Stab and yarn pull-out resistance of shear thickening fluids (STFs)/E-glass based on PEG modification and modeling yarn pull-out behavior with artificial intelligence

Abstract

Impregnating fabrics with shear thickening fluid (STF) improves impact resistance. In this study modification of polyethylene glycol (PEG 200) was carried out to enhance the thickening behavior of STF. The rheological analysis shows tunned STFs by PEG modification with glutaric acid and oxalic acid increase the maximum viscosity by about 10.33 and 3.28 folds with respect to unmodified STF. Additionally, the alternations of a liquid dispersion medium (PEG) led to higher chain length in STFs, representing superior interaction between media and particles by profuse H-bonding. The results confirmed that increasing the molecular length of PEG-based on STF caused a significant improvement in the knife and spike stabbing impact resistance, quasi-static, and yarn pull-out performance of the neat fabric. In addition, it was realized, by increasing impact velocity the energy absorption ability of STF-treated fabric composite increases. Additionally, a regression analysis using artificial intelligence was applied to study the effect of the pull-out rate on the mechanical response of different materials. Using a third-order polynomial for AI regression model, it turned out that while the pull-out rate has the least influence on untreated E-glass fabrics (UEG) response, for other materials, the behavior changes significantly by increasing the rate from 100 to 400 mm/min.