Forecasting residual mechanical properties of hybrid fibre-reinforced self-compacting concrete (HFR-SCC) exposed to elevated temperatures

Abstract

The use of hybrid fibre-reinforced Self-compacting concrete (HFR-SCC) has escalated recently due to its significant advantages in contrast to normal concrete such as increased ductility, crack resistance, and eliminating the need for compaction etc. The process of determining residual strength properties of HFR-SCC after a fire event requires rigorous experimental work and extensive resources. Thus, this study presents a novel approach to develop equations for reliable prediction of compressive strength (cs) and flexural strength (fs) of HFR-SCC using gene expression programming (GEP) algorithm. The models were developed using data obtained from internationally published literature having eight inputs including water-cement ratio, temperature, fibre content etc. and two output parameters i.e., cs and fs. Also, different statistical error metrices like mean absolute error (MAE), coefficient of determination (R2) and objective function (OF) etc. were employed to assess the accuracy of developed equations. The error evaluation and external validation both approved the suitability of developed models to predict residual strengths. Also, sensitivity analysis was performed on the equations which revealed that temperature, water-cement ratio, and superplasticizer are some of the main contributors to predict residual compressive and flexural strength.