Discrete Element Modeling and Numerical Simulation of Pervious Concrete Based on the Cement Coating Method

This study proposes an optimized mix design for pervious concrete and develops a discrete element method (DEM) model to analyze the microstructure of aggregates coated with cement paste. When the parameter k i is set to 1.3, the coating thickness (CT) reaches the optimal CT (OCT), which is 0.65 mm (for aggregates 4.75–9.5 mm), 0.91 mm (for aggregates 9.5–16 mm), and 1.17 mm (for aggregates 16–19 mm). The optimal aggregate mix ratio of 4.75–9.5 mm to 16–19 mm, which is 7:3, was determined using the simplex centroid method. The designed pervious concrete achieved a compressive strength of 26 MPa and a permeability coefficient of 1.68 mm/s, thereby meeting the pavement standards of ≥25 MPa and ≥0.5 mm/s, while simplifying the mix design process. A DEM model incorporating OCT was developed and compared with a non-coated model, demonstrating an increase in accuracy of 10.26%. The DEM model of pervious concrete with a cement coating effectively captured the stress-strain behavior, compressive strength, and permeability characteristics of pervious concrete, aligning well with experiment data and exhibiting a relative error of 8.32%, which is within 10%. Its accuracy exceeds that of the non-coated model by 10.26%, significantly enhancing the reliability of numerical simulations. This approach reduces dependence on extensive laboratory testing, thereby streamlining the mix design process while maintaining practical feasibility. This study provides a valuable numerical tool for optimizing the performance of pervious concrete in engineering applications.

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Publication Details

Journal
Transportation Research Record Journal of the Transportation Research Board
Published
2025-11-24
DOI
https://doi.org/10.1177/03611981251381765
Primary Topic
Urban Stormwater Management Solutions
Type
article
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article

Discrete Element Modeling and Numerical Simulation of Pervious Concrete Based on the Cement Coating Method

Jun Zhao, Qidan Xiao, Li Feng Cai, Yi Liu
Transportation Research Record Journal of the Transportation Research Board
Urban Stormwater Management Solutions
article

Discrete Element Modeling and Numerical Simulation of Pervious Concrete Based on the Cement Coating Method

Jun Zhao, Qidan Xiao, Li Feng Cai, Yi Liu
article en

Abstract

This study proposes an optimized mix design for pervious concrete and develops a discrete element method (DEM) model to analyze the microstructure of aggregates coated with cement paste. When the parameter k i is set to 1.3, the coating thickness (CT) reaches the optimal CT (OCT), which is 0.65 mm (for aggregates 4.75–9.5 mm), 0.91 mm (for aggregates 9.5–16 mm), and 1.17 mm (for aggregates 16–19 mm). The optimal aggregate mix ratio of 4.75–9.5 mm to 16–19 mm, which is 7:3, was determined using the simplex centroid method. The designed pervious concrete achieved a compressive strength of 26 MPa and a permeability coefficient of 1.68 mm/s, thereby meeting the pavement standards of ≥25 MPa and ≥0.5 mm/s, while simplifying the mix design process. A DEM model incorporating OCT was developed and compared with a non-coated model, demonstrating an increase in accuracy of 10.26%. The DEM model of pervious concrete with a cement coating effectively captured the stress-strain behavior, compressive strength, and permeability characteristics of pervious concrete, aligning well with experiment data and exhibiting a relative error of 8.32%, which is within 10%. Its accuracy exceeds that of the non-coated model by 10.26%, significantly enhancing the reliability of numerical simulations. This approach reduces dependence on extensive laboratory testing, thereby streamlining the mix design process while maintaining practical feasibility. This study provides a valuable numerical tool for optimizing the performance of pervious concrete in engineering applications.

Transportation Research Record Journal of the Transportation Research Board
Xinyang Normal University (CN), North China University of Water Resources and Electric Power (CN)
Openalex Percentile: Top 66%
Urban Stormwater Management Solutions
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