Artificial Neural Network Model: Prediction of Mechanical Properties in Beta-Titanium Biomaterial Conference Paper

abstract

• Theoretical prediction of mechanical properties using Artificial Neural Network (ANN) of a new beta-titanium alloy was investigated and compared with the experimental results obtained as a function of heat treatment. The cold worked biomaterial was subjected to different thermal processing cycles. The experimental values of mechanical properties were determined using MTS Landmark-servo hydraulic UTS machine. The new beta-titanium alloy demonstrated an excellent combination of strength and ductility for -annealing and solution treatment plus aging thermal processing treatments. This data was used to train an artificial neural network (ANN) model to predict hardness. The predicted hardness values were found to demonstrate very good agreement with the experimental values.

authors

• Haque, Mohammed

published proceedings

• Applied Mechanics and Materials

author list (cited authors)

• Sudhakar, K. V., & Haque, M. E.

citation count

• 4

complete list of authors

• Sudhakar, KV||Haque, ME

publication date

• October 2013

publisher

• Trans Tech Publications  Publisher

published in

• Applied Mechanics and Materials  Journal

keywords

• 40 Engineering
• 4016 Materials Engineering
• Bioengineering

Digital Object Identifier (DOI)

• 10.4028/www.scientific.net/amm.367.40

International Standard Book Number (ISBN) 13

• 9783037857885

start page

• 40

end page

• 44

volume

• 367

URL

• http://dx.doi.org/10.4028/www.scientific.net/amm.367.40