Autor:

Bouzaffour, Mohamed ; Nassraoui, Mohammed

Współtwórca:

Jurczak, Paweł - red.

Tytuł:

Springback prediction of sheet metal hydroforming using finite element analysis and artificial neural networks

Tytuł publikacji grupowej:

IJAME, volume 30 (2025)

Temat i słowa kluczowe:

springback ; hydroforming ; artificial neural networks ; machine learning ; finite element simulation

Abstract:

The objective of this paper is to develop a method for the rapid estimating springback in the hydroforming process of circular sheets. First, the springback behavior has been studied with using finite element simulations for various configurations such as sheet thickness, sheet diameter, and deformation pressure. The results obtained shows an excellent correlation with the experimental data. ; Next, the springback of circular sheets in the setting of hydroforming has been predicted using the artificial neural networks (ANN) approach. Statistical measures, specifically the mean square error (MSE) and the coefficient (R2) are implemented for evaluating this approach. The results reveal that artificial neural networks provide an accurate, high-performance model for predicting the springback of circular sheets.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2025

Typ zasobu:

artykuł

Format:

application/pdf

DOI:

10.59441/ijame/205461

Strony:

42-56

Źródło:

IJAME, volume 30, number 3 (2025)

Jezyk:

eng

Licencja:

CC 4.0

Licencja CC BY-NC-ND 4.0:

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Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego