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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.

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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.

Item Type: Journal Article
ISSN: 0924-0136
Keywords: constitutive model; non-linear optimisation; confidence limit; neural network
Academic Unit/Department: Mathematics, Computing and Technology > Engineering & Innovation
Mathematics, Computing and Technology
Item ID: 6963
Depositing User: Martin Rist
Date Deposited: 22 Feb 2007
Last Modified: 14 Jan 2016 16:28
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