Aspects of high strain rate industrial forging of Inconel 718

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

The major part of all material and microstructural data used for the modelling of nickel superalloy forgings is obtained from uniaxial laboratory tests with limited plastic strain and very simple thermo-mechanical history. At the same time, new challenges in near net shape industrial forging require a high level of reliability of modelling prediction of metal flow, for predicting the risk of defects and microstructural transformation. A few recently conducted benchmarking studies have shown that despite the availability of various material models (including microstructural ones) embedded in commercial FE software, in many cases, the level of prediction remains unsatisfactory. This is especially true for fast industrial forging processes (like screw press or hammer forgings). This paper suggests a methodology for processing the results from industrial forgings for obtaining robust data for calibration, validation, and improvement of material and microstructural models. This also can provide additional information on the material science behind the microstructural phenomena, which are problematic to capture and study using simple uniaxial tests.
Original languageEnglish
Title of host publicationSuperalloys 2020
EditorsSammy Tin, Mark Hardy, Justin Clews, Jonathan Cormier, Qiang Feng, John Marcin, Chris O'Brien, Akane Suzuki
Place of PublicationCham, Switzerland
PublisherSpringer
Pages461 - 470
Number of pages10
ISBN (Electronic)978-3-030-51834-9
ISBN (Print)978-3-030-51833-2
DOIs
Publication statusE-pub ahead of print - 29 Aug 2020

Publication series

NameThe Minerals, Metals & Materials Series
PublisherSpringer
ISSN (Print)2367-1181

Keywords

  • Inconel 718
  • high strain rate
  • metal flow
  • microstructure evolution
  • FEM

Fingerprint Dive into the research topics of 'Aspects of high strain rate industrial forging of Inconel 718'. Together they form a unique fingerprint.

Cite this