Prediction of fibre orientation in FRC structural elements using a coupled SPH-DEM model

This study introduces a numerical framework for predicting fibre orientation in fibre-reinforced concrete (FRC) structural elements, using a coupled Smoothed Particle Hydrodynamics (SPH) and Discrete Element Method (DEM) approach. The methodology simulates the concrete casting process, leveraging a fibre bundling technique to enhance computational efficiency. A numerical model, implemented in Rocky-DEM with GPU acceleration, is coupled with a custom Python post-processor to assess fibre orientation and distribution within local mesh elements through 3D and 2D ellipsoidal representations. A parametric study was conducted to optimize the SPH element size and sound speed, ensuring the balance between accuracy and computational efficiency. The framework is validated using a benchmark of an FRC slab, demonstrating high accuracy in predicting local fibre orientation and distribution. The results highlight the method computational efficiency, particularly due to its GPU-based parallel computing implementation, which significantly reduces simulation time compared to CPU-based solvers. Compared to existing high-fidelity simulations, this study offers a practical, engineering-focused methodology that is computationally efficient and scalable for real-world FRC applications. The proposed approach is particularly well suited for the fabrication of horizontal FRC elements, with future research recommended for extending its applicability to vertical elements that are more sensitive to fibre segregation.