Fast Predictive Model of Crystallographic Texture Evolution in Metal Additive Manufacturing

This communication introduces a fast material- and process-agnostic modeling approach, not reported in the open literature, that is calibrated for predicting evolution of texture metal additive manufacturing stainless steel 304L as function process parameter, namely laser scanning speed. The outputs model are compared against independent validation experiments same material system show excellent consistency. also predicts trend change intensity parameter. major novelty strength this work model’s speed extremely light computational load. calibrations predictions were carried out 9.2 s on typical desktop computer.