Low-cycle fatigue characterization and texture induced ratcheting behaviour of forged AZ80 Mg alloys

Abstract Stress-controlled uniaxial “push-pull” fatigue testing was conducted on as-received (cast and extruded) and closed-die cast-forged and extruded-forged AZ80 Mg alloy. The as-cast material possessed random texture and somewhat symmetric cyclic responses. The extruded and forged materials possessed sharp basal texture and asymmetric cyclic responses. All materials exhibited tension/compression asymmetry in their cyclic response to varying degrees, depending on the thermomechanical processing conditions. It was discovered that the style of closed-die forging being investigated had spatially varying properties with texture orientations which varied based on the local forging directions and intensities which were dependent on the starting texture as well as the thermomechanical history. Under fatigue testing, the materials all developed some form of mean strain, with the nature and magnitude of this mean strain being dependent on primarily its texture intensity and propensity to twin in either tension or compression reversals. The type of mean strain (tensile or compressive) depends upon both the orientation and intensity of the starting texture of material. The texture induced ratcheting and resulting mean strain evolution was most pronounced in the as-cast material and had a significant impact on the fatigue life. Following forging, the material exhibited an increase in fatigue life of anywhere from 2 to 15 times for the cast then forged material and more modest yet still significant 8 times longer at stress amplitudes around 140 MPa for the extruded then forged material. The extruded forged material exhibited similar fatigue lives to that of the base material at stress amplitudes which approached the yield strength. The nature of the mean stress development and degree of fatigue life improvement depended on the processing conditions and the type of base material (cast or extruded) utilized to create the forging. Two energy based models were utilized to predict the life of the forged material, and gave a reliable life prediction for a variety of material conditions that were investigated.