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Pregled bibliografske jedinice broj: 328133

Časopis

Autori: Lela, Branimir; Duplančić, Igor; Bajić, Dražen
Naslov: Parametric and nonparametric modelling of earing and hardness of deep drawn cups
Izvornik: Materials Science and Technology (0267-0836) 25 (2009), 8; 969-975
Vrsta rada: članak
Ključne riječi: Deep drawing; Neural networks; AA8011A; Earing; Hardness
Sažetak:
This study compares different approaches in modelling the earing phenomenon and hardness of cups in deep drawing process. The blank holder force (BHF), annealing temperature (AT) and annealing time (ANT) of blanks prior to deep drawing process have been chosen as the three influential parameters on the earing and hardness. In order to obtain mathematical models for the earing and hardness of the deep drawn cups, the methodology of artificial neural networks (ANNs) have been used. Bayesian network (BN), radial basis function network (RBFN), Gaussian processes (GP) and multilayer perceptron (MLP) are four different ANN approaches that have been used for the modelling. The research has been conducted on a cold-rolled Al-Fe-Si (AA8011A) aluminium sheet. After obtaining the mathematical models describing the influence of BHF and annealing on hardness and earing, a comparison of the proposed models has been performed. A search for the optimal parameters of deep drawing process has been carried out too.
Projekt / tema: 023-0692976-1742, 023-0231926-1748
Izvorni jezik: ENG
Rad je indeksiran u
bazama podataka:
Current Contents Connect (CCC)
Scopus
SCI-EXP, SSCI i/ili A&HCI
Science Citation Index Expanded (SCI-EXP) (sastavni dio Web of Science Core Collectiona)
Kategorija: Znanstveni
Znanstvena područja:
Strojarstvo
URL cjelovitog teksta:
Google Scholar: Parametric and nonparametric modelling of earing and hardness of deep drawn cups
Upisao u CROSBI: Dražen Bajić (), 8. Tra. 2008. u 14:26 sati



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