Modelling of hyperelastic polymers for automotive lamps under random vibration loading with proportional damping for robust fatigue analysis


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Abstract

The objective of this paper was to model random vibration response of components of an automotive lamp made of Polycarbonate/Acrylonitrile Butadiene Styrene (PC-ABS), Polymethyl methacrylate (PMMA) and Polypropylene 40% Talc filled (PPT40) materials using a nonlinear hyperelastic model. Traditionally, the Rayleigh damping matrix used in the dynamic response analysis is constructed considering linear elastic behaviour based on either initial stiffness or secant stiffness. The performance of linear stiffness matrices is compared in this work with that based on the nonlinear hyperelastic, Mooney-Rivlin model, specifically addressing Rayleigh damping matrix construction. The random vibration responses of 10 samples of each material are measured. The mean square error of acceleration response was used to assess the effectiveness. Considering three materials of study, the hyperelastic model resulted in the reduction of the least square error at best by 11.8 times and at worst by 2.6 times. The Mooney-Rivlin material model based Raleigh damping matrix was more accurate in modelling the dynamic behaviour of components of nonlinear materials and it also represented the manufacturing variabilities more reliably.

Authors

Chukwudi P. Okeke
Anand N. Thite
John F. Durodola
Neil A. Fellows
M.T. Greenrod

Faculty

Faculty of Technology, Design and Environment

Keywords

hyperelastic, Mooney-Rivlin material models, nonlinear stress-strain, simulation, modelling, proportional damping, Rayleigh, transient analysis, random vibration, manufacturing variations

DOI

10.1016/j.prostr.2018.12.302

Citation

Okeke, C., Thite, A., Durodola, J., Fellows, N. and Greenrod, M. () 'Modelling of hyperelastic polymers for automotive lamps under random vibration loading with proportional damping for robust fatigue analysis', European Conference on Fracture (ECF22). Belgrade, Serbia, 26-31 August. Elsevier, pp.1460-1469.DOI: 10.1016/j.prostr.2018.12.302.

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