Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1583121 | Materials Science and Engineering: A | 2008 | 8 Pages |
Abstract
A thermo-mechanical model is developed to predict metal behavior during hot working operations. At first, a neural network model is trained to calculate flow stress of deforming metal as a function of temperature, strain and strain rate and then by coupling the neural network model and a thermo-viscoplastic finite element model, temperature and velocity fields during hot open die forging process are predicted. To examine the model, hot nonisothermal upsetting on a low carbon steel is performed while force–displacement behavior and temperature history during hot working are recorded. A good agreement is observed between the predicted data and the measured results.
Related Topics
Physical Sciences and Engineering
Materials Science
Materials Science (General)
Authors
Siamak Serajzadeh,