Hybrid machine learning and physical modeling of feedstock deformation during robotic 3D printing of continuous fiber thermoplastic composites.

Ghnatios C, Fayazbakhsh K

Open source

DOI: 10.1186/s40323-026-00337-6
Published: 2026
Container: Advanced modeling and simulation in engineering sciences
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1186/s40323-026-00337-6,
  title = {Hybrid machine learning and physical modeling of feedstock deformation during robotic 3D printing of continuous fiber thermoplastic composites.},
  author = {Ghnatios C and Fayazbakhsh K},
  year = {2026},
  journal = {Advanced modeling and simulation in engineering sciences},
  doi = {10.1186/s40323-026-00337-6},
  url = {https://doi.org/10.1186/s40323-026-00337-6}
}

RIS

TY  - JOUR
TI  - Hybrid machine learning and physical modeling of feedstock deformation during robotic 3D printing of continuous fiber thermoplastic composites.
AU  - Ghnatios C
AU  - Fayazbakhsh K
PY  - 2026
JO  - Advanced modeling and simulation in engineering sciences
DO  - 10.1186/s40323-026-00337-6
UR  - https://doi.org/10.1186/s40323-026-00337-6
ER  -

APA

C, G., & K, F. (2026). Hybrid machine learning and physical modeling of feedstock deformation during robotic 3D printing of continuous fiber thermoplastic composites.. Advanced modeling and simulation in engineering sciences. https://doi.org/10.1186/s40323-026-00337-6

Source records

pubmed · retrieved 2026-09-25T10:47:48.279Z
europe-pmc · retrieved 2026-09-25T10:47:48.272Z
doaj · retrieved 2026-09-25T10:47:48.253Z