3.8 Proceedings Paper

ANN-AGCS for the prediction of temperature distribution and required energy in hot forging process using finite element analysis

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MATERIALS TODAY-PROCEEDINGS
卷 21, 期 -, 页码 263-267

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ELSEVIER
DOI: 10.1016/j.matpr.2019.05.426

关键词

Adaptive genetic algorithm; Cuckoo search algorithm; Neural network; Finite element analysis; Hot forging process

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This work calculates the flow of stress of deforming metal as a function of temperature, strain and strain rate using a hybrid adaptive genetic algorithm and cuckoo search (ANN-AGCS) model. The flow behavior of material and the temperature variations in hot upsetting process are predicted by using the finite element analysis. To record the hot deformation performance through the force displacement. In this model to perform a hot non isothermal forging of a low carbon steel. A good decision is done between the predicted data and the measured results. (C) 2019 Elsevier Ltd. All rights reserved.

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