Stochastic point process applied in aggregates composition for concrete

Abstract

The objective of this work is to apply a stochastic point process technique in the evaluation of aggregate composition parameters for concrete. Several experimental, numeric and computational methods have been used for determining an ideal packing of aggregates for concrete, based on the principle of the lowest content of voids. Experimental method is quite hard-working. On the other hand, the mathematical and computational models need potent computer and be tested experimentally. Equipment and computational methods have been developed, to provide images of the particle distribution, approaching the actual distribution of aggregates and allowing to obtain ideal aggregates compositions. This work uses a stochastic point process, based on the point processes method, which a simple sequential inhibition (SSI) process on the arbitrary closed region places the particles. The SSI generates image of spherical particles distributions for viewing and checking compliance of parameters of aggregates compositions. The characteristics of aggregates (porosity, granulometry, proportion of each aggregate composition, and specific mass) and the problem's domain are input data. The SSI's output data of interest are virtual image of particles distribution, particles composition, porosity of each composition, diameter and number of particles. From SSI's output data, it can be determined the packing factor and a histogram of particles diameters. This information is evaluated and compared with the input composition. As a result, the stochastic SSI demonstrates to be efficient in comparing the output and experimental data, complying with the purpose of the study.