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A computational study on the three-dimensional printability of precipitate-strengthened nickel-based superalloys.

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posted on 2020-04-15, 10:37 authored by HC Basoalto, C Panwisawas, Y Sovani, MJ Anderson, RP Turner, B Saunders, JW Brooks
This paper presents a computational framework to study the differences in process-induced microvoid and precipitate distributions during selective laser melting (SLM) of two nickel-based superalloys representative of low (IN718) and high (CM247LC) volume fraction precipitate-strengthened alloys. Simulations indicate that CM247LC has a higher propensity to form process-induced microvoids than IN718. Particle sintering is predicted to be strongly influenced by the powder size distribution. For deposition thickness of approximately 40 μm, thermal gradients during cooling are predicted to be larger for CM247LC than IN718 and consequently expect the development of larger residual stresses for a high volume fraction γ' alloy. A coupled mean field/finite-element approach has been used to predict the precipitate distributions across a simple rectangular build and during a subsequent hot isostatic pressing (HIP) cycle. Unimodal and multi-modal particle distributions are predicted for IN718 and CM247LC at the end of the SLM, respectively. A higher volume fraction of γ' is predicted for CM247LC at the end of the SLM process. During HIP, simulations indicate a dramatic increase in the γ' volume fraction in CM247LC, which can result in a reduction in stress relaxation and lead to a ductility drop.

Funding

The authors thank the Aerospace Technology Institute (ATI) for funding this work through the Manufacturing Portfolio programme (project no. 113084).

History

Citation

Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (2018) 474:2220 20180295

Version

  • AM (Accepted Manuscript)

Published in

Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences

Volume

474

Issue

2220

Pagination

20180295

Publisher

The Royal Society

issn

1364-5021

eissn

1471-2946

Acceptance date

2018-11-16

Copyright date

2018

Available date

2018-12-19

Publisher version

https://royalsocietypublishing.org/doi/full/10.1098/rspa.2018.0295

Notes

The computations described in this paper were performed using the University of Birmingham's BlueBEAR HPC service, which provides a High Performance Computing service to the University's research community. See http://www.birmingham.ac.uk/bear for more details.

Language

eng

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