Abstract
This paper employs rigid-plastic finite element DEFORMTM 3D software to estimate the plastic deformation behavior of an aluminum billet during its axisymmetric extrusion through a conical die. The die and container are assumed to be rigid bodies and the temperature change induced during extrusion is ignored. The important parameters which effect on the extrusion process were assumed to be: the reduction of area (0.75), semi- cone die angles (5, 6, 7, 8, 10, 12, and 14o) coefficient of friction is 0.05 and the extrusion speed is 250 mm/s. Under various extrusion conditions, the present numerical analysis estimates the stresses, the die load and the flow velocity of the billet at the die exit. Genetic algorithm coupled with neural network is employed to find optimum die angle leading to minimum stresses without any constraint. The simulation results confirm the suitability of the current finite element software for modeling the three-dimensional cold extrusion of aluminum rod.
Highlights
Forward extrusion is a forming process in which a work piece is pushed through a die whose exit diameter is smaller than that of the work piece
Optimization of the design variables is conducted by a genetic algorithm, where the fitness values are evaluated on the basis of a finite element method (FEM) analysis model
Figure (4) shows a Comparison with the present finite element results, this result compared with the experimental work of Gouveia et al [15] for the same conditions to validate the present work and the maximum error was 9.42% between the present work and experimental work for Gouveia et al They were a good agreement
Summary
Forward extrusion is a forming process in which a work piece is pushed through a die whose exit diameter is smaller than that of the work piece. The effects of pockets in the porthole die on the metal flow, temperature at the die bearing exit and the extrusion load. Two different multi-hole portholes die with and without pockets in lower die were designed. Pockets in lower die play an important role, such as more even metal flow and plastic deformation, lower temperature rise at the bearing exit and lower peak extrusion load, which indicates the possibility of increasing the extrusion speed and productivity which is beneficial to the extrusion process [1]. A new approach to the optimal design of the die shape in extrusion is presented by Chung et al [2]. Optimization of the design variables is conducted by a genetic algorithm, where the fitness values are evaluated on the basis of a finite element method (FEM) analysis model
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