• Introducing a parameterized model to capture the Unit-Cell dimensions of 2D braids • A novel meso-scale cylindrical RVE using cyclic symmetry and PBC for 2D braids • Nine-thread tow FEM model for accurate microstructural stress distribution analysis • Mesh-Convergence and validation with less than 8% prediction error • Continuous axial strands boost triaxial composite stiffness by 10–15% Accurate prediction of the elastic constants of braided composites has become increasingly critical, yet the complex geometry of these materials remains challenging for evaluating stiffness. To address this challenge, a novel meso-scale finite-element representative volume element (RVE) framework was developed to predict the elastic behavior of tubular biaxial and triaxial braided composites directly. An analytical approach was first derived to calculate the minimal curved unit-cell dimensions regardless of braid diameter for the three main patterns as a function of curvature angle and yarn pitch length of the braid structure. Subsequently, periodic RVEs were generated to capture the engineering properties of the resulting composites. Periodic boundary conditions were applied under six independent loading modes to extract the full 6 × 6 stiffness tensor. The resulting predictions were validated through uniaxial tensile and torsion tests to verify tube-level modulus, and also three-point bending experiments to confirm the model's robustness under combined stress states, showing an error margin of less than 8% compared to numerical results. A qualitative comparison of maximum principal stress contours further validated the RVE's capability to replicate anisotropic load paths and shear coupling. Taken together, the proposed multiscale RVE–FEM methodology is demonstrated to be a reliable, physics-based tool for the design and optimization of braided composite structures.
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Ali Shakersoureh
Amirkabir University of Technology
Majid Safarjohari
Amirkabir University of Technology
Hadi Dabiryan
Amirkabir University of Technology
Results in Engineering
Amirkabir University of Technology
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Shakersoureh et al. (Wed,) studied this question.
synapsesocial.com/papers/69e31f1a40886becb653e8b8 — DOI: https://doi.org/10.1016/j.rineng.2026.110558