A physics-constrained framework for fatigue data augmentation of post-weld treated joints: censored S-N estimation with an exploratory generative component

Mülkoglu O., Kandemir M., Yildirim H.

JOURNAL OF INTELLIGENT MANUFACTURING, 2026 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1007/s10845-026-02975-4
  • Dergi Adı: JOURNAL OF INTELLIGENT MANUFACTURING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Compendex, INSPEC, Business Source Ultimate (EBSCO), Engineering Source (EBSCO), Materials Science & Engineering Collection (ProQuest), Pharma Collection (ProQuest), Technology Collection (ProQuest)
  • Anahtar Kelimeler: Fatigue strength improvement, TIG dressing, HFMI treatment, Data augmentation, Physics-informed machine learning, Variational Autoencoder, Bayesian analysis, Welded joints
  • Ankara Yıldırım Beyazıt Üniversitesi Adresli: Evet