Parameter optimisation in constitutive equations for hot forging

Mulyadi, M.; Rist, M.A.; Edwards, L. and Brooks, J.W. (2006). Parameter optimisation in constitutive equations for hot forging. Journal of Materials Processing Technology, 177(1-3) pp. 311–314.

DOI: https://doi.org/10.1016/j.jmatprotec.2006.04.058

Abstract

Various methods for parameter optimisation in constitutive equations applied to the hot deformation of a popular alpha-beta titanium alloy have been examined. The use of direct search and gradient methods are shown to be effective, even with a limited dataset, and reliable confidence limits can be computed in each case. However, a hybrid approach, whereby genetic algorithms are used to find an initial parameter starting point, and then a direct search (simplex) method is applied to obtain a global minimum, is particularly promising. For comparison, an artificial neural network approach, which does not require the use of any constitutive equations, has also been implemented.

Viewing alternatives

Metrics

Item Actions

Export

You can export this page using these formats Digital Object Identifier - DOI

About

• Item ORO ID
• 6963
• Item Type
• Journal Item
• ISSN
• 0924-0136
• Keywords
• constitutive model; non-linear optimisation; confidence limit; neural network
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Engineering and Innovation
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Depositing User
• Martin Rist