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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.

Secondary-phase particles are routinely dispersed in metals and ceramics to prevent grain growth and take full advantage of the small grain size in the mechanical properties of polycrystals. Somewhat surprisingly, the preferential or abnormal growth of a few grains is observed in particle-containing systems at relatively high temperature, which will limit the lifetime of the material. The origins and mechanisms of particle-assisted abnormal grain growth are widely contested. Here, we employ integrated three-dimensional X-ray imaging to throw new light on the complex interactions between grain boundaries and particles in an Al–Cu alloy as a model system. We observe abnormal grain growth in the presence of a highly non-random distribution of particles. The incipient grain size is set by the local distribution of particles such that the larger grains come from particle-poor regions. Subsequently, grains with a size advantage may "run away" from the grain size distribution, in agreement with predictions from an analytical model that takes into account the competing capillary and particle pinning pressures. Image, graphical abstract [ABSTRACT FROM AUTHOR]

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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, A D 730 and N 19 ). A temperature-time codependency equation was established to describe the evolution of primary γ ′ precipitates of each material using experimental data, the T h e r m o - C a l c 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. [ABSTRACT FROM AUTHOR]

Mechanical and functional properties of Oxide Dispersion Strengthened (ODS) ferritic/martensitic steels are strongly related to their microstructures. Thus, numerical modeling of microstructure evolution during ODS forming is of prime importance. In this work, two well-known full field methodologies dedicated to recrystallization modeling, the level-set and the Monte Carlo methods, are applied, discussed and compared to experimental data in their ability to describe properly recrystallization for ODS steels. [ABSTRACT FROM AUTHOR]