Finite element analysis (FEA) applied to tire design is a valuable tool for reducing development time and costs. Validation of the predicted results via measurements is required for acceptance by development engineers. It will be shown that the three dimensional Digital Imaging Correlation (DIC) technique is a viable method for obtaining validation data of experimental displacements and strains for tires. A method for verifying the accuracy of the DIC process itself by displacing a thin, rectangular test sample of rubber material a known distance is explained. Once the measurement technique is proven accurate, the focus of this paper shifts to verifying the finite element model predictions against the DIC measurements. This verification includes comparison of surface displacements and in-plane strain values. Validation of internal strain predictions are accomplished by removing material from the exterior of both the physical test tire and the finite element model, thus exposing interior components. This validation procedure demonstrates the accuracy of the finite element model simulations and has lead to increased usage of analysis in place of prototypes and testing.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Using 3D digital imaging correlation techniques to validate tire FEM


    Additional title:

    Validierung der FEM-Simulation von Reifen durch digitale 3D-Bildkorrelationsmethoden


    Contributors:


    Publication date :

    2006


    Size :

    11 Seiten, 9 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





    IMAGE PROCESSING TECHNIQUES TO VALIDATE SENSOR CLEANING

    LEPORT KILIAN / ARTICHOKER JACE / NEWHOUSE WESLEY et al. | European Patent Office | 2024

    Free access

    Using Digital Tools to Analyse and Validate Sound Measurements

    Norell, Fredrik | TIBKAT | 2021

    Free access


    Target Correlation and Allocation Using Reliability Metrics to Validate Design Effectiveness of Improved Sample

    Yogeeswaran, Ramarajan / Subramaniom, Shiju | British Library Conference Proceedings | 2018