Development of an automated property simulation tool for direct aged alloy 718 engine disk forgings

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Abstract

As the optimization of highly demanding engine parts like engine disks pushes the materials used to their limits, the estimation of the material properties becomes increasingly important. The complex interactions of strengthening mechanisms in direct aged (DA) Alloy 718 forgings demand detailed modeling of each mechanism. As some strengthening mechanisms are influenced during the billet processing it is essential to consider the forging stock manufacturing in the design process of forged engine disks. Therefore, a finite element analysis of the billet processing was incorporated in an existing simulation chain of the closed die forging process of engine disks. It includes all thermo-mechanical operations after vacuum arc remelting, i.e. homogenization, upsetting, drawing and radial forging of the billet as well as prepressing, forging and heat treatment of a disk. In order to implement the local variations of microstructure caused by the billet processing a newly developed grain class model was applied. Furthermore a duplex microstructure, which is often present in the surface region of the billet, was considered using the grain class model. For a sound precipitation modeling the local temperature history of the whole simulation chain was considered in the thermo-kinetic software tool MatCalc. After parameterization of the MatCalc model, parameters for the precipitation, solid solution and grain boundary contribution to the total yield strength was calculated. For the determination of the DA-effect a semi-empirical, deterministic model was developed. The established, automated simulation chain takes all mentioned mechanisms into account and calculates the local yield strength of the forged engine disk.

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Stockinger, M., Stanojevic, A., Wieser, V., & Raninger, P. (2018). Development of an automated property simulation tool for direct aged alloy 718 engine disk forgings. In Minerals, Metals and Materials Series (Vol. 2018-June, pp. 353–367). Springer International Publishing. https://doi.org/10.1007/978-3-319-89480-5_21

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