Computational Study of Optimal Aggregate Ratio in the Mix Design of Various Concrete Types

The construction industry is increasingly prioritizing the enhancement of concrete materials to meet environmental goals and promote sustainability by optimizing aggregate proportion. The improvement of aggregate proportion reduces cement usage and enhances the physical, mechanical, and durability properties of concrete. This research simulated aggregate proportion to determine the optimal packing density, aiming to improve the performance of concrete. Specifically, LIGGGHTS software was used to model various aggregate proportions and identify the mixture with the highest packing density. The simulation results, which showed the variance of the experimental data, were validated against the results from the modified Andreasen and Andersen model and the experimental data. The study indicates that the optimal packing density and stress distribution between particles provides a robust framework for predicting material performance. Using these results, it is possible to identify the optimal state of aggregate composition or the optimal packing density by analyzing the gradation and specific ratios of aggregate composition, and significantly increase the accuracy of mix design and resource management. It also saves time and money. The findings from this research will help researchers facilitate the selection of optimal aggregate mixes efficiently, thereby saving both time and resources.