Experimental investigation and development of analytical model for pre-peak stress-strain curve of structural lightweight aggregate concrete

In lightweight aggregate concrete (LWAC), the weakest component of LWAC is not the cement matrix or the interfacial transition zone but the lightweight aggregate (LWA). So the mechanical performance of LWAC is not only controlled by the quality of cement matrix but also by the volume content and properties of aggregates. Also, for structural analysis and design of LWAC, a unified stress-strain curve that covers different types of LWA is necessary. In this research, the effect of volume fraction and aggregate properties on mechanical performance of LWAC was examined. Five types of LWA with different volume contents were used to experimentally determine the pre-peak stress-strain curves of LWAC under compression. It was found out that the peak stress and modulus of elasticity of LWAC decreased with the increase in the volume content of LWA. Higher particle density, in general, resulted in higher compressive strength and modulus of elasticity of LWAC. Except for concrete that was made with angular LWA (YC), increase in the crushing strength of LWA led to an increase in the compressive strength of LWAC. The higher value of shape index showed greater influence on the mechanical properties of LWAC. Based on the pre-peak portion of the stress-strain curve, it was found that the higher volume content of LWA in concrete mix resulted in a more brittle failure of LWAC. The brittleness of LWAC also increased with the increase in the shape index of LWA. The increase in the LWA crushing strength resulted in higher plasticity of the resulting LWAC. An analytical model for the pre-peak stress-strain curve of LWAC was proposed and validated by taking into account the effect of properties of LWA. The validation of model showed that the difference between the experimental and prediction results to be less than 1.5%. Thus, the precision of prediction model demonstrated the effectiveness of the method and the potential application of the model for LWAC.