Modified pervious concrete containing biomass aggregate: Sustainability and environmental benefits - M. Mhaya, Akram; Shahidan, Shahiron; Mohd Zuki, Sharifah Salwa; Hakim, S.J.S.; Wan Ibrahim, Mohd Haziman; Mohammad Azmi, Mohamad Azim; Huseien, Ghasan Fahim H (elsevier, 2025)
Pervious concrete (PC) can be called porous concrete or no fine concrete that has a high rate of permeability and low compressive strength. In general, compressive strength is inversely related to the void ratio. In this research, PC incorporating biomass as a coarse aggregate replacement (0 %–10 %) was assessed utilizing compressive strength tests in a systematic way. Here, response surface methodology (RSM) was utilized in designing the experimental works. This study focused on the effect with respect to biomass aggregate (BA) on the compressive strength and the void ratio of PC. Three groups of mixtures with 0 %, 5 % and 10 % of BA were experimented with. The first group was a control mix without additives. The second group contained gellan gum (GG) and silica fume (SF) as additives. The third group comprised rice husk ash (RHA), fly ash (FA) and SF as blended cement. Compressive strength, permeability, void ratio as well as water absorption tests were conducted. The test results showed that BA, as a partial replacement of natural aggregate, tends to reduce the compressive strength of PC. Specimens with blended cement containing 5 % of BA achieved 12.10 MPa, which is 46.7 % higher than the control mix, which achieved 6.45 MPa, after 28 days of curing. Note that the compressive strength of the specimens modified with pozzolanic materials (FA, SF, and RHA) and containing 10 % of BA was 42.5 % higher than the control mix. In contrast, specimens with GG and SF achieved almost the same compressive strength compared with the control mix. This is expected to reignite the interest in PC containing BA for sustainable construction. However, it was also deduced that the outcomes of both the mathematical and experimental models of RSM were accurate and consistent. Strong correlation and minimum error were indicated by the correlation statistical indicators (R2 ), which were higher than 0.98, and the error was less than 0.2.