Probabilistic failure simulation of glass fibre reinforced weft-knitted thermoplastics

• Published in: Composites science and technology Vol. 90; pp. 25 - 31
• Main Authors: Thieme, M., Boehm, R., Gude, M., Hufenbach, W.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 10.01.2014; Elsevier
• Subjects: A. Textile composites; Applied sciences; B. Fracture; C. Probabilistic methods; D. Failure criterion; E. Multi-axial testing; Exact sciences and technology; Forms of application and semi-finished materials; Laminates; Polymer industry, paints, wood; Technology of polymers; E. Multi-axial testing; B. Fracture; C. Probabilistic methods; D. Failure criterion; A. Textile composites; Monte Carlo method; Experimental test; Thermoplastics; Computer simulation; Laminate; Fiber reinforced material; Theoretical study; Mechanical properties; Fracture criterion; Mineral fiber; Modeling; Composite material; Glass fiber fabric; Loadbearing capacity; Probabilistic model; Knitted fabrics; Woven material; Fracture mode
• ISSN: 0266-3538; 1879-1050
• DOI: 10.1016/j.compscitech.2013.10.011

If textile-reinforced composites should be put into practice, the proof of load-bearing capacity has to be provided. For this purpose, deterministic overall safety proofs without material adapted partial safety factors are used which do not meet the textile-specific scatter characteristics and therefore neglect many advantages of those composites. Based on deterministic stress-based failure criteria and given loading conditions, a probabilistic methodology to predict the joint failure probability is proposed. The methodology is verified experimentally for hybrid yarn based textile thermoplastics. A statistical material characterisation using flat specimens, multi-axial tests with tube specimens and a Monte-Carlo simulation are used for that purpose. As a significant outcome of the study, the reliability of the failure prediction is significantly improved especially for multi-axial stress states with failure mode interaction. Based on the improved knowledge about the anisotropic material uncertainties, a more significant partial safety factor can be determined.