TY - JOUR
T1 - Process–structure–property relationships in bimodal machined microstructures using robust structure descriptors
AU - Fernandez-Zelaia, Patxi
AU - Melkote, Shreyes N.
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/11
Y1 - 2019/11
N2 - Machining is a severe plastic deformation process that subjects materials to high rates of deformation and elevated temperatures. Dynamic recrystallization during severe plastic deformation drives grain refinement into the sub-micron range but the ductility and thermal stability of these structures is poor. In contrast, bimodal microstructures consisting of both fine and coarse grains have been shown to exhibit attractive strength and ductility properties at these temperatures. In this paper, we study the process–structure–property relationships for pure copper subject to a machining process where the cutting speeds are varied. Further, we investigate the role of thermal effects by varying the post-deformation cooling rates. Microstructures generated under these deformation conditions are quantified using angularly resolved chord length statistics. The derived metrics are found to be robust descriptors of the studied microstructures as they automatically capture complex features such as unimodal and bimodal distributions of grain structure, grain constituent length scales, and morphological anisotropy induced by shear deformation. The uniaxial equivalent yield strength of the generated structures are estimated using spherical nanoindentation and inverse modeling techniques. Finally, we present a methodology for identifying the constrained property-process inverse mapping for machining using a Bayesian framework and the established forward process–structure–property mapping.
AB - Machining is a severe plastic deformation process that subjects materials to high rates of deformation and elevated temperatures. Dynamic recrystallization during severe plastic deformation drives grain refinement into the sub-micron range but the ductility and thermal stability of these structures is poor. In contrast, bimodal microstructures consisting of both fine and coarse grains have been shown to exhibit attractive strength and ductility properties at these temperatures. In this paper, we study the process–structure–property relationships for pure copper subject to a machining process where the cutting speeds are varied. Further, we investigate the role of thermal effects by varying the post-deformation cooling rates. Microstructures generated under these deformation conditions are quantified using angularly resolved chord length statistics. The derived metrics are found to be robust descriptors of the studied microstructures as they automatically capture complex features such as unimodal and bimodal distributions of grain structure, grain constituent length scales, and morphological anisotropy induced by shear deformation. The uniaxial equivalent yield strength of the generated structures are estimated using spherical nanoindentation and inverse modeling techniques. Finally, we present a methodology for identifying the constrained property-process inverse mapping for machining using a Bayesian framework and the established forward process–structure–property mapping.
KW - Machining
KW - Materials informatics
KW - Microstructure characterization
KW - Microstructure evolution
KW - Nanoindentation
KW - Severe plastic deformation
UR - http://www.scopus.com/inward/record.url?scp=85067284794&partnerID=8YFLogxK
U2 - 10.1016/j.jmatprotec.2019.116251
DO - 10.1016/j.jmatprotec.2019.116251
M3 - Article
AN - SCOPUS:85067284794
SN - 0924-0136
VL - 273
JO - Journal of Materials Processing Technology
JF - Journal of Materials Processing Technology
M1 - 116251
ER -