کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
513871 866664 2012 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Blank optimization in a stamping process—Influence of the geometry definition
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Blank optimization in a stamping process—Influence of the geometry definition
چکیده انگلیسی

Nowadays initial geometry optimization methods are increasingly being adopted in order to solve complex mechanical plastic forming processes. This kind of approach can focus, in estimating the initial shape of a certain metallic specimen (or blank) in order to achieve a desired geometry after forming. In the present work the superplastic forming of a carter is described and studied in detail. After plastic forming it is possible to verify an undesirable non-homogeneous thickness distribution in the final geometry. A non-uniform thickness distribution of the initial blank can be proposed in order to obtain a regular final thickness of the sheet and avoid this problem. In the present paper the blank surface is modeled by means of a non-uniform rational B-spline (NURBS) surface, where the coordinates of specific NURBS control net vertices are chosen to be the optimization variables. The optimization procedure is carried out by combining a finite element (FE) software and a suitable optimization code. Four different studies were performed, differing in the number of control vertices that formulates the NURBS surface (16, 25, 36 and 49 control vertices were considered), in order to study the influence of the initial geometry definition. A geometry definition leading to better results is achieved, considering both computational cost and final result precision, and subsequent discussions are carried out.


► An optimization procedure to define the initial geometry of a sheet metal blank is presented.
► The goal is to produce a uniform thickness final part.
► The location of the NURBs control vertices that formulate the blank are the optimization variables.
► The influence of the number and the location of these variables on the optimization is studied.
► For the cases considered, the best results were achieved using 16 optimization variables.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Finite Elements in Analysis and Design - Volume 61, November 2012, Pages 75–84
نویسندگان
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