The accuracy of a finite element model for design and analysis of a metal forging operation is limited by the incorporated material model’s ability to predict deformation behavior over a wide range of operating conditions. Current rheological models prove deficient in several respects due to the difficulty in establishing complicated relations between many parameters. More recently, artificial neural networks (ANN) have been suggested as an effective means to overcome these difficulties. In the present work, a previously developed ANN with the ability to determine flow stresses based on strain, strain rate, and temperature is incorporated with finite element code. Utilizing this linked approach, a preliminary model for forging an aluminum wheel is developed. This novel method, along with a conventional approach, is then measured against the forging process as it is currently performed in actual production.
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ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
September 24–28, 2005
Long Beach, California, USA
Conference Sponsors:
- Design Engineering Division and Computers and Information in Engineering Division
ISBN:
0-7918-4740-3
PROCEEDINGS PAPER
A Virtual Model for Aluminum Hot Forging Using an Artificial Neural Network Material Model Within Finite Element Analysis
B. Scott Kessler,
B. Scott Kessler
University of Missouri at Columbia, Columbia, MO
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A. Sherif El-Gizawy
A. Sherif El-Gizawy
University of Missouri at Columbia, Columbia, MO
Search for other works by this author on:
B. Scott Kessler
University of Missouri at Columbia, Columbia, MO
A. Sherif El-Gizawy
University of Missouri at Columbia, Columbia, MO
Paper No:
DETC2005-85257, pp. 1039-1048; 10 pages
Published Online:
June 11, 2008
Citation
Kessler, BS, & El-Gizawy, AS. "A Virtual Model for Aluminum Hot Forging Using an Artificial Neural Network Material Model Within Finite Element Analysis." Proceedings of the ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 3: 25th Computers and Information in Engineering Conference, Parts A and B. Long Beach, California, USA. September 24–28, 2005. pp. 1039-1048. ASME. https://doi.org/10.1115/DETC2005-85257
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