Quantitative prediction of the aged state of Ni-base superalloys using PCA and tensor regression

Journal Article · 31 January 2019 · Acta Materialia

DOI: https://doi.org/10.1016/j.actamat.2018.11.047 · OSTI ID:1636990

Gorgannejad, S.; Reisi Gahrooei, M.; Paynabar, K.; Neu, R. W.

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• Sponsoring Organization: USDOE
• Grant/Contract Number: FE0011722
• OSTI ID: 1636990
• Journal Information: Acta Materialia, Journal Name: Acta Materialia Journal Issue: C Vol. 165; ISSN 1359-6454
• Publisher: ElsevierCopyright Statement
• Country of Publication: United States
• Language: English