Modelling of forming limit diagram of perforated commercial pure aluminium sheets using artificial neural network

2010 ◽  
Vol 47 (4) ◽  
pp. 1072-1078 ◽  
Author(s):  
K. Elangovan ◽  
C. Sathiya Narayanan ◽  
R. Narayanasamy
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Forming Limit Diagram ◽  
Forming Limit ◽  
Pure Aluminium ◽  
Artificial Neural ◽  
Aluminium Sheets

scholarly journals Prediction of Forming Limit Diagram for AA5754 Using Artificial Neural Network Modelling

2016 ◽  
Vol 716 ◽  
pp. 770-778 ◽  
Author(s):  
Mohamed Mohamed ◽  
Sherif Elatriby ◽  
Zhusheng Shi ◽  
Jian Guo Lin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Forming Limit Diagram ◽  
Forming Limit ◽  
Network Modelling ◽  
Forming Condition ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Artificial Neural Network Modelling ◽  
Good Agreement

Warm stamping techniques have been employed to solve the formability problem in forming aluminium alloy panels. The formability of sheet metal is a crucial measure of its ability for forming complex-shaped panel components and is often evaluated by forming limit diagram (FLD). Although the forming limit is a simple tool to predict the formability of material, determining FLD experimentally at warm/hot forming condition is quite difficult. This paper presents the artificial neural network (ANN) modelling of the process based on experimental results (different temperature, 20°C-300°C and different forming rates, 5-300 mm.s-1) is introduced to predict FLDs. It is shown that the ANN can predict the FLDs at extreme conditions, which are out of the defined boundaries for training the ANN. According to comparisons, there is a good agreement between experimental and neural network results

Prediction of Limiting Strains for Square Pattern – Square Hole Perforated Commercial Pure Aluminium Sheets

2012 ◽  
Vol 548 ◽  
pp. 382-386 ◽  
Author(s):  
G. Venkatachalam ◽  
S. Narayanan ◽  
Narayanan C. Sathiya
Keyword(s):  
Sheet Metal ◽  
Forming Limit Diagram ◽  
Forming Limit ◽  
Pure Aluminium ◽  
Element Analysis ◽  
Material Condition ◽  
Geometrical Features ◽  
Perforated Sheet ◽  
Commercial Aluminium ◽  
Aluminium Sheets

Forming limit diagram (FLD) is the most appropriate tool used to obtain the safe strain region in sheet metal forming industries. This FLD is based on limiting values of major and minor strains. This Limiting strain is the strain at the onset of fracture / necking in a sheet metal. It is influenced by the material / condition of the material, strain condition in geometrical features of a sheet metal. In this paper, square pattern – square holed, perforated commercial aluminium sheets are considered for the study. The limiting strain for the above perforated sheet metals is predicted using finite element analysis. It is found that the limiting strain is controlled by percentage of open area, ligament ratio and hole size.

Autofluorescence spectroscopy of oral leukoplakia using an artificial neural network

2000 ◽  
Vol 25 (4) ◽  
pp. 325-325
Author(s):  
J.L.N. Roodenburg ◽  
H.J. Van Staveren ◽  
N.L.P. Van Veen ◽  
O.C. Speelman ◽  
J.M. Nauta ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Oral Leukoplakia ◽  
Autofluorescence Spectroscopy ◽  
Artificial Neural

1902: Is Steinstrasse After ESWL of Renal Stones Predictable? Artificial Neural Network Analysis

2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Analysis ◽  
Renal Stones ◽  
Neural Network Analysis ◽  
Artificial Neural Network Analysis ◽  
Artificial Neural

Forecasting travel demand: a comparison of logit and artificial neural network methods

1998 ◽  
Vol 49 (7) ◽  
pp. 717-722 ◽  
Author(s):  
M C M de Carvalho ◽  
M S Dougherty ◽  
A S Fowkes ◽  
M R Wardman
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Travel Demand ◽  
Network Methods ◽  
Artificial Neural
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