Volume 4, Number 2, 2020
|Number of page(s)||11|
|Section||Computational and Numerical Acoustics|
|Published online||16 April 2020|
Polynomial relations for cylindrical wheel stiffness characterization for use in a rolling noise prediction model
Matelys Research Lab, 7 Rue des Maraîchers, Bât B, 69120 Vaulx-en-Velin, France
2 INSA–Lyon, 20 Avenue Albert Einstein, 69621 Villeurbanne cedex, France
* Corresponding author: firstname.lastname@example.org
Accepted: 10 March 2020
In vehicle tire/road contact modeling, dynamic models are typically used which incorporate the vehicle’s suspension in their estimation: thus relying on a known stiffness to determine the movement of the wheel in response to roughness excitation. For the case of a wheeled device rolling on a floor (such as a delivery trolley moving merchandise around inside a commercial building), there is often no suspension, yet the wheel is still too soft to able to be considered mechanically rigid (as is the case in train/rail contact). A model which is aimed at incorporating the dynamic effects of the trolley in predicting the sound generated by rolling needs to provide a robust way of estimating the wheel’s effective stiffness. This work presents an original technique for estimating the stiffness of a solid cylindrical wheel. A parametric study was conducted in order to identify the dependence of the wheel stiffness on each of the relevant variables: including the wheel’s radius, axle size, width, applied load, and material properties. The methodology may be used to estimate the stiffness of new wheel types (i.e. different geometries and materials) without needing to solve a finite element model each time. Such a methodology has application beyond the field of acoustics, as the characterization of shapes with non-constant cross sections may be useful in the wider field of materials science.
© M. Edwards et al., Published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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