Universal Journal of Mechanical Engineering Vol. 4(2), pp. 25 - 33
DOI: 10.13189/ujme.2016.040202
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Neural Network and Genetic Algorithm Based Finite Element Model for Optimal Die Shape Design in Al-1100 Cold Forward Extrusion

Abdul Kareem Flaih Hassan , Raad Jamal Jassim , Mustafa Muneam Jafaar ^*
Department of Mechanical Engineering, College of Engineering, University of Basra, Iraq

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 14^o) 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.

KEYWORDS
Extrusion, Die Angle, Stress Distribution, Aluminum Rod

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Abdul Kareem Flaih Hassan , Raad Jamal Jassim , Mustafa Muneam Jafaar , "Neural Network and Genetic Algorithm Based Finite Element Model for Optimal Die Shape Design in Al-1100 Cold Forward Extrusion," Universal Journal of Mechanical Engineering, Vol. 4, No. 2, pp. 25 - 33, 2016. DOI: 10.13189/ujme.2016.040202.

(b). APA Format:
Abdul Kareem Flaih Hassan , Raad Jamal Jassim , Mustafa Muneam Jafaar (2016). Neural Network and Genetic Algorithm Based Finite Element Model for Optimal Die Shape Design in Al-1100 Cold Forward Extrusion. Universal Journal of Mechanical Engineering, 4(2), 25 - 33. DOI: 10.13189/ujme.2016.040202.