Dissolution of the Primary γ′ Precipitates and Grain Growth during Solution Treatment of Three Nickel Base Superalloys

Abstract

Second phase particles (SPP) play an essential role in controlling grain size and properties of polycrystalline nickel base superalloys. The understanding of the behavior of these precipitates is of prime importance in predicting microstructure evolutions. The dissolution kinetics of the primary γ′ precipitates during subsolvus solution treatments were investigated for three nickel base superalloys (René 65, AD730 and N19). A temperature-time codependency equation was established to describe the evolution of primary γ′ precipitates of each material using experimental data, the Thermo-Calc software and the Johnson–Mehl–Avrami–Kolmogorov (JMAK) model. The dissolution kinetics of precipitates was also simulated using the level-set (LS) method and the former phenomenological model. The precipitates are represented using an additional LS function and a numerical treatment around grain boundaries in the vicinity of the precipitates is applied to reproduce their pinning pressure correctly. Thus, considering the actual precipitate dissolution, these simulations aim to predict grain size evolution in the transient and stable states. Furthermore, it is illustrated how a population of Prior Particle Boundaries (PPB) particles can be considered in the numerical framework in order to reproduce the grain size evolution in the powder metallurgy N19 superalloy. The proposed full-field strategy is validated and the obtained results are in good agreement with experimental data regarding the precipitates and grain size.

Level-Set modeling of grain growth in 316L stainless steel under different assumptions regarding grain boundary properties

“…Figure 6 shows the evolution of RNb as a function of the annealing time. Using the methodology discussed in [76,77], one can obtain an average reduced mobility µγ using the Burke and Turnbull model [75]. This model, where topological and neighboring effects are neglected, is based on five main assumptions: the driving pressure is proportional to the mean curvature, grains are equixaed, the GB mobility and energy are isotropic, the annealing temperature is constant and no second phase particles are present in the material.…”

“…This methodology has been used in [76,78,79,80,77] assuming general grain boundaries with homogeneous GB energy and mobility. From the evolution of RNb in Figure 6 (excluding the Σ3 TBs), one can then obtain Level-Set modeling of grain growth in 316L stainless steel under different assumptions regarding grain boundary properties a first approximation of the product µγ for the general boundaries at 1050 • C. This approximation will be used for the µγ definition in isotropic simulations.…”

Level-Set Modeling of Grain Growth in 316L Stainless Steel under Different Assumptions Regarding Grain Boundary Properties

“…Figure 6 shows the evolution of as a function of the annealing time. Using the methodology discussed in [ 72 , 73 ], one can obtain an average reduced mobility using the Burke and Turnbull model [ 74 ]. This model, where topological and neighboring effects are neglected, is based on five main assumptions: the driving pressure is proportional to the mean curvature, grains are equixaed, the GB mobility and energy are isotropic, the annealing temperature is constant, and no second-phase particles are present in the material.…”

“…This methodology has been used in [ 72 , 73 , 75 , 76 , 77 ] assuming general grain boundaries with homogeneous GB energy and mobility. From the evolution of in Figure 6 (excluding the TBs), one can then obtain a first approximation of the product for the general boundaries at 1050 °C.…”

Towards Multi-Scale Modeling of Zirconium Alloys Recrystallization and Application to Thermo-Mechanical Processes Optimization

“…In this case, without stored energy due to dislocations, meaning in a fully recrystallized material, grains growth rate is only a function of the grain boundaries energy and mobility. Assuming a grain boundary energy of 0,22 J.m -2 from the bibliography [20], the mobility was identified by an iterative fitting of modeling compared to experimental results (see [21] for more details concerning this procedure). For this purpose, grain growth was characterized as a function of time and temperature for an alloy reproducing the behavior of zircaloy-4 without the presence of SPPs (Second Phase Particles), i.e.…”