variation in the features of concrete between beam of fibers with full length and fibers which are available in hinged zone. Similarly, the categorization of neural network such as Neural Network–Levenberg–Marquardt (NN‐LM) and Neural Network‐Gradient Descent (NN‐GD) is further used to perform the experimentation in an intelligent manner, which comes close to the actual values while calculating the mean absolute error (MAE) and root mean square error (RMSE) values.
Bending tests were conducted on ferrocement laminates containing chicken mesh and steel slag. The fundamental goal of the examination was to investigate the effects of partial substitution of fine aggregate by steel slag in cement mortar combining chicken mesh of different volume fractions as reinforcement in thin ferrocement laminates. The following variables were investigated: (a) volume fraction of chicken mesh as 0.94%, 1.88%, 2.82%, and 3.77% and (b) level of steel slag substitution from 0% to 50% by weight fine aggregate. Results show that ferrocement laminates with chicken mesh of volume fractions of 3.77% and 30% substitution of fine aggregate with steel slag display better performance in terms of load deflection behaviour, first crack load, ultimate load, energy absorption, and ductility ratio when related with other specimens. An analytical model has been proposed to predict the ultimate moment carrying capacity of ferrocement laminates under flexure to validate the experimental results.
The focus of this study is to forecast the 28-day compressive strength and split tensile strength of concrete with various percentages of jute and coconut fibres mixed with quarry dust. The response surface methodology (RSM) and the artificial neural networks (ANN) methods were adopted for 3 variable process modelling (coconut fibres of 0% to 2.5%, jute fibres of 0% to 2.5%, and quarry dust of 0% to 25% by weight of cement). The RSM Box−Behnken design (BBD) method was adopted to design the experiments. Test results showed that compressive strength of 34.6 N/mm2 was obtained for concrete with 0% jute, 0% coir, and 12.5% quarry dust. Similarly, the maximum split tensile strength of 3.8 N/mm2 was obtained for concrete with 1.25% jute fibres, 1.25% coconut fibres, and 12.5% quarry dust. ANOVA and Pareto charts were used to assess regression models for response data. Each progression variable’s statistical significance was assessed, and the resulting models were expressed as second-order polynomial equations. Levenberg−Marquardt (LM) algorithm with feed-forward back propagation neural network was used for assessing the compressive strength and split tensile strength of concrete. The statistical data, root mean square error (RMSE), mean absolute error (MAE), mean absolute and percentage error (MAPE), and determination coefficient (R2) show that both techniques, ANN and RSM, are effective tools for predicting compressive strength and split tensile strength. Furthermore, RSM and ANN models have a high correlation with experimental data. However, the response surface methodology model is more accurate.
Nylon fibers are used as strengthening material to increase the mechanical properties of concrete.In thisstudy mechanical properties of concrete containing latex modified nylon fiber reinforced concrete wasassessed with fractional substitution of cement by flyash for M40 grade concrete at 7 days, 14 days and 28days of curing. The dosage of fibres used in this study was 0.05%, 0.1% and 0.15% of volume fraction.Cement was replaced with fly ash at a percentage of 10%, 15%, 20% by weight. SBR latex was varied at arate of 0.05%, 0.1%, 0.15% to the total cementitious content in concrete. Cube, cylinder and prism specimensare tested to determine the compressive, split tensile and flexural strength at 7 days and 28 days curing.Results shows that Nylon fiber reinforced concrete with 0.15% of fiber, 0.05% SBR Latex with 10% hashigher influence on flexural strength, split tensile strength and compressive strength of concrete.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.