Understanding the Dynamics of Ultrasonic Additive Manufacturing

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Mao, Qing
Coutris, Nicole
Gibert, James
Fadel, Georges

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University of Texas at Austin


Ultrasonic Additive Manufacturing (UAM) is an additive manufacturing technique that uses ultrasound to merge metal foils (150 µm thick, 24 mm wide) layer by layer to fabricate three-dimensional bodies. As new layers are deposited and the height-to-width ratio of the built feature changes, the dynamics of UAM changes accordingly. Prior research suggested the existence of a limit for the height-to-width ratio. Above this limit, additional layers fail to bond because the built feature reaches its resonance frequency. Specifically, the bond failure is affected by the lack of plastic shear deformation between two foils which is essential to the generation of true metallic bonds. As the height-to-width ratio falls in the critical range, the built feature becomes resonant under the high-frequency excitations (20 kHz) of the sonotrode, leading to large-amplitude oscillations matching those of the sonotrode, and resulting in reduction of differential motion and therefore plastic shear deformation between the foils. In order to develop a model incorporating plasticity, heat transfer, and friction to study UAM, 2-D and 3-D lump parameter models consisting of mass-spring networks are proposed to study the dynamics of the elastic part of the built feature. The models are established such that they preserve the modal parameters of the built feature in free vibration. The lumped parameter models are validated by comparing their modal predictions with those from 2-D and 3-D finite element models. The lumped parameter model will be coupled with a 3-D finite element model to describe an elasto-plastic bonding layer introducing the friction and thermal aspects of UAM. By examining the deformation of the bonding layer under the combined effects of the excitation of the sonotrode and the vibration of the built feature, the bond failure due to geometry change of the built feature will be better understood and quantified in the future.


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