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<p>Dynamic crack branching in quasi-brittle materials, such as concrete, remains a complex numerical task due to its sensitivity to various modeling parameters. This study utilizes the Phase field Method (PFM), implemented through a User Element (UEL) in Abaqus, to investigate the influence of operational parameters on fracture predictions. While PFM and UEL are established techniques, their application in dynamic regimes requires a careful selection of spatial and temporal scales to ensure consistent results. Through a series of numerical tests, this study identifies a stable operating window that maintains physical and numerical consistency in the captured fracture topologies. Additionally, a simplified scaling approach for the energy release rate is discussed to address mixed-mode scenarios. The findings establish a reliable simulation protocol for high-throughput fracture analysis, providing a foundation for future AI-enhanced structural mechanics.</p>

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Dynamic fracture and branching in concrete: a robust phase field finite element analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月1日

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  • Thi Thuy Anh Vu,
  • Chi Hieu Ha,
  • Dang Huy Phan,
  • Phuong Tran

摘要

Dynamic crack branching in quasi-brittle materials, such as concrete, remains a complex numerical task due to its sensitivity to various modeling parameters. This study utilizes the Phase field Method (PFM), implemented through a User Element (UEL) in Abaqus, to investigate the influence of operational parameters on fracture predictions. While PFM and UEL are established techniques, their application in dynamic regimes requires a careful selection of spatial and temporal scales to ensure consistent results. Through a series of numerical tests, this study identifies a stable operating window that maintains physical and numerical consistency in the captured fracture topologies. Additionally, a simplified scaling approach for the energy release rate is discussed to address mixed-mode scenarios. The findings establish a reliable simulation protocol for high-throughput fracture analysis, providing a foundation for future AI-enhanced structural mechanics.