Mesoscopic analysis and intra-layer progressive failure model of fused filament fabrication 3D printing GFRP.

• The concept of continuous printing filament hypothesis is proposed through mesoscopic analysis. • A novel progressive failure model is established to predict the intra-layer failure process of FFF 3D printing GFRP. • Mechanical parameters of FFF 3D printing GFRP are determined by designing specific specimens and tests. • The distribution and regularities of intra-layer failure of FFF 3D printing GFRP are explored experimentally. The deficiency of failure analysis methods severely hinders the civil engineering application of Fused Filament Fabrication (FFF) 3D printing composites. In order to comprehensively investigate the failure process, this paper innovatively proposes the concept of continuous printing filament hypothesis based on mesoscopic analysis. This hypothesis serves to characterize the interconnection status between glass fiber reinforced polymer (GFRP) filaments during FFF 3D printing. Building upon this hypothesis, a progressive failure model is established, which can predict the intra-layer failure process under axial quasi-static load accurately. In the failure model, both Mode-2D and Mode-3D failure criteria are employed to pinpoint intra-layer damage initiation, while damage evolution is depicted using a stiffness reduction mode based on the fracture energy criterion. Simultaneously, the fundamental orthotropic mechanical parameters are examined, and 24 variations of printing laminates are meticulously designed. The ultimate tensile strengths (UTS), encompassing both cross-stacking (2/8, 4/6, 5/5) and angle-stacking (30°, 45°, 60°), are tested and simulated using the progressive failure method established during this study. Experimental results show that the lower layers of composites exhibit stronger ultimate resistance due to their layer-by-layer characteristics. Compared to the experimental results, all the relative errors of UTS predicted by Mode-3D are less than 15%. Therefore, the accuracy and predictive capacity of the progressive failure model are affirmed by the experimental data. [ABSTRACT FROM AUTHOR]