Predicting failure loads of graphene incorporated adhesively bonded single lap joints fabricated with short glass fibre reinforced polylactic acid using ANN approach
Thulasidhas Dhilipkumar, Abdellatif M. Sadeq, Arun Prasad Murali, Karthik V. Shankar, P. Karuppusamy, Murugan Rajesh, Mohammad Rezaul Karim, Karuppaiah Selvakumar, N. Dinesh kumar · 2025
Read Predicting failure loads of graphene incorporated adhesively bonded single lap joints fabricated with short glass fibre reinforced polylactic acid using ANN approach by Thulasidhas Dhilipkumar, Abdellatif M. Sadeq, Arun Prasad Murali, Karthik V. Shankar, P. Karuppusamy, Murugan Rajesh, Mohammad Rezaul Karim, Karuppaiah Selvakumar, N. Dinesh kumar (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12764977.txt.
Description
Thulasidhas Dhilipkumar and co-authors report a 2025 study of glued joints made from printed plastic parts with short glass fibres. They added graphene to the glue and asked if the joints got stronger. They also used a neural network to predict when joints would fail.
Print direction mattered: parts printed flat were strongest under pull. Adding a small share of graphene to the glue raised shear strength by about a fifth. It also raised the natural pitch of the joints, a sign of more stiffness. The network matched test results very closely. The authors say the mix of better glue and smart prediction can help design printed parts that are joined, not cast whole.
Catalog record
| CREATOR | Thulasidhas Dhilipkumar, Abdellatif M. Sadeq, Arun Prasad Murali, Karthik V. Shankar, P. Karuppusamy, Murugan Rajesh, Mohammad Rezaul Karim, Karuppaiah Selvakumar, N. Dinesh kumar |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 43 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |