The crack behavior is necessary to characterize under quasi-static and cyclic loading to avoid brittle fracture in the textile-reinforced composites. This manuscript explains the fracture mechanism, deformation modes of the fracture, factors affecting the fracture toughness, and the fabrication process of textile-reinforced composites. The necessary tools and equipment used in the secondary processing, microstructural characterization, and sample quality evaluation are presented with their features. Experimental fracture toughness characterization with data reduction techniques and their specific ASTM test standards are provided for a better understanding of composite fracture mechanics. The fatigue failure mechanism is elaborated with affecting factors and experimental testing methods. Machine learning and AI-based advanced characterization techniques are also discussed with computational modeling of textile composites. The effect of moisture content, temperature, thermal cycling, UV radiation, chemical degradation, mechanical wear, and impact loading on the fracture and fatigue performance of textile composites is discussed to understand the environmental and operational effects.

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Fracture and Fatigue Behavior of High-Performance Textile Reinforced Composites

  • Pawan Sharma,
  • Harlal Singh Mali

摘要

The crack behavior is necessary to characterize under quasi-static and cyclic loading to avoid brittle fracture in the textile-reinforced composites. This manuscript explains the fracture mechanism, deformation modes of the fracture, factors affecting the fracture toughness, and the fabrication process of textile-reinforced composites. The necessary tools and equipment used in the secondary processing, microstructural characterization, and sample quality evaluation are presented with their features. Experimental fracture toughness characterization with data reduction techniques and their specific ASTM test standards are provided for a better understanding of composite fracture mechanics. The fatigue failure mechanism is elaborated with affecting factors and experimental testing methods. Machine learning and AI-based advanced characterization techniques are also discussed with computational modeling of textile composites. The effect of moisture content, temperature, thermal cycling, UV radiation, chemical degradation, mechanical wear, and impact loading on the fracture and fatigue performance of textile composites is discussed to understand the environmental and operational effects.