Akademik Veri Yönetim Sistemi
Sustainable Construction Materials and Technologies, cilt.7, sa.2, ss.108-118, 2022 (ESCI)
The aim of the study is to optimize the aggregate gradation curve (AGC)
for recycled aggregate concrete (RAC). Accordingly, TS 802 aggregate
gradation curves such as A16, B16 and C16 and, also two proposed AGCs
such as G1 and G2 are examined in the experiments. Hence, in total, 10
mixes are designed in consideration of A16, B16, C16, G1 and G2. The
physical (density and water absorption) and the mechanical (compressive
strength) properties are determined conducting the standard tests at the
age of 28th days after a standard 22±2oC water curing. Also, a
criterion weighting method such as Entropy Method is used in the
evaluation of the properties of concretes and the weights of the
properties of concretes are determined. Then, TOPSIS is used to find the
best concrete in consideration of the design parameters and test
results for the selection of the optimum AGC. As a result, the influence
of AGC on the properties of natural aggregate concretes (NACs) and RACs
are unsimilar and while A16 results in a denser NAC with higher
compressive strength, C16 can be offered to decrease the open pore
content of RAC in terms of water absorption leading a durable concrete
with a higher compressive strength. Besides, the results of Entropy
Method present interesting findings, and the coarse aggregate ratio in
the mix is found as the most effective parameters among the investigated
design parameters. However, the best AGCs are found as A16 for NAC and
G2 for RAC according to TOPSIS results. It is concluded that further
investigations are required.