Use of numerical method for optimization of granulometric curves in eco-efficient concrete

Abstract

Concrete is the most used construction material and thus, being the cement a significant part of this material, it is also widely used around the world. Cement production is responsible for more than 5% of global CO2 emissions, which has been continuously increasing. A solution to reduce the cement content in concretes without loss of performance is thorough the particle packing optimization. This work uses practical numeri-cal simulations through linear programming and the modified Andreasen & Andersen model to reduce the void content of aggregate mixtures and produce concretes with superior and intermediate packing levels. A broad range of distribution modulus “q” values were tested. Deviations between the particle size distribution (PSD) curves were calculated in each step of the process. In this study, mixtures with the smallest deviations – experimental PSD curves closer to the mathematical packing model – did not present the lowest void con-tents. The distribution modulus “q” directly affects the fine aggregate content in the mixtures: Lower q values favors higher fine aggregate contents. For concrete granular skeletons composed by sand and gravel, there is a q value below which sand is the top deviation contributor and above which gravel is the top deviation con-tributor. Moreover, there is a limit to the distribution modulus after which the void content of aggregate skel-etons tends to increase. In this study, that was 0.30. Concretes with superior packing (S concrete) and with the lowest distribution factor (q = 0.25) showed better performance in relation to the other studied concretes, with a higher compressive strength at 91 days and with a binder intensity around 6 at 28 days and below 5 at 91 days.