Bayesian calibration of constitutive models for polymeric foams
Résumé
Porous materials are traditionally used for their sound absorption and insulation properties. Over the past decade, more attention has been given to their elastic and damping properties. There is a particular interest in the automotive industry to replace heavy layers (consisting of constrained viscoelastic rubber layers) with felts or foams evidencing high damping capabilities. Hence, characterizing efficiently the viscoelastic properties of porous materials is crucial for quality control and further improvements in product development and fabrication. In this sense, the main contribution of this work is to propose a stochastic strategy to determine the constitutive equations describing the viscoelastic behaviour of foams. Vibration tests are carried out on a two-layer panel containing a free-layer of a foam. A finite element model is developed considering only the viscoelasticity of the porous skeleton, neglecting the influence of the fluid phase. A fractional derivative model is calibrated and validated for two types o foam based on a Bayesian framework. The models indicate that the reconstitute porous rubber presents absolute values of the complex modulus greater than the ones provided by the closed-cell polyurethane foam and its energy dissipation is greater the one provided by the closed-cell polyurethane one.