Neural Network Modelling of Track Profile in Cold Spray Additive Manufacturing.

ABSTRACT: Cold spray additive manufacturing is an emerging technology that offers the ability to deposit oxygen-sensitive materials and to manufacture large components in the solid state. For further development of the technology, the geometric control of cold sprayed components is fundamental but not yet fully matured. This study presents a neural network predictive modelling of a single-track profile in cold spray additive manufacturing to address the problem. In contrast to previous studies focusing only on key geometric feature predictions, the neural network model was employed to demonstrate its capability of predicting complete track profiles at both normal and off-normal spray angles, resulting in a mean absolute error of 8.3%. We also compared the track profile modelling results against the

SUBMITTER: Ikeuchi D 

PROVIDER: S-EPMC6747964 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature