Journal of Materials Research and Technology (May 2022)
Flow behavior and strain rate sensitivity assessment of γ and γʹ phases in Co–Al–W-based superalloy using experimental and computational approaches
Abstract
The recently developed precipitation-hardened cobalt-based superalloys can be considered as a new category of elevated temperature materials. An attempt was made in this research to estimate the elastoplastic characteristics of γ and γʹ phases embedded in Co–Al–W superalloy by using nanoindentation data and constitutive equations. The elastic modulus and hardness were initially utilized to determine the yield stress, which will be subsequently used to characterize the flow behavior in the plastic region. The proposed computational model has been verified with quantitative and semi-quantitative results, calculated by finite element analysis (FEA). It was perceived that both γ and γʹ phases in the investigated superalloy exhibited the ductile load-bearing response as γʹ strengthening phase displayed higher yield stress compared to the γ matrix. The work hardening rate and work hardening exponent were also identified to be higher for γʹ rather than γ phase due to the presence of an anti-phase boundary, which consequently promotes the strain hardening mechanism. The load–displacement curves in both phases illustrated pop-ins which marks the transition from elastic to plastic deformation. Finally, the elastic and plastic data of both constituent phases were incorporated into the FEA paradigm to simulate the indentation projected area. Based on the indentation morphology, the FEA simulation results were further validated with experimental nano-mechanical data. The results revealed that the load–displacement curve acquired from the numerical simulation of the Berkovich indenter has an excellent agreement with the obtained nanoindentation test. The primary purpose of this research is to recognize the correlation between the strain-rate sensitivity of the hardness and the flow stress using FEA results integrated with the analytical modeling.