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Specificity of statistics of elastic and strain-strength properties of high-strength polypropylene fibers
Russian version
DOI: 10.21883/PSS.2022.01.52493.199
Boiko Yu.M.1, Marikhin V.A.1, Moskalyuk O.A. 2, Myasnikova L.P.1
1Ioffe Institute, St. Petersburg, Russia
2Saint-Petersburg State University of Technology and Design, St. Petersburg, Russia
Email: yuri.boiko@mail.ioffe.ru
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Regularities of statistical distributions of a complex of mechanical properties, including the modulus of elasticity (E), strength (sigma) and strain at break (εb), high-strength industrial oriented polypropylene (PP) fibers have been analyzed using the Weibull and Gauss models based on a large array of measurements (50 identical samples in each series). The values of the statistical Weibull modulus (m) - a parameter characterizing the scatter of the measured values of the data arrays of E, sigma and εb have been estimated for the PP samples of two types: single fibers (monofilaments) and multifilament fibers consisting from several hundred single fibers. For the PP multifilament fibers, a more correct description of the distributions of E, sigma and εb has been received both in the framework of the normal distribution (Gaussian distribution) and in the framework of the Weibull distribution in comparison with the description of such distributions for the PP monofilaments. The influence of the polymer chain conformation on the regularities of the statistical distributions of E, sigma and εb for the high-strength oriented polymeric materials with different chemical chain structures and the correctness of their descriptions in the framework of the Gauss and Weibull models have been analyzed. For this purpose, the values of m calculated in this work for PP with a helical chain conformation have been compared with the values of m determined by us earlier for ultra-high molecular weight polyethylene and polyamide-6 with the chain conformations in the form of an in-plane trans-zigzag. Keywords: polypropylene, mechanical properties, statistical analysis, Weibull distribution, Gaussian distribution.
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