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Construction of aluminum alloy constitutive model based on BP neural network and the study of non-isothermal hydroforming

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Abstract

With the continuous development of high-end technology in aerospace and automotive, the materials used are lightweight and strong to meet the needs of high performance, high precision, and lightweight of parts; however, they are too difficult to deform, which means that it is difficult to obtain high-quality and high-precision parts. In order to improve the forming quality and precision of parts, taking Aluminum Alloy 6061-T6l cylindrical cup with spherical bottom as the research object, the non-isothermal hydroforming process is studied by combining numerical simulation with experiment. The key of numerical simulation technology lies in the accuracy of simulation, which depends on the establishment of a suitable rheological stress relationship. For this reason, a constitutive model that can truly reflect the thermoforming characteristics of Aluminum Alloy 6061-T6l materials is established through a uniaxial tensile test and BP neural network. Applying the constitutive model to the study of numerical simulation of non-isothermal hydroforming, the cylindrical cup with spherical bottom with high quality is obtained through the optimization of non-isothermal process parameters. After experimental verification, the results of numerical simulation are highly compatible with the actual forming results of parts, and have high reliability.


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