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| Reference : Parameter identification and shape/process optimization in metal forming simulation |
| Scientific journals : Article | |||
| Engineering, computing & technology : Mechanical engineering Engineering, computing & technology : Materials science & engineering Physical, chemical, mathematical & earth Sciences : Physics | |||
| http://hdl.handle.net/2268/3170 | |||
| Parameter identification and shape/process optimization in metal forming simulation | |
| English | |
| Kleinermann, J. P. [Université de Liège - ULG > > >Département d'aérospatiale et mécanique > LTAS-Mécanique numérique non linéaire > >] | |
Ponthot, Jean-Philippe  [Université de Liège - ULg > Département d'aérospatiale et mécanique > LTAS-Mécanique numérique non linéaire >] | |
| 20-Aug-2003 | |
| Journal of Materials Processing Technology | |
| Elsevier Science | |
| 139 | |
| 1-3 | |
| 521-526 | |
| International | |
| 0924-0136 | |
| Lausanne | |
| Switzerland | |
| [en] finite element ; large deformation ; inverse problems ; parameter identification ; forming processes optimization ; optimization methods | |
| [en] Nowadays, computer simulations of metal forming processes using the finite element method (FEM) have reached some level of maturity. The purpose of inverse problems is to determine the simulation input data for one or more of these forming processes, leading to a desired result. The first example is called parameter identification. This consists in evaluating the material parameters for material behavior laws that would lead to the most accurate model, minimizing the difference between experimental results and the corresponding FEM simulation. The second example is initial geometry and tool shape design, consisting in determining the initial shape of the specimen and/or the shape of the forming tools, in order to provide the desired final geometry after the forming process. Both inverse problem examples can be formulated as optimization problems. In this paper, the authors propose to solve these optimization problems with different non-linear optimization methods and to compare their efficiency. (C) 2003 Elsevier Science B.V. All rights reserved. | |
| Researchers ; Professionals ; Students | |
| http://hdl.handle.net/2268/3170 | |
| 10.1016/S0924-0136(03)00530-2 |
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