Evaluation of concrete bricks with crumb rubber and polypropylene fibres under impact loading

Abstract

The influence of Polypropylene (PP) fibres and crumb rubber (CR) on the concrete bricks under impact loading was studied through experimental as well as statistical analysis. A total number of 12 mixes were considered with different percentages of only PP fibres as phase 1, crumb rubber with fibres as phase 2 and only crumb rubber as phase 3, at 28 days. In phase 1 of Mixes 1–4, the PP fibres were added into control mix (CM) with varying percentage of volume fraction, i.e., 0.1%, 0.2%, 0.3%. The highest strength to weight ratio found for the mix 3 (0.3% PP fibres), however PP fibres at 0.2% were considered as best in terms of preparation of the mixes. In phase 2 of Mixes 5–8, the crumb rubber was replaced by 3, 6, 9, and 12% by volume of fine aggregates of size less than 4.5 mm along with 0.2% PP fibres. In phase 3 of Mixes 9–12, fine aggregates were replaced by crumb rubber by 3, 6, 9, and 12% without fibres to explicitly perceive the influence of fibres on crumb rubber concrete. The durability tests of the bricks such as Initial rate of water absorption (IRWA) and water absorption was performed all chosen mixes however, efflorescence and sulphate attack tests were carried out on mix 5–8. The mechanical strength of bricks under compression, tension and flexure was determined. Further, impact energy absorption characteristics studies/tests were carried on Mix 1 and Mix 5–12 using drop weight impact tests. It was observed that the addition of crumb rubber of 12% along with 0.2% of PP fibre (Mix 8) reduced the density by 9.41% compared to the control mix (Mix 1). It was also observed that the energy absorption capacity was found to increase with an increase of CR up to 6% along with 0.2% PP fibre, whereas increasing replacement level beyond 6% CR, the impact energy absorption capacity found decreased. It was concluded that the reliability life assessment of brick made using crumb rubber and fibre can be predicted using two-parameter Weibull distribution.