A hybrid decoupled machine learning framework with physical constraints for predicting welding-induced residual stresses in steel girders.

Zhang J, Huang W, Ni Z, Zhang Y

Open source

DOI
10.1038/s41598-026-48635-8
Published
2026 Apr 17
Container
Scientific reports
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.1038/s41598-026-48635-8,
  title = {A hybrid decoupled machine learning framework with physical constraints for predicting welding-induced residual stresses in steel girders.},
  author = {Zhang J and Huang W and Ni Z and Zhang Y},
  year = {2026},
  journal = {Scientific reports},
  doi = {10.1038/s41598-026-48635-8},
  url = {https://doi.org/10.1038/s41598-026-48635-8}
}

RIS

TY  - JOUR
TI  - A hybrid decoupled machine learning framework with physical constraints for predicting welding-induced residual stresses in steel girders.
AU  - Zhang J
AU  - Huang W
AU  - Ni Z
AU  - Zhang Y
PY  - 2026
JO  - Scientific reports
DO  - 10.1038/s41598-026-48635-8
UR  - https://doi.org/10.1038/s41598-026-48635-8
ER  -

APA

J, Z., W, H., Z, N., & Y, Z. (2026). A hybrid decoupled machine learning framework with physical constraints for predicting welding-induced residual stresses in steel girders.. Scientific reports. https://doi.org/10.1038/s41598-026-48635-8

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