Share:


The study of the stability of asphalt concrete mixture composition optimization mathematical models using imitative simulation

Abstract

The method of statistical imitative simulation (Monte-Carlo) was used to simulate the heterogeneity of the produced asphalt concrete mixture (ACM) mineral part grading. The stability of optimisation of mathematical models of ACM composition developed by us was tested by a computer using tpe theory of this method application. Average values aij and their average standard deviations σ ij of seven (Aj = 7) finally hatched aggregate partial residues on control sieves i (= 9) were set for research. Imported filler A 1 and reclaimed dust A2 were replaced by their mixture Ā1 when the accepted ratio of these materials masses λ is 1, 2 and 3. The maximum (A max) and minimum (A min) values of ACM materials quantity optimal composition were calculated from numerical values of aggregate with different heterogeneity ((minimum – σ ijmin, medium – σ ijvid , maximum – σ ijmax) increasing the number of computer imitations N (100, 300, 500, 1000, 5000, 10 000). The graphs of the difference between the calculated maximum and minimum values of optimal quantity of aggregate dependence ΔAj on the imitation number N are presented. Calculation results proved the sufficient stability and practical application of the used optimization mathematical model to forecast ACM heterogeneity, when the heterogeneity and optimal quantity of the aggregate used in the mixture are known.


First Published Online: 19 Dec 2011

Keyword : asphalt concrete mixture, production technology, imitative simulation, model stability, Monte-Carlo method

How to Cite
Podviezko, V., & Sivilevičius, H. (2003). The study of the stability of asphalt concrete mixture composition optimization mathematical models using imitative simulation. Transport, 18(6), 259-266. https://doi.org/10.3846/16483840.2003.10414108
Published in Issue
Dec 31, 2003
Abstract Views
407
PDF Downloads
309
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.