Heat treated cast aluminum components like engine blocks and cylinder heads can develop significant amount of residual stress and distortion particularly with water quench. To incorporate the influence of residual stress and distortion in cast aluminum product design, a rapid simulation approach has been developed based on artificial neural network and component geometry characteristics. Multilayer feed-forward artificial neural network (ANN) models were trained and verified using FEA residual stress and distortion predictions together with part geometry information such as curvature, maximum dihedral angle, topologic features including node's neighbors, as well as quench parameters like quench temperature and quench media.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Rapid Residual Stress and Distortion Prediction in Cast Aluminum Components Using Artificial Neural Network and Part Geometry Characteristics


    Additional title:

    Sae Technical Papers


    Contributors:
    Xiao, Bowang (author) / Wang, Qigui (author) / Wen, Xiao (author) / Wang, Yucong (author) / Quan, Zhibin (author) / Gao, Zhiqiang (author)

    Conference:

    SAE 2014 World Congress & Exhibition ; 2014



    Publication date :

    2014-04-01




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





    Residual Stress Prediction for Part Distortion Modeling

    Grevstad, A. / Zamorano, L. / Saini, N. et al. | SAE Technical Papers | 2006


    Development of experimental methods to validate residual stress models for cast aluminum components

    Lasecki,J.V. / Su,X. / Allison,J.E. et al. | Automotive engineering | 2006


    Development of Experimental Methods to Validate Residual Stress Models for Cast Aluminum Components

    Lasecki, J. V. / Allison, John E. / Su, Xuming | SAE Technical Papers | 2006


    Modeling of Residual Stresses in Quenched Cast Aluminum Components

    Chang, Cherng-Chi / Paluch, David / zhang, Guihua et al. | SAE Technical Papers | 2011