Ningombam Reena Devi, Ph.D.  Sambit Kumar Beura, Prateek Kumar Dhir and Pradip Sarkar



This work experimentally evaluated compressive strength and splitting tensile strength of cellular lightweight concrete (CLC) under varying strain-rate conditions.

A novel artificial technique called multigene genetic programming (MGGP) was used in conjunction with the stepwise regression analysis to develop mathematical models that are efficient in predicting major strength parameters (compressive strength and tensile strength) of CLC under various displacement rates (0.1–10  mm/min.

In the observation, the MGGP-based models outperformed the regression-based models for predicting both splitting tensile and compressive strengths.

The outcome of this study demonstrates that displacement rate and density have considerable impacts on both compressive and splitting tensile strength of CLC. With an increase in displacement rate from 0.1 to 10  mm/min, the compressive strength and tensile strength of CLC are found to increase by 87% and 116%, respectively. The proposed models would help to predict the strength parameters analytically with significant accuracy where experimental tests are not feasible to perform.