Abstract:
In recent years, structural lightweight concrete has gained momentum in its use due to its superior properties in terms of dead load reduction, better thermal comfort, improved fire resistance, etc. The use of lightweight aggregates manufactured from industrial bi-products such as flyash presents an alternative to ever-depleting natural aggregates and has been the solution to environmental challenges and a circular economy. With the increase in the use of sintered flyash lightweight aggregate-based concrete (LC-SFA), there is a need to evaluate the applicability of existing empirical equations and models available to predict the on-site strength of concrete using the pull-out method. The pull-out technique for on-site strength estimation has been well researched for normal concrete (NC), but very limited studies have been reported for structural lightweight concrete. This study aimed to develop a model for the determination of on-site compressive strength from 20 to 50 MPa for lightweight concrete (LC) with sintered flyash lightweight aggregate with a high degree of predictability and accuracy using the non-destructive pull-out test, and compare the results with normal weight concrete. The pull-out method adopted in the study has demonstrated that the in-place compressive strength of concrete can be predicted with high accuracy and better repeatability of LC-SFA. The percentage variation in compressive strength predicted by different models varies from −2% to 80%. The proposed model for normal concrete and the model developed by Jensen and ACI for normal concrete gave values somewhat near to the experimental results of LC, however, the variation was more than 15% in the case of ACI, and in the case of Jensen, the values were on the lower side. The study revealed that existing empirical equations available for normal weight concrete to predict the compressive strength on the basis of pull-out force will not be applicable to lightweight concrete, and proposed a model based on a study conducted gives high accuracy and repeatability.