Effect of titanium dioxide as nanomaterials on mechanical and durability properties of rubberised concrete by applying RSM modelling and optimizations

Abstract

The use of rubber aggregates derived from discarded rubber tyres in concrete is a pioneering approach to replacing natural aggregate (NA) and promoting sustainable building practices. Recycled aggregate in concrete serves the dual purpose of alleviating the accumulation of discarded rubber tyres on the planet and providing a more sustainable alternative to decreasing natural aggregate. Due to fact that the crumb rubber (CR) decreases the strength when used in concrete, incorporating titanium dioxide (TiO2) as a nanomaterial to counteract the decrease in strength of crumb rubber concrete is a potential solution. Response Surface Methodology was developed to generate sixteen RUNs which contains different mix design by providing two input parameters like TiO2 at 1%, 1.5%, and 2% by cement weight and CR at 10%, 20%, and 30% as substitutions for volume of sand. These mixtures underwent testing for 28 days to evaluate their mechanical, deformation, and durability properties. Moreover, the compressive strength, tensile strength, flexural strength and elastic modulus were recorded by 51.40 MPa, 4.47 MPa, 5.91 MPa, and 40.15 GPa when 1.5% TiO2 and 10% CR were added in rubberised concrete after 28 days respectively. Furthermore, the incorporation of TiO2 led to reduced drying shrinkage and sorptivity in rubberized concrete, especially with increased TiO2 content. The study highlights that TiO2 inclusion refines pore size and densifies the interface between cement matrix and aggregate in hardened rubberized concrete. This transformative effect results in rubberized concrete demonstrating a commendable compressive strength comparable to normal concrete.

Effect of seawater salinity, pH, and temperature on external corrosion behavior and microhardness of offshore oil and gas pipeline: RSM modelling and optimization

“…These pictures show a significant connection between real and predicted values, showing a good degree of alignment. Notably, both models exhibit smooth continuity in their variance with no unexpected deviations 47 . The fact that actual data points are close to projected ones demonstrates a great agreement, demonstrating that the quadratic model for corrosion rate response and the linear model for microhardness response are effective in predicting results based on distinct variables 48 .…”