Prediction of Yoshida Uemori model parameters by the bees algorithm and Genetic Algorithm for 5xxx series aluminium alloys
Küçük Resim Yok
Tarih
2021
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In sheet metal forming processes, springback is a very important issue in the view of the excellent quality design. Several mathematical models have been developed to estimate the springback more accurately, including various material parameters. In this study, the model parameters of Yoshida-Uemori two surface plasticity model, which can well predict the springback for different loading conditions, have been determined using The Bees Algorithm and Genetic Algorithm which are frequently used recently for optimization of nonlinear problems. In addition, the performances of the algorithms have been determined for the different frequency of experimental data, dense-sparse, sparse-dense, dense-dense and sparse-sparse for elastic and plastic regions. According to the results, although the determined material parameters have different values, the fitting performances are found similar for both The Bees Algorithm and Genetic Algorithm. However, in the view of the data frequency, the more appropriate results are obtained from the dense-dense data set (Case 3).
Açıklama
Anahtar Kelimeler
Malzeme Bilimleri, Özellik ve Test, Metalürji Mühendisliği
Kaynak
Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi
WoS Q Değeri
Scopus Q Değeri
Cilt
10
Sayı
2
