Plastics blow molding has grown rapidly for the past couple of decades. Annular parison extrusion is a critical stage in extrusion blow molding. In this work, numerical simulations on the parison extrusion were performed using finite element (FE) method and the Kaye-Bernstein-Kearsley-Zapas type constitutive equation. A total of 100 simulations was carried out by changing the extrusion die inclination angle, die gap, and parison length. Then a backpropagation artificial neural network (ANN) was proposed as a tool for modeling the parison extrusion using the numerical simulation results. The network architecture determination and the training process of the ANN model were discussed. The predictive ability of the ANN model was examined through several sets of FE simulation results different from those utilized in the training stage. The effects of the die inclination angle, die gap, and parison length on the parison swells can be predicted using the ANN model. The results showed that the die gap has a smaller effect on the diameter swell but a greater effect on the thickness swell. Both diameter and thickness swells increase as the die inclination angle increases. The hybrid method combining the FE and ANN can shorten the time for the predictions drastically and help search out the processing conditions and/or die geometric parameters to obtain optimal parison thickness distributions.
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e-mail: mmhuang@scut.edu.cn
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February 2007
Technical Papers
Finite Element and Neural Network Modeling of Viscoelastic Annular Extrusion
Han-Xiong Huang,
Han-Xiong Huang
Professor
Center for Polymer Processing Equipment and Intellectualization, College of Industrial Equipment and Control Engineering,
e-mail: mmhuang@scut.edu.cn
South China University of Technology
, Guangzhou, P.R.C.
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Yan-Sheng Miao
Yan-Sheng Miao
Center for Polymer Processing Equipment and Intellectualization, College of Industrial Equipment and Control Engineering,
South China University of Technology
, Guangzhou, P.R.C.
Search for other works by this author on:
Han-Xiong Huang
Professor
Center for Polymer Processing Equipment and Intellectualization, College of Industrial Equipment and Control Engineering,
South China University of Technology
, Guangzhou, P.R.C.e-mail: mmhuang@scut.edu.cn
Yan-Sheng Miao
Center for Polymer Processing Equipment and Intellectualization, College of Industrial Equipment and Control Engineering,
South China University of Technology
, Guangzhou, P.R.C.J. Fluids Eng. Feb 2007, 129(2): 218-225 (8 pages)
Published Online: July 25, 2006
Article history
Received:
September 6, 2005
Revised:
July 25, 2006
Citation
Huang, H., and Miao, Y. (July 25, 2006). "Finite Element and Neural Network Modeling of Viscoelastic Annular Extrusion." ASME. J. Fluids Eng. February 2007; 129(2): 218–225. https://doi.org/10.1115/1.2409357
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