Recrystallization and Work-Hardening Prediction During Forging Process of Inconel 718

Abstract

The numerical simulation of forging process allows to know the temperature and strain evolution in every point of the part. The metallurgical models are able to account of these evolutions in order to predict the grain size everywhere in the work piece. The aim of the present study is to predict the recrystallized fraction in various processes (hot die forging, ring rolling, or hammering). The recrystallized fraction is strongly dependent on the stored energy (work-hardening or dislocation density) contained in the material. As a matter of fact a predictive recrystallized fraction model based on dislocation density is developed. It predicts successfully the recrystallized fraction on small samples and parts. The dislocation density is connected with the broadening of (400) X-ray line profile. The line profile broadening measurement is related to the conventional 0.2% yield stress. The correlation between predicted and measured work-hardening will be done in a following work, which will enable to link the microstructure to mechanical properties and then to predict the yield stress within a numerical simulation of the forging process.

718 Superalloy Forging Simulation: A Way to Improve Process and Material Potentialities

“…The models are mainly based on the description of microstructural and metallurgical evolutions [3] on one hand and on mechanical or thermo-mechanical strengthening laws on the other hand. If the mechanical and thermal algorithms have been used for long, the implemented metallurgical laws are more difficult to establish and have to be fitted to a large number of experimental data, describing a wide range of process conditions.…”

Simulating microstructural evolution during the hot working of alloy 718

“…To this end, Jaramillo et al 21 employed a numerical model for the recrystallization rate of alloy 718, based on the critical intrinsic variables and the measured activation energy for recrystallization in a finite-element model, to predict evolved microstructure in hot-rolled plate. Marty et al 22 proposed a different numerical model for the recrystallization rate in alloy 718 based on evolving dislocation density as modified by the various mechanisms of recovery. Of particular interest, the model was used to predict the progression of the volume fraction recrystallized in a multiple-stroke compression test, and the predictions compared well with actual test results.…”

Modelling Microstructural Transformations of Nickel Base Superalloy in 718 During Hot Deformation

“…When a new grainset is added, the dislocation density is set to 1 × 10 12 m −2 , a value identified by Marty et al [7] as being the lowest dislocation density observed in polycrystals.…”

“…The value of K has been calculated to be approximately 6·6 × 10 14 , calculated using Equation 3, where ρ c , the critical dislocation density for the onset of recrystallisation is 1×10 14 m −2 [18]; ρ unrx , the dislocation density of a newly recrystallised grain, is 1×10 12 m −2 [7], and ε crit is the observed critical strain (approximately 0·15 in the case of IN 718 [19]). The value of K is, therefore, fitted to experimental data such that, excluding recovery processes and assuming that the original structure has a uniform dislocation density equal to ρ unrx , dynamic recrystallisation would begin at the assumed critical strain of 0·15.…”

“…[1][2][3][4][5][6][7][8][9][10][11][12]), they either fall into the category of being too simplistic and producing only an average grain size and approximate volume fraction recrystallised, or are far too complicated and too computationaly intensive to be used on a daily basis by process engineers. A model is required, therefore, that can be run within a commercially available finite element package, or in tandem with one, that will deliver detailed results, run in a reasonable time, and be simple to use.…”