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On the constitutive modeling using meta-models and their deployment for finite element analysis to evaluate the high temperature deformation behaviour of Al 2014 alloy

Isothermal hot compression tests were carried out on Al 2014 alloy over a range of deformation temperatures (300–500 °C) and strain rates (0.0003–1 s −1 ). The flow stress data obtained from the experiment as a function of temperature, strain rate, and strain were used to develop constitutive models...

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Bibliographic Details
Published in:International journal on interactive design and manufacturing 2024-05, Vol.18 (4), p.2247-2259
Main Authors: Mahender, T., Balasundar, I., Gupta, A. V. S. S. K. S., Raghu, T.
Format: Article
Language:English
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Summary:Isothermal hot compression tests were carried out on Al 2014 alloy over a range of deformation temperatures (300–500 °C) and strain rates (0.0003–1 s −1 ). The flow stress data obtained from the experiment as a function of temperature, strain rate, and strain were used to develop constitutive models using three popularly used meta-models viz., genetic algorithm (GA), response surface methodology (RSM), and artificial neural network (ANN). The prediction accuracy of meta-models was evaluated using standard statistical parameters such as correlation coefficient (R) and average absolute relative error (AARE). RSM and ANN showed better prediction at high temperature and strain rates when compared to GA. A quartic regression equation was suggested by RSM, while a 3–15–1 neural network architecture provided a better correlation. To check the reliability of the meta-models, the established meta-model constitutive equations were deployed in a commercial finite element analysis software through user subroutines. The results obtained were then compared and discussed here.
ISSN:1955-2513
1955-2505
DOI:10.1007/s12008-022-01172-w