Engineering and Applied Science Research (Mar 2023)
A swarm intelligence shrinkage optimization of fly ash and tile aggregate based self-compacting concrete exposed to high temperatures
Abstract
Almost all the building structure is built with the basis ofSelf-compacting concrete (SCC). Hence, it has increased the researcher's interest in enriching the mechanical properties by optimizing the shrinkage. At the elevated temperature, the cause of shrinkage measure was very high. To overcome this issue, a novel intelligent African Buffalo-based Shrinkage Diminution (ABbSD) has been developed mathematically to optimize the shrinkage strain on concretes. In addition, the SCC-M40 and SCC-M50 were the grades selected for this research. Also, broken tile aggregates and fly ash were partially replaced at 0%, 10%, 20%, 30% and 40% and 0%, 10%, 20% and 30% by coarse aggregate mass and cement, respectively. Moreover, the hardened concrete properties were measured to determine the optimum mix of the concrete specimen. Also, to determine the optimum specimen's strength at elevated temperatures, concrete specimens were heated at 100 to 250 degree Celsius for 2hrs and 4hrs. Henceforth, the performance parameters like compressivestrength, split tensile, shrinkage, and flexural strength were measured. Then the shrinkage parameter values are then given as the optimization algorithm's input. Moreover, the African buffalo fitness function is activated to tune the performance parameters to the desired level. Consequently, the comparison was performed to determine the prepared optimum concrete specimen's effectiveness. The result demonstrated that the developed specimen has higher strength than other SCC specimens. Hence, the recorded shrinkage reduction rate by the proposed model is 38 to 40%. In addition, the compressive strength of M-4 and P-3 at 28 days is 43.37 N/mm2 and 50.97N/mm2,and the recorded compressive Strength for M-4and P-3 at 90 days is 50.38N/mm2and 60.69N/mm2respectivelywhich is quite high compared to other models. It is considered as the advantage of the proposed model over other studies.
