Fatigue limit prediction and analysis of nano-structured AISI 304 steel by severe shot peening via ANN
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
AISI 304 stainless steel is very widely used for industrial applications due to its good integrated performance and corrosion resistance. However, shot peening (SP) is known as one of the effectual surface treatments processes to provide superior properties in metallic materials. In the present study, a comprehensive study on SP of AISI 304 steel including 42 different SP treatments with a wide range of Almen intensities of 14-36 A and various coverage of 100-2000% was carried out. Varieties of experiments were accomplished for the investigation of the microstructure, grain size, surface topography, hardness and residual stresses as well as axial fatigue behavior. After experimental investigations, artificial neural networks modeling was carried out for parametric analysis and optimization. The results indicated that, treated specimens with higher severity had more desirable properties and performances.
Açıklama
Anahtar Kelimeler
AISI 304 stainless steel, Shot peening, Fatigue limit, Artificial neural networks, Optimization
Kaynak
Engineering With Computers
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
37
Sayı
4
