On the use of Stochastic Bouc–Wen model for simulating viscoelastic internal variables from a finite element approximation of steady-rolling tire

Abstract

Reducing tire rolling resistance and energy loss is a topic of interest to the tire industry. Understanding and modeling these phenomena are essential to approach this problem and propose robust solutions. This work suggests a reduced-order model based on the Bouc–Wen model to simulate internal variables from viscoelastic constitutive laws. Furthermore, sensitivity analysis is performed on the Bouc–Wen parameters to evaluate their influence on the system response and capture the full range of possible values that improve the predictive ability of the reduced-order model. This task is accomplished by calculating the Sobol’s indices estimated from a Polynomial-Chaos expansion. Once the range of feasible model solutions is established, the reduced-order model is calibrated through Bayesian inference. Finally, the uncertainties are propagated, and the reduced-order model is validated using data of viscoelastic internal variables from the finite element approximation of a steady-rolling tire. Satisfactory results are obtained, as the reduced-order model can simulate viscoelastic internal variables with a reduced computational cost for some branches of interest. Its responses are in agreement with the experimental data.

Characterizing the nonlinear behavior of viscoelastic materials: A Bayesian approach combining oberst beam experiments and digital-twin simulations

“…The global sensitivity analysis is carried out by means of the Sobol indices that are, in turn, calculated by the Polynomial-Chaos Expansion (PCE). The procedure is performed with UQLab framework [35], and further details of the methodology are available in [36].…”