Optimization of drilling parameters to minimize delamination in CNT-filled GFRP composites using machine learning

Optimization of drilling parameters to minimize delamination in CNT-filled GFRP composites using machine learning

Composites are most commonly fastened in assemblies by drilling. The current investigation examines the effect of the drilling factors on the quality of the drilled holes. The holes were drilled on epoxy resin polymer composites reinforced using glass fibers with Carbon nano tube (CNT) as fillers. H...

Full description

Saved in:
Bibliographic Details
Main Authors: Aveen K P, Ullal Vignesh Nayak, K M Pranesh Rao, Shivaramu H T, V Londhe Neelakantha, Shashikumar C M
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Applications in Engineering Science
Subjects:
FRP composites
Delamination factor
CNT filler
Machine learning
Multi-output random forest regressor
Bayesian optimization
Online Access:http://www.sciencedirect.com/science/article/pii/S266649682500055X
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.sciencedirect.com/science/article/pii/S266649682500055X

Similar Items