Prediction of peak temperature value in friction lap welding of aluminium alloy 7475 and PPS polymer hybrid joint using machine learning approaches
Author:
Funder
VIT University
Publisher
Elsevier BV
Subject
Mechanical Engineering,Mechanics of Materials,Condensed Matter Physics,General Materials Science
Reference11 articles.
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3. Joining of aluminum alloy and polymer via friction stir lap welding;Huang;J. Mater. Process. Technol.,2018
4. Improving mechanical properties of composite/metal friction stir lap welding joints via a taper-screwed pin with triple facets;Huang;J. Mater. Process. Technol.,2019
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1. Machine learning approach with various regression models for predicting the ultimate tensile strength of the friction stir welded AA 2050-T8 joints by the K-Fold cross-validation method;Materials Today Communications;2023-03
2. Strategies to improve joint strength of friction lap welded AA7475/PPS hybrid joint with surface pre-treatment on AA7475;Materials Letters;2023-02
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4. Evolving application of machine learning in the synthesis of CHA/ZrO2 nanocomposite for the microhardness prediction;Materials Letters;2022-11
5. Impact of Pin Length on Joint Strength of Friction Lap Welded Aluminum Alloy 7475 and Polyphenylene Sulfide Thermoplastic Polymer Joints;Journal of Materials Engineering and Performance;2022-10-31
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