Stochastic Mesoscopic Modeling of Concrete Systems Containing Recycled Concrete Aggregates Using Monte Carlo Methods

Anuruddha Jayasuriya, Matthew J. Bandelt, Matthew P. Adams

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


This paper investigates the applicability of numerically generated recycled concrete aggregate (RCA) systems by varying the material properties. The methodology was adopted by using a computational algorithm that can generate concrete systems with different RCA replacement levels to numerically simulate recycled aggregate concrete (RAC) systems under mechanical loading. Numerically simulated results are compared with an experimental database that has been established, including a substantial data set on RAC mixture design proportions. RAC geometries and material properties were stochastically generated using Monte Carlo simulation methods, resulting in 200 representative numerical models that were subjected to simulated mechanical loading. The overall variability of the concrete properties was not well-predicted in the numerical models compared to the experimental database results due to modeling limitations and material heterogeneity exhibited in experiments. The variability of tensile strength was governed by the complex strain localization patterns in the interfacial transition zone (ITZ) phases in RAC systems that were simulated.

Original languageEnglish (US)
Pages (from-to)3-18
Number of pages16
JournalACI Materials Journal
Issue number2
StatePublished - Mar 2022

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Building and Construction
  • General Materials Science


  • Monte Carlo simulation
  • finite element modeling
  • numerical simulation
  • random aggregate structure
  • recycled concrete aggregate (RCA)
  • statistical database analysis


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