FFF 3D打印CFRP带孔层合板拉伸失效行为的细观分析 及渐进损伤预测

Mesoscopic analysis and progressive failure prediction in tensile failure behavior of FFF 3D printing CFRP perforated laminates

  • 摘要: 为实现熔丝制造(Fused filament fabrication, FFF)3D打印复合材料精准、高效的渐进损伤预测,本文以FFF 3D打印碳纤维增强树脂基复合材料(Carbon fiber reinforced polymer,CFRP)带孔层合板为对象,对其拉伸失效行为开展了机理性探索。创新性提出了适用于FFF 3D打印CFRP结构的渐进损伤失效分析方法,该方法可精确模拟孔边应力集中状态下的层内失效-层间分离耦合行为,并修正了就位效应影响下的打印材料强度。同时,开展了较为系统的(正交铺设、角铺设、混合铺设和螺旋铺设)3D打印带孔层合板拉伸失效试验,从细观损伤到宏观失效多尺度角度对其渐进损伤行为进行了分析,验证了本文提出方法的正确性,并揭示了FFF 3D打印CFRP带孔层合板的失效机理。结果表明,FFF 3D打印CFRP带孔构件的拉伸失效由纤维断裂和基体开裂主导,同时伴随应力集中处的层间II型滑开剪切失效。此外,角铺设工况中由于存在不同层叠角度及族聚层厚度而引发就位效应,同种铺设比例下试件极限承载力最大相差15.29%。采用经验公式修正就位效应后的三维渐进损伤模型平均计算误差为4.51%。故本文所提出的渐进损伤模型可为FFF 3D打印CFRP在桥梁工程关键承力构件中的应用奠定理论基础。

     

    Abstract: To achieve precise and efficient progressive failure prediction for fused filament fabrication (FFF) 3D printing composite materials, this study investigates the tensile failure behavior of FFF 3D printing carbon fiber reinforced polymer (CFRP) perforated laminates, and the mechanistic exploration is conducted. A novel progressive failure analysis method is proposed, specifically developed for FFF 3D printing CFRP structures, which accurately simulates the coupled behavior of intra-layer failure and inter-layer delamination under hole-edge stress concentration while modifying the strength of printed materials considering in-situ effects. Systematic experimental investigations are conducted on 3D printing perforated laminates with diverse stacking configurations (cross-stacking, angle-stacking, mixed-stacking, and rotational-stacking), enabling multi-scale analysis from mesoscopic damage initiation to macroscopic structural failure to validate the proposed method and reveal the failure mechanisms. Results indicate that tensile failure of FFF 3D printing CFRP perforated laminates is dominated by fiber breakage and matrix cracking, accompanied by interlaminar Mode-II shear failure at stress concentration regions. Notably, in-situ effects induced by varying printing angles and clustered layer thicknesses in angle-stacking configurations resulted in up to 15.29% difference in ultimate bearing capacity among specimens with identical stacking orientations. The proposed model, incorporating empirical formula corrections for in-situ effects, demonstrates a mean prediction error of 4.51%. Thus, the progressive failure modeling framework establishes a theoretical foundation for bridge engineering applications of FFF 3D printing CFRP in critical load-bearing structures.

     

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