Imprecise knowledge based design and development of titanium alloys for prosthetic applications

Datta, S. and Mahfouf, M. and Zhang, Qian and Chattopadhyay, P.P. and Sultana, N. (2015) Imprecise knowledge based design and development of titanium alloys for prosthetic applications. Journal of the Mechanical Behavior of Biomedical Materials, 53 . pp. 350-365. ISSN 1751-6161. (doi: (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

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Imprecise knowledge on the composition-processing-microstructure-property correlation of titanium alloys combined with experimental data are used for developing rule based models for predicting the strength and elastic modulus of titanium alloys. The developed models are used for designing alloys suitable for orthopaedic and dental applications. Reduced Space Searching Algorithm is employed for the multi-objective optimization to find composition, processing and microstructure of titanium alloys suitable for orthopaedic applications. The conflicting requirements attributes of the alloys for this particular purpose are high strength with low elastic modulus, along with adequate biocompatibility and low costs. The ‘Pareto’ solutions developed through multi-objective optimization show that the preferred compositions for the fulfilling the above objectives lead to β or near β alloys. The concept of decision making employed on the solutions leads to some compositions, which should provide better combination of the required attributes. The experimental development of some of the alloys has been carried out as guided by the model-based design methodology presented in this research. Primary characterizations of the alloys show encouraging results in terms of the mechanical properties.

Item Type: Article
Uncontrolled keywords: titanium alloy, orthopaedic application, alloy design, elastic modulus, yield strength, biocompatibility, rule based modelling, evolutionary algorithm, multi-objective optimization
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
T Technology > TA Engineering (General). Civil engineering (General) > TA168 Systems engineering, cybernetics and intelligent systems
T Technology > TA Engineering (General). Civil engineering (General) > TA 403 Materials Science
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: Qian Zhang
Date Deposited: 18 Sep 2015 14:14 UTC
Last Modified: 08 Sep 2016 23:00 UTC
Resource URI: (The current URI for this page, for reference purposes)
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