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<p>In recent years, the shear strength of fiber-reinforced polymer (FRP) reinforced concrete (RC) beams has been increasingly well documented, as these beams are more susceptible to shear failure than conventional steel-RC beams. This study focuses on developing a rational mechanism-based model for predicting the shear capacity of FRP-RC deep beams without stirrups. A rotating angle-softened truss model (RA-STM) with an appropriate tension-stiffening relationship is employed as the base model. The predictive performance of the base RA-STM is validated against 177 experimental datasets gathered from existing literature. The analytical data derived from the base RA-STM are subsequently used to improve performance via a data-driven approach. Consequently, a failure mode classification index is developed to classify the failure mechanisms of deep FRP-reinforced beams without transverse reinforcement, and explicit functions for equilibrium and compatibility conditions are formulated. Two simplified versions of the base RA-STM (RA-STM_I and RA-STM_II) are established which provides better predictions than several other mechanical-based models. Furthermore, the simplified RA-STM_II effectively reflects the impact of three governing parameters <i>a/d</i> ratio, <i>ρ</i><sub><i>f</i></sub><i>E</i><sub><i>f</i></sub>, and <i>f</i><sub><i>cm</i></sub> on the shear strength.</p>

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A data-enhanced simplified RA-STM for shear strength estimation of FRP-RC deep beams

  • 期刊论文

  • 发表日期：

    2026年1月10日

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  • Phan Duy Nguyen,
  • Vu Hiep Dang

摘要

In recent years, the shear strength of fiber-reinforced polymer (FRP) reinforced concrete (RC) beams has been increasingly well documented, as these beams are more susceptible to shear failure than conventional steel-RC beams. This study focuses on developing a rational mechanism-based model for predicting the shear capacity of FRP-RC deep beams without stirrups. A rotating angle-softened truss model (RA-STM) with an appropriate tension-stiffening relationship is employed as the base model. The predictive performance of the base RA-STM is validated against 177 experimental datasets gathered from existing literature. The analytical data derived from the base RA-STM are subsequently used to improve performance via a data-driven approach. Consequently, a failure mode classification index is developed to classify the failure mechanisms of deep FRP-reinforced beams without transverse reinforcement, and explicit functions for equilibrium and compatibility conditions are formulated. Two simplified versions of the base RA-STM (RA-STM_I and RA-STM_II) are established which provides better predictions than several other mechanical-based models. Furthermore, the simplified RA-STM_II effectively reflects the impact of three governing parameters a/d ratio, ρfEf, and fcm on the shear strength.