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October 13, 2025Structural Concrete0 citations

Deep learning‐assisted DEM simulation for optimizing concrete mix proportions

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JZJichen ZhongDWDong WangJZJunxing Zheng

Key Points

  • The study shows that increasing aggregate volume fraction generally enhances compressive strength in concrete.
  • Under quasi-static loading, models with real aggregate geometries demonstrated reliable mechanical performance with an optimal loading rate of 0.08 m/s.
  • Two numerical models were created: one with real aggregates and another with circular aggregates for performance comparison.
  • Optimizing concrete mix proportions based on real aggregate distributions can lead to high-strength and durable structures.

Abstract

Abstract This study utilized the DECAS‐Net model to precisely segment concrete images containing complex aggregate distributions (mIoU = 85.90%), enabling the construction of a comprehensive database of realistic aggregate geometries. Based on this database, two types of numerical models were developed: concrete models incorporating real aggregates with varying volume fractions and corresponding PFC2D models using circular aggregates for comparative analysis. The systematic investigation was conducted to examine the influence of loading rate, aggregate volume fraction, and aggregate shape on both the macroscopic and microscopic mechanical responses of the concrete. The results demonstrated that, under quasi‐static loading conditions, the model incorporating real aggregate geometries combined with the Bonded Particle Model (BPM) yielded reliable performance, with an optimal loading rate threshold identified at 0.08 m/s. Furthermore, it was observed that appropriately increasing the aggregate volume fraction generally enhances mechanical properties, with the optimal range identified between 5% and 10%, where the concrete exhibits peak compressive strength and Young's modulus. These findings directly inform the optimization of concrete mix proportions in engineering design, enabling the development of high‐strength, durable structures with tailored aggregate distributions.

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Cite This Study

Zhong et al. (2025) studied this question.

synapsesocial.com/papers/68ecc715d1cc7436f7d18adehttps://doi.org/10.1002/suco.70355
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