The role of mesoscopic deformation heterogeneities in plastic flow and recrystallization of a magnesium sheet alloy

Materialia ◽  
2020 ◽  
Vol 12 ◽  
pp. 100715 ◽  
Author(s):  
Risheng Pei ◽  
Sandra Korte-Kerzel ◽  
Talal Al-Samman
Author(s):  
Dinakar Sagapuram ◽  
Anirudh Udupa ◽  
Koushik Viswanathan ◽  
James B. Mann ◽  
Rachid M’Saoubi ◽  
...  

Abstract The mechanics of large-strain deformation in cutting of metals is discussed, primarily from viewpoint of recent developments in in situ analysis of plastic flow and microstructure characterization. It is shown that a broad range of deformation parameters can be accessed in chip formation—strains of 1–10, strain rates of 10–105/s, and temperatures up to 0.7Tm—and controlled. This range is far wider than achievable by any other single-stage, severe plastic deformation (SPD) process. The resulting extreme deformation conditions produce a rich variety of microstructures in the chip. Four principal types of chip formation—continuous, shear-localized, segmented, and mushroom-type—as elucidated first by Nakayama (1974, “The Formation of ‘Saw-Toothed Chip’ in Metal Cutting,” Proceedings of International Conference on Production Engineering, Tokyo, pp. 572–577) are utilized to emphasize the diverse plastic flow phenomena, especially unsteady deformation modes that prevail in cutting. These chip types are intimately connected with the underlying flow, each arising from a distinct mode and triggered by an instability phenomenon. The role of plastic flow instabilities such as shear banding, buckling, and fracture in mediating unsteady flow modes is expounded, along with consequences of the flow modes and chip types for the cutting. Sinuous flow is shown to be the reason why gummy (highly strain-hardening) metals, although relatively soft, are so difficult to cut. Synthesizing the various observations, a hypothesis is put forth that it is the stability of flow modes that determines the mechanics of cutting. This leads to a flow-stability phase diagram that could provide a framework for predicting chip types and process attributes.


2020 ◽  
Vol 150 ◽  
pp. 103257 ◽  
Author(s):  
Bjørn Håkon Frodal ◽  
Emil Christiansen ◽  
Ole Runar Myhr ◽  
Odd Sture Hopperstad

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