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In this paper, a stiffness–temperature model based on Weibull statistics was applied to quantitatively describe changes in the storage modulus of thermoplastic polyurethane over a wide range of temperature. The variation of the storage modulus with temperature was obtained from dynamic mechanical analysis tests across transition temperatures. Both the physical and statistical parameters of the applied model were estimated in the process of parametric fitting of the model to the storage modulus versus a temperature curve by using a trust region algorithm for a robust nonlinear least squares method. Good agreement between the modeled and experimental data has been found over the entire investigated temperature range, including all observed relaxation transitions.

Weibull distribution application on temperature dependence of polyurethane storage modulus