Abstract
AbstractApplication of Ti aluminide is limited due to its poor ductility at room temperature. Over the last two decades several studies have been conducted and large amount of data have been generated. These data have been utilized in the present work to obtain optimized set of parameters through Mamdani fuzzy inference system. Ductility database were prepared and three parameters viz. alloy type, grain size and heat treatment cycle were selected for modeling. Additionally, ductility data were generated from literature for training and validation of models on the basis of linearity and considering the primary effect of these three parameters. All the data have been used to frame the fuzzy rules with its membership values. Performance of the models was evaluated, which shows model has better agreement with the data generated from observed data. Possibility of improving ductility more than 5% is observed for multicomponent alloy with grain size of 10-50μm using a multistep heat treatment cycle.KeywordsTi aluminideductilityMamdaniFuzzy
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
