Modeling the Flow Behavior of Wire Arc Additive Manufactured Steel Over a Wide Range of Strain Rates and Temperatures

Abstract

Compared to traditional manufacturing processes, the layer-by-layer deposition process of wire arc additive manufacturing brings significant differences in microstructure, resulting in distinct deformation behaviors. This study focuses on developing an appropriate constitutive model to characterize the flow behavior of wire arc additive manufactured (WAAMed) steel. To analyze the deformation behavior of WAAMed steel, the hot compression tests at the temperature range of 850 °C–1150 °C and strain rate range of 0.01–10 s⁻¹ were conducted by Gleeble thermomechanical simulator. The strain-compensated Arrhenius model and modified Johnson–Cook model have been proposed to predict the flow stress under different temperatures and strain rates, as well as the genetic algorithm-back propagation method (GA-BP). The prediction capability of these models has been compared with experimental data using various statistical measures. It can be concluded that all three constitutive models are capable of accurately predicting the flow stress of WAAMed steel. The predictive capability and stability of back propagation artificial neural network were significantly improved by incorporating a genetic algorithm. Compared to the other models, GA-BP model demonstrates the highest accuracy and stability, achieving a relative coefficient of 0.99669 and an average absolute relative error of 3.39 pct.