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OPTIMAL DESIGN FOR NON‐STEADY‐STATE METAL FORMING PROCESSES—II. APPLICATION OF SHAPE OPTIMIZATION IN FORGING
Author(s) -
FOURMENT L.,
BALAN T.,
CHENOT J. L.
Publication year - 1996
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/(sici)1097-0207(19960115)39:1<51::aid-nme845>3.0.co;2-#
Subject(s) - forging , steady state (chemistry) , metal forming , mechanical engineering , shape optimization , finite element method , optimal design , engineering , engineering drawing , structural engineering , materials science , computer science , chemistry , machine learning
This paper is the second part of a two‐part article about shape optimization of metal forming processes. This part is focused on numerical applications of the optimization method which has been described in the first paper. The main feature of this work is the analytical calculations of the derivatives of the objective function for a non‐linear, non‐steady‐state problem with large deformations. The calculations are based on the differentiation of the discrete objective function and on the differentiation of the discrete equations of the forging problem. Our aim here is to show the feasibility and the efficiency of such a method with numerical examples. We recall the formulation and the resolution of the direct problem of hot axisymmetrical forging. Then, a first type of shape optimization problem is considered: the optimization of the shape of the initial part for a one‐step forging operation. Two academic problems allow for checking the accuracy of the analytical derivatives, and for studying the convergence rate of the optimization procedure. Both constrained and unconstrained problems are considered. Afterwards, a second type of inverse problem of design is considered: the shape optimization of the preforming tool, for a two‐step forging process. A satisfactory shape is obtained after few iterations of the optimization procedure.