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GOALI: Constituitive Modeling for Polycrystalline Aluminum Alloy Extrusions and Application to Hydroforming of Thin-Walled Tubes

$239,738FY2000ENGNSF

Michigan State University, East Lansing MI

Investigators

Abstract

In these Grant Opportunities for Academic Liaison with Industry (GOALI) project, the investigators will jointly develop and use polycrystalline and phenomenological constitutive models for hydroforming process simulations of aluminum alloy thin-walled extrusions. The predictive capability of the phenomenological models will be fine-tuned and validated with a combination of polycrystalline modeling results and experiments. Hydroforming of thin-walled hollow extrusions has become popular with automotive and materials industries for making complex structural components, such as instrument panel beam and engine cradle. The main advantage of tube hydroforming, in comparison with conventional stamping, is the potential to replace an assembly of parts by only one component. This leads to a reduction of the number of welding operations and to substantial gains in manufacturing costs. Components manufactured from aluminum alloy tubes would translate into significant weight saving for the structure as well. In order to optimize the conditions for a given hydroforming operation, numerical simulations of the process are carried out. However, realistic predictions can be achieved only with accurate mathematical descriptions of the material behavior (constitutive models), specifically for aluminum alloy tubes. To date, most of the hydroformed parts are made with steel and very little research has been performed on hydroforming of aluminum alloy tubes. The ultimate goal of the project is to develop the most accurate phenomenological equations and a set of guidelines to provide, within the constraints existing in industrial environments, the best possible material description for hydroforming of aluminum alloy thin-walled extrusions. This should accelerate the proliferation of hydroformed parts for these materials.

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