Simulation study reveals that nozzle geometry, fiber length, and extrusion speed dictate fiber alignment in 3D printed concrete, indicating pathways for tailored structural reinforcement.
Steel fibers are a promising reinforcement for 3D concrete printing (3DcP), which enhance post-cracking mechanical strength and fracture resistance. However, during the printing process, fibers tend to align with the printing direction, which exacerbates the inherent anisotropy of 3DcP structural components. Accurate prediction of fiber orientation is therefore essential for mitigating this effect. Traditional numerical approaches, however, are often limited by prohibitive computational costs due to the large number of fibers and the complex fluid–fiber interactions involved. This study proposes a computationally efficient three-dimensional coupled computational fluid dynamics–discrete element method (CFD–DEM) model for the rapid simulation of fiber orientation during the extrusion process. To improve computational efficiency, fluid–fiber interactions are treated using a one-way coupling framework, in which fiber rotation is analytically resolved based on Jeffery’s rotation equations. Validation against experimental measurements demonstrates the reliability of the proposed model. Parametric studies reveal that smaller nozzle openings, longer fiber lengths, and higher printing speeds promote stronger alignment of fibers along the printing direction, whereas the influence of rheological properties is relatively limited. In addition, shear-induced rotation is identified as one of the dominant mechanisms governing fiber orientation during extrusion. Increasing the size of the shear-dominated region near the nozzle exit can therefore improve fiber alignment in the printing direction. Beyond its engineering implications, the proposed modeling framework provides a design-oriented tool for fiber-reinforced 3DcP systems. By enabling the prediction and control of fiber orientation fields, the approach opens opportunities for directionally informed structural design in robotic concrete construction and can be extended to other short-fiber-reinforced material systems.
No takes yet. Share an insight, caveat, or question.
Yan et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: