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

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 vari...

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Bibliographic Details
Published in:Journal of vibration and control 2023-10, Vol.29 (19-20), p.4799-4813
Main Authors: Raqueti, Rafael da S, Teloli, Rafael de O, da Silva, Samuel, Bussetta, Philippe, Cunha, Americo
Format: Article
Language:English
Subjects:
Applications
Approximation
Bayesian analysis
Energy loss
Engineering Sciences
Mechanics
Parameter sensitivity
Polynomials
Reduced order models
Rolling resistance
Sensitivity analysis
Simulation
Statistical inference
Statistics
Viscoelasticity
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Summary: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.
ISSN:1077-5463
1741-2986
DOI:10.1177/10775463221125038