Influence of coarse aggregate size and content on the properties of recycled aggregate concrete using non-destructive testing methods

Recycled concrete aggregates (RCA) are obtained by concrete recycling processes. When adopted with specially graded aggregate, long-established inexpensive and unobtrusive non-destructive techniques have the potential to revolutionize the construction sector. The combined influences of RCA size and content are commonly proprietary information or incompletely reported in avail-able literature by means of non-destructive tests (NDTs). Hence, this paper represents the experi-mental investigation of the recycled aggregate concrete (RAC) properties prepared with varying sizes and replacement levels of coarse aggregate using destructive and non-destructive testing techniques. In this work, several NDTs were performed on cylindrical samples of 100 mm dia. x 200 mm and compared to destructive testing (DT) to determine the properties of 5-12 mm and 12-20 mm coarse aggregate concrete mixes having 15%, 30%, and 45% replacement of natural coarse aggregate (NCA) by RCA. For this purpose, 0%, 15%, 30%, and 45% RAC contents were utilized with the corresponding replacement of NCA for 5-12 mm and 12-20 mm coarse aggre-gate to determine their effects on the slump, compressive strength, digital rebound hammer, ul-trasonic pulse velocity (UPV), electrical resistivity, water permeability, and modulus of elasticity (MOE) tests. It was revealed that RAC achieved lower compressive strength, rebound number, MOE, electrical resistivity, and UPV values with the increment of RCA replacement level at 7, 28, and 56 days, especially inferior values observed for 45% RCA replacement concrete mixes. On the other hand, the concrete with 5-12 mm aggregate size showed higher surface hardness, compres-sive strength, water permeability, UPV, and electrical resistance than the concrete with 12-20 mm aggregate size. Furthermore, several empirical relationships have been established be-tween DT and NDT on the concrete properties and compared with other research findings. There-fore, these relationships demonstrated that NDT could efficiently predict RAC properties by in-creasing the pace of testing as well as reducing the cost of determining those parameters.