Determination of Prony Series Coefficient of Polymer Based on Experimental Data in Time Domain Using Optimization Technique

Polymers due to their versatile properties and characteristics are very promising material for the future. But the mechanical behavior of the polymer depends on loading type, temperature and time. These behaviors of the polymer can be mathematically modeled using the phenomenological Prony series models. But the challenge is to find the parameters tau(q) and E-q to provide a good conformance with the experimental data. In the present work methodology for inverse identification in the time domain for experimental data using mixed optimization techniques (Genetic Algorithm and Nonlinear Programing) is used to determine Prony series coefficients. The results are compared with the experimental data to validate the method.