Title:
Application of Evolutionary Algorithms for Optimization of Dense Packing of Concrete Aggregates
Author(s):
Sobolev
Publication:
Web Session
Volume:
Issue:
Appears on pages(s):
Keywords:
DOI:
Date:
11/3/2024
Abstract:
Sequential Packing Algorithm - SPA was developed to model the dense packing of large assemblies of particulate materials such as aggregate systems used for portland cement or asphalt concrete. The SPA performance was further enhanced using the artificial intelligence (AI) approach. The AI optimization based on genetic algorithms (GA) uses natural selection and genetics to estimate the fractal dimensions and porosity of Apollonian packing of spherical particles. Multi-cell packing procedures, fine adjustment of the algorithm’s parameters, as well as implementation of GA were demonstrated to be effective tools to optimize the computational resources, to speed-up the SPA and to pack a large number of spherical objects and also be applicable to packing of other geometrical shapes such as ellipsoids and fibers. The developed algorithm can be used to describe and visualize dense packings corresponding to concrete aggregates. Based on the simulation results, different particle size distributions of particulate materials and packing efforts are correlated to corresponding packing degree. These virtual packings agree well with the standard requirements and available research data.