# Concrete Mesostructure Modeling via Random Radius Field and Rigid Body Dynamics Packing

**Authors:** Zhanbiao Zhang, Hui Wu, Mingzhuan Wei, Xiaogang Zhang, Yin Zhou, Xingyi Hu

PMC · DOI: 10.3390/ma19061099 · 2026-03-12

## TL;DR

This paper introduces a new method for modeling concrete mesostructures using stochastic geometry and physics-based packing to simulate realistic aggregate arrangements and crack propagation.

## Contribution

A novel framework combining random radius fields and rigid body dynamics for efficient and realistic concrete mesostructure modeling.

## Key findings

- The RRF method generates 3D aggregates with controllable and realistic morphologies.
- RBD-based packing simulates physical casting processes to achieve high-density aggregate skeletons.
- The framework successfully reproduces crack propagation and damage evolution in recycled aggregate concrete.

## Abstract

This paper proposes a novel and efficient mesostructure generation framework integrating stochastic geometry with physically based packing. First, a random radius field (RRF) method is developed, utilizing multi-scale noise superposition and topology optimization to generate 3D aggregates with realistic and controllable morphologies. Second, a packing strategy based on Rigid Body Dynamics (RBD) is developed to simulate the physical casting process including gravity falling and vibration, achieving high-density aggregate skeletons. The framework is validated through the generation of a multi-phase mesostructure and the fracture simulation of recycled aggregate concrete (RAC). The simulation results successfully reproduced the crack propagation patterns and damage evolution paths associated with different aggregate shapes. These findings confirm the capacity and effectiveness of the proposed framework as a robust tool for the mesoscopic modeling of heterogeneous concrete materials.

## Full-text entities

- **Chemicals:** aggregate concrete (-)

## Figures

11 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13027559/full.md

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Source: https://tomesphere.com/paper/PMC13027559