Optimization of Fiber-Reinforced Concrete using Data Mining

This is the complete, public report of the research project carried out with the support of the ACI Foundation. A database of fiber-reinforced concrete (FRC) mixtures have been compiled from papers published over the last two decades and used for this study, providing the basis for the development of robust models to estimate the residual flexural strength. It has been demonstrated that the mix design variables representing the binder composition and the aggregates content and combined grading explain 49% of the differences in residual flexural strength parameters, as opposed to the 51% explained by the variables directly related to the fibers. This proves that the residual flexural capacity of FRC is heavily influenced by variables other than the fibers and supports the idea that proportioning FRC mixtures mainly by modifying the fiber content is not a good approach. The variability of the residual flexural strength parameters has also been studied, and equations have been obtained to estimate their standard deviation as a function of the mixture proportions, the fiber dimensions, and the test/specimen configuration (3PBT or 4PBT).