Abstract

Hot compression tests were performed on liquid-solid (L-S) bonded 304 stainless steel (SS)/Q235 carbon steel (CS) laminated composites, strain partitioning and microstructure evolution were analyzed, and an Arrhenius constitutive model and artificial neural network (ANN) model were established to describe the flow behavior. The mechanical incompatibilities of the SS and CS led to strain partitioning of the SS/CS laminated composite, and higher strain occurred in the CS. A dimensionless parameter dc was defined to evaluate the deformation coordination of SS/CS laminated composites, and smaller values of dc representing better coordinated deformation of the SS/CS laminated composite occurred at lower or higher Zener-Hollomon (Z) values. Flow stress curves presented a single peak and multiple peak types, indicating that dynamic recrystallization (DRX) occurred during the hot compression process. DRX obviously refined the grain size in both SS and CS during hot deformation, and the recrystallized grains in CS were much smaller than those in SS. However, DRX in the two materials was asynchronous, the strain partitioning, coarse grain and solute drag effect delayed the DRX of SS, and the volume fraction of recrystallized grains in SS decreased with increasing Z values. The relationship between the critical strain of DRX and peak strain satisfied εc=0.44εp, and the average activation energy of the SS/CS laminated composite approached the austenite lattice self-diffusion energy. The ANN model had better accuracy and stability for predicting the flow stress than the Arrhenius constitutive model, the correlation coefficient between the predicted and experimental values was 0.9963, and the average absolute relative error was only 2.96%.

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