Empirical modeling of fresh and hardened properties of self-compacting concretes by genetic programming

This article introduces genetic programming (GP) as a new tool for the formulations of fresh and hardened properties of self-compacting concretes (SCC). There are no well known explicit formulations for predicting fresh and hardened properties of SCCs. Therefore, the objective of the paper presented herein is to develop robust formulations based on the experimental data and to verify the use of GP for generating the formulations for slump flow diameter, V-funnel flow time, compressive strength, ultrasonic pulse velocity and electrical resistivity of SCCs. To generate a database for the training and testing sets, a total of 44 SCC mixtures with and without mineral admixtures were cast at 0.32 and 0.44 water/binder ratios. The mineral admixtures used were fly ash, silica fume and granulated blast furnace slag. Of all 44 concrete mixtures, the training and testing sets consisted of randomly selected 28 and 16 mixtures, respectively. The paper showed that the GP based formulation appeared to well agree with the experimental data and found to be quite reliable, especially for hardened concrete properties.