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Artificial Neural Network Modeling of ECAP Process
- Source :
- Materials and Manufacturing Processes. 28:276-281
- Publication Year :
- 2013
- Publisher :
- Informa UK Limited, 2013.
-
Abstract
- Equal channel angular pressing (ECAP) is a type of severe plastic deformation procedure for achieving ultra-fine grain structures. This article investigates artificial neural network (ANN) modeling of ECAP process based on experimental and three-dimensional (3D) finite element methods (FEM).In order to do so, an ECAP die was designed and manufactured with the channel angle of 90° and the outer corner angle of 15°. Commercial pure aluminum was ECAPed and the obtained data was used for validating the FEM model. After confirming the validity of the model with experimental data, a number of parameters are considered. These include the die channel angles (angle between the channels Φ and the outer corner angle Ψ) and the number of passes which were subsequently used for training the ANN. Finally, experimental and numerical data was used to train neural networks. As a result, it is shown that a feed forward back propagation ANN can be used for efficient die design and process determination in the ECAP. There is...
- Subjects :
- Pressing
Materials science
business.product_category
Artificial neural network
business.industry
Mechanical Engineering
Process (computing)
Experimental data
Mechanical engineering
Structural engineering
Industrial and Manufacturing Engineering
Finite element method
Mechanics of Materials
Die (manufacturing)
General Materials Science
Severe plastic deformation
business
Communication channel
Subjects
Details
- ISSN :
- 15322475 and 10426914
- Volume :
- 28
- Database :
- OpenAIRE
- Journal :
- Materials and Manufacturing Processes
- Accession number :
- edsair.doi...........e122c3abf662cf6cf25df1c2715545c4
- Full Text :
- https://doi.org/10.1080/10426914.2012.667889