Study of the prediction of the mechanical strength of concrete based on the fractal model of granular distribution

Studies revealed that the grain size of concretes have a quasi-perfect fractal distribution of the total grain size. This enabled to identify the basic granular mixture and determine the porosity, based on the granular fractalidentification modulus "GFIM", comprising the fractal dimension FD of the aggregate involved and the granular range D/d. The aim of this research work to shed new light on the prediction of concrete mechanical compressive strength and introduce a new approach the FD.log.(D/d) modulus. The approach adopted a twophase concrete model, the first phase being the aggregate and the second phase referring the paste in powder (cement, water, mineral addition and possibly fines). Applying a reading array to experimental compiled results of more than 300 concretes selected from literature provided a clear correlation between the development of concrete compressive strength RC28. The approach thus a new and more instructive and controlling concretes performance on fractal basis.