Displacement transmissibility based system identification for polydimethylsiloxane integrating a combination of mechanical modelling with evolutionary multi-objective optimization. Issue 6 (2nd June 2020)

• Record Type: Journal Article
• Authors: Sharma, Arun Kumar; Datta, Rituparna; Agarwal, Shubham; Bhattacharya, Bishakh
• Is Part Of: Engineering optimization. Volume 52:Issue 6(2020)
• Page Start: 1037
• Page End: 1051
• Publication Date: 2020-06-02
• Subjects: Burger model -- Kelvin–Voigt model -- NSGA-II -- PDMS -- system identification -- Zener model; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2019.1634701
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: In this study, displacement transmissibility based parameter identification of a silicon based organic viscoelastic polymer, polydimethylsiloxane (PDMS) has been proposed. The vision is to fill the identification gap for a mechanical model of soft viscoelastic polymers of average-to-high molecular weight. The present investigation is based on an experimental transmissibility analysis carried out on a PDMS block in a self-designed and fabricated system using laser technology. The parametric identification of four viscoelastic models attempted in this study includes the Kelvin–Voigt (K-V) model, the Zener model, and the Burger-I and Burger-II models. To identify the parameters accurately, a multi-objective optimization problem with conflicting objective functions has been solved using the Non-dominated Sorting Genetic Algorithm (NSGA-II). The obtained results indicate that the Zener model best captures the transmissibility variation. Thus, the proposed technique can be utilized for developing mechanical models and identifying the parameters of similar average-to-high molecular weight soft viscoelastic polymers.