WIT Press


PREDICTING MODULUS OF ELASTICITY OF RECYCLED AGGREGATE CONCRETE USING NONLINEAR MATHEMATICAL MODELS



Price

Free (open access)

Paper DOI

10.2495/CMEM-V6-N4-703-715

Volume

Volume 6 (2018), Issue 4

Pages

12

Page Range

703 - 715

Author(s)

JUNIOR A. REYES-SÁNCHEZ, ANTONIO J. TENZA-ABRIL, FERRAN VERDU & JOSÉ A. REYES PERALES

Abstract

It is estimated that currently the consumption of natural aggregates used annually in the production of concrete in the world is around 10 billion tons. Moreover, more than 10 million tons of waste is generated annually from the construction industry. The incorporation of recycled aggregates in the production of concrete arises mainly due to an environmental factor, because it emphasizes the reduction in the consumption of raw materials, reduction of the emission of pollutants to the atmosphere derived from the processes of extraction of natural aggregates, between others. Several studies quantifies the decrease of mechanical properties according to the percentage of replacement of natural aggregate by recycled concrete aggregate. In the present study the authors provide several nonlinear models, which are able to predict the modulus of elasticity behaviour of the concrete manufactured with recycled aggregate. A database was composed of 147 different mixtures of recycled aggregate concrete collected from publications of scientific journals. The database has been used to introduce it to the software Polimodels. Polimodels is able to generate different models using different nonlinear regression algorithms. Six different models for the modulus of elasticity are proposed, dependents on certain physical and mechanical parameters of the recycled aggregate, as the following; the percentage of absorption, Los Angeles abrasion coefficient, and the percentage of substitution of natural aggregate by recycled aggregate. It is possible to appreciate the remarkable reduction in the modulus of elasticity due to the increase of recycled aggregates in the concrete. When the models have more independent variables a better adjustment is noticed that help us to improve the prediction of the modulus of elasticity of recycled aggregate concrete.

Keywords

elastic modulus, nonlinear models, prediction, recycled aggregates, recycled concrete