Experimental Investigation and Predictive Modelling of Tribological Behaviour in Fly Ash Reinforced Polymer Composites Fabricated via Stereolithography
subject: Fly ash; Predictive modelling; Stereolithography; Sustainable materials; Wear behaviour
description: Tribological evaluation of fly ash-reinforced UV-curable resin composites produced through stereolithography additive manufacturing formed the central focus of this study. Controlled fly ash additions extending up to 2% by weight were examined, and all tests ran under dry sliding conditions. Neat resin was designated as the experimental reference throughout. Even with the modest addition of 0.5% fly ash, wear came down by roughly 9.8%, which was small but directionally significant. Moving to 1% fly ash pushed wear reduction to 16.4%. At 1.5%, the reduction advanced further to 21.3% with all evaluations performed under identical testing conditions. The 2% fly ash specimen produced the highest wear reduction of 25.8% among all compositions examined. Frictional behavior followed a comparable declining trend across filler levels. At 0.5% fly ash COF fell 7.6% below the neat resin value, and at 1% that reduction grew to 12.9%. The 1.5% addition brought friction reduction to 17.4%. Total COF reduction at 2% fly ash reached 20.3%, which confirmed a steady and consistent frictional improvement with progressive filler incorporation. Linear regression and artificial neural networks and XGBoost-based gradient boosting were the three predictive frameworks developed alongside experimental work. All three tracked closely with measured tribological outcomes. Prediction accuracies reached up to 95.4% with lower error values documented across every model. The 2% fly ash formulation stood out as the most effective composition tested. It delivered the strongest combined improvements in wear resistance and friction stability while remaining fully compatible with the operational demands of additive manufacturing. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2026.
creator: Keshavamurthy, R.; Suma, V.; Ramesh, C.S.; Rajhi, Ali A.; Duhduh, Alaauldeen A.; Ravitej, Y.P.
source: Journal of Bio- and Tribo-Corrosion;Volume;12;Issue;2;Article No.;91;
publisher: Springer Science and Business Media Deutschland GmbH
date: 01-01-2026
rights: Restricted Access; Hardcopy may be available in the library
relation: ISSN: 21984220;
format: online
language: English
type: Article
coverage: Keshavamurthy R., Department of Mechanical and Automobile Engineering, Christ University, Karnataka, Bangalore, 560074, India; Suma V., Department of Computer Science and Design, Dayananda Sagar College of Engineering, Karnataka, Bangalore, 560078, India; Ramesh C.S., Department of Mechanical Engineering, GM University, Karnataka, Davanagere, India; Rajhi A.A., Department of Mechanical Engineering, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia; Duhduh A.A., Department of Mechanical Engineering Technology, CAIT, Jazan University, P.O. Box 114, Prince Mohammed Street, Jazan, 45142, Saudi Arabia; Ravitej Y.P., Department of Mechanical Engineering, Dayananda Sagar University, Karnataka, Bangalore, India