Temat: deep drawing - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Numerical analysis of the deep drawing process including the history of stress and strain
Autorzy:: Kaldunski, P.
Powiązania:: https://bibliotekanauki.pl/articles/280806.pdf
Data publikacji:: 2018
Wydawca:: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:: deep drawing
modeling
numerical analysis
FEM
stress history
strain history
Opis:: This paper discusses the results of a numerical study of circular cup drawing of steel sheets using ﬁnite element method. The drawing process is considered as a geometrical and physical nonlinear problem with unknown boundary conditions in the contact area of the system, such as the tool and the workpiece. The updated Lagrangian description is used to characterize these nonlinear phenomena on a typical incremental step time. Numerical results are obtained using an explicit method in Ansys/Ls-Dyna program. The constitutive Cowper-Symonds material model with linear hardening strain to predict material plasticity is used. The results of implementation of stresses and strains from a blanking operation ﬂat disc of a sheet of metal for deep-drawing process are presented. After the blanking process simulation, an implicit springback analysis is performed. Then a numerical analysis of cup forming from this ﬂat disc plate was carried out. The analysis results are compared with one another through reading of the sheet thickness in several characteristic points and the overall height of the product.
Źródło:: Journal of Theoretical and Applied Mechanics; 2018, 56, 3; 781-792
1429-2955
Pojawia się w:: Journal of Theoretical and Applied Mechanics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Experimental and numerical investigation of the deep drawing process for an automobile panel and prediction of appropriate amount of parameters by multi-layer neural network
Autorzy:: Najafabadi, S. S.
Anaraki, A. T.
Moradi, M.
Powiązania:: https://bibliotekanauki.pl/articles/281868.pdf
Data publikacji:: 2017
Wydawca:: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:: deep drawing
finite element analysis (FEA)
multi-layer artificial neural network (ANN)
Taguchi design
Opis:: In this paper, the deep drawing process of an automobile panel in order to select the appropriate amount of parameters has been investigated. The parameters include friction between the blank and die, blank width and length, blank thickness and gap between the blank and blank-holder. A multi-layer artificial neural network (ANN) trained by finite element analyses (FEA) is applied in order to improve forming parameters and achieve a better quality. As the FEA results are used to train the ANN, the FEA results have been verified by three experiments. Finally, an appropriate amount of each parameter is predicted by the trained ANN and a FEA has been done based on the ANN prediction to evaluate the accuracy of the trained ANN. Moreover, it is shown that the ANN could predict results within a 10 percent error. In addition, the proposed method for prediction of the appropriate parameters (ANN) is confirmed by comparing with the Taguchi design of experiment prediction. It is also shown that the model obtained by the former method has lower errors than the latter one. In this study, the Taguchi model is used to evaluate the effect of parameters on tearing and wrinkling. Based on the Taguchi design of experiment, while the blank length is the most effective parameter on tearing, the maximum height of wrinkles on flanged parts mainly depends on the blank thickness.
Źródło:: Journal of Theoretical and Applied Mechanics; 2017, 55, 2; 707-718
1429-2955
Pojawia się w:: Journal of Theoretical and Applied Mechanics
Dostawca treści:: Biblioteka Nauki

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