Tribological behaviour of Al6061/Gr/WC hybrid MMCs using multi-response optimisation Online publication date: Mon, 03-Apr-2023
by Gangadhara Rao Ponugoti; Ravi Kumar Mandava; Pandu Ranga Vundavilli
International Journal of Mathematical Modelling and Numerical Optimisation (IJMMNO), Vol. 13, No. 2, 2023
Abstract: The current investigation is motivated to examine the improvement in mechanical properties and tribological behaviour of Al6061/Gr/WC. Initially, the mechanical and tribological properties were evaluated after adding the reinforcement that is, graphite (Gr) at 3, 6, 9 and 12 wt.% compositions. Therefore, 9 wt.% of Gr generated superior properties than others. Consequently, the hybrid composites were fabricated by reinforcing tungsten carbide (WC) at 1, 2, 3 wt.% and Gr at 9 wt.%. Successful fabrication of the hybrid composites was confirmed through SEM examinations for microstructural characterisation. Further, the concept of design of experiments (DOEs) has been used to obtain the number of experiments. Later on, two nature inspired optimisation algorithm that invasive weed optimisation (IWO) and particle swarm optimisation (PSO) were implemented to determine the optimal wear properties and the results were compared with grey relational analysis (GRA) approach.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Mathematical Modelling and Numerical Optimisation (IJMMNO):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email [email protected]