Comprehensive Analysis of Stress-strain Relationships for Recycled Aggregate Concrete

Pawar, Akshay Jaikumar; Suryawanshi, Shiwanand

doi:10.5829/ije.2022.35.11b.05

Comprehensive Analysis of Stress-strain Relationships for Recycled Aggregate Concrete

Document Type : Original Article

Authors

¹ Department of Civil Engineering, Research Scholar, Sardar Vallabhbhai National Institute of Technology, Surat, India.

² Department of Civil Engineering, Associate Professor, S.V. National Institute of Technology, Surat 395007, India.

10.5829/ije.2022.35.11b.05

Abstract

There is a growing demand of suitable substitute materials of concrete ingredients especially fine and coarse aggregates in order to achieve sustainable development in the era of rapid urbanisation. Therefore, the concrete making process by utilisation of aggregates that recycled from construction and demolition (C&D) debris has emerged as a primary objective for many government agencies. Consequently, the utilisation of recycled aggregate concrete (RAC) in structural applications become essential aspect. However, RAC can be employed in structural applications only if effective stress-strain relationship is available. The stress-strain models developed for natural aggregate concrete (NAC) are not fully suitable for RAC. Hence, the selection of good model which has precise prediction capacity plays a crucial role. Moreover, the stress-strain models provide the basis for the analysis and modern design procedures especially in FEA packages. In the present study, the stress-strain models for RAC have been selected from the literature and critically reviewed in order to evaluate their predictive efficacy. The test samples in the form of measured stress-strain relationships derived from literature have been compared with the predictions of each selected model. Besides the comparison of measured and predicted stress-strain profiles, the output of selected models in terms of normalized toughness and ductility index was assessed. The consistency of output of models are further evaluated by employing statistical tools such as coefficient of variance and root mean square error. The outcomes of the model in the form of polynomial expression was relatively more accurate to that of other counterparts.

Keywords