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Development of advanced techniques f...

Cho, Hyunjoong.

Development of advanced techniques for identification of flow stress and friction parameters for metal forming analysis.

紀錄類型:	書目-電子資源 : 單行本
正題名/作者:	Development of advanced techniques for identification of flow stress and friction parameters for metal forming analysis./
作者:	Cho, Hyunjoong.
面頁冊數:	218 p.
附註:	Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6656.
Contained By:	Dissertation Abstracts International67-11B.
標題:	Engineering, Industrial. -
電子資源:	Download PDF (下載PDF全文)
ISBN:	9780542966125

Development of advanced techniques for identification of flow stress and friction parameters for metal forming analysis.
Cho, Hyunjoong.

Development of advanced techniques for identification of flow stress and friction parameters for metal forming analysis. - 218 p.

Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6656.

Thesis (Ph.D.)--The Ohio State University, 2007.

The accuracy of process simulation in metal forming by finite element method depends on the accuracy of flow stress data and friction value that are input to FEM programs. Therefore, it is essential that these input values are determined using reliable tests and evaluation methods. This study presents the development of inverse analysis methodology and its application to determine flow stress data of bulk and sheet materials at room and elevated temperatures. The inverse problem is defined as the minimization of the differences between the experimental measurements and the corresponding FEM predictions. Rigid-viscoplastic FEM is used to analyze the metal flow while a numerical optimization algorithm adjusts the material parameters used in the simulation until the calculated response matches the measured data within a specified tolerance.

ISBN: 9780542966125Subjects--Topical Terms:

170926
Engineering, Industrial.

Development of advanced techniques for identification of flow stress and friction parameters for metal forming analysis.
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245 1 0 $a Development of advanced techniques for identification of flow stress and friction parameters for metal forming analysis.
300 $a 218 p.
500 $a Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6656.
500 $a Adviser: Taylan Altan.
502 $a Thesis (Ph.D.)--The Ohio State University, 2007.
520 $a The accuracy of process simulation in metal forming by finite element method depends on the accuracy of flow stress data and friction value that are input to FEM programs. Therefore, it is essential that these input values are determined using reliable tests and evaluation methods. This study presents the development of inverse analysis methodology and its application to determine flow stress data of bulk and sheet materials at room and elevated temperatures. The inverse problem is defined as the minimization of the differences between the experimental measurements and the corresponding FEM predictions. Rigid-viscoplastic FEM is used to analyze the metal flow while a numerical optimization algorithm adjusts the material parameters used in the simulation until the calculated response matches the measured data within a specified tolerance.
520 $a The use of the developed inverse analysis methodology has been demonstrated by applying it to the selected reference rheological tests; cylinder compression test, ring compression test, instrumented indentation test, modified limiting dome height test, and sheet hydraulic bulge test. Furthermore, using the determined material property data, full 3-D finite element simulation models, as examples of industrial applications for orbital forming and thermoforming processes have been developed for reliable process simulation.
520 $a As results of this study, it was shown that the developed inverse analysis methodology could identify both the material parameters and friction factors from one set of tests, simultaneously. Therefore, this technique can offer a systematic and cost effective way for determining material property data for simulation of metal forming processes.
590 $a School code: 0168.
650 4 $a Engineering, Industrial. $3 170926
650 4 $a Engineering, Mechanical. $3 170925
650 4 $a Engineering, Materials Science. $3 1000005553
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710 2 $a The Ohio State University. $3 170954
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