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    An improved generic Johnson-Cook model for the flow prediction of different categories of alloys at elevated temperatures and dynamic loading conditions

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    Date
    2021
    Author
    Shokry, Abdallah
    Gowid, Samer
    Kharmanda, Ghais
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    Abstract
    This paper presents a generic model for material flow prediction based on the well-known Johnson-Cook model. The model is developed to precisely predict the flow behavior of various categories of alloys. The coupled effects between strain, strain rate, and temperature were taken into consideration. The proposed model is developed and assessed using the hot deformation data of four different categories of alloys; with four different base elements. Besides, the data of two different alloys under dynamic loading are used for assessment. The proposed modification is compared to the original Johnson-Cook model and three different modifications for the Johnson-Cook model; a model for the hot deformation and two models for the dynamic loading, giving that all alloys have different base elements. The well-known statistical correlation coefficient parameters (R), Average Absolute Relative Error (AARE), and Root Mean Squared Error (RMSE) are used to assess the prediction accuracy of the proposed model. The results show that the proposed model outperforms the other addressed models as it can precisely predict the flow behavior of the six alloys, with the highest R-value of 0.9940 ± 0.0126 and lowest AARE and RMSE values of 1.95 ± 1.08 % and 4.15 ± 3.47 MPa, respectively.
    DOI/handle
    http://dx.doi.org/10.1016/j.mtcomm.2021.102296
    http://hdl.handle.net/10576/53012
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    • Mechanical & Industrial Engineering [‎1461‎ items ]

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