4.7 Article

Application of a multi-component mean field model to the coarsening behaviour of a nickel-based superalloy

期刊

ACTA MATERIALIA
卷 114, 期 -, 页码 80-96

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.actamat.2016.05.024

关键词

nickel based superalloy; IN738LC; Particle coarsening; Mean field theory; Multi-components systems

资金

  1. RWE Npower
  2. Rolls-Royce plc
  3. EPSRC [EP/M005607/1, EP/H500367/1] Funding Source: UKRI
  4. Engineering and Physical Sciences Research Council [EP/M005607/1, EP/H500367/1] Funding Source: researchfish

向作者/读者索取更多资源

A multi-component mean field model has been applied to predict the particle evolution of the gamma' particles in the nickel based superalloy IN738LC, capturing the transition from an initial multimodal particle distribution towards a unimodal distribution. Experiments have been performed to measure the coarsening behaviour during isothermal heat treatments using quantitative analysis of micrographs. The three dimensional size of the gamma' particles has been approximated for use in simulation. A coupled thermodynamic/mean field modelling framework is presented and applied to describe the particle size evolution. A robust numerical implementation of the model is detailed that makes use of surrogate models to capture the thermodynamics. Different descriptions of the particle growth rate of non-dilute particle systems have been explored. A numerical investigation of the influence of scatter in chemical composition upon the particle size distribution evolution has been carried out. It is shown how the tolerance in chemical composition of a given alloy can impact particle coarsening behaviour. Such predictive capability is of interest in understanding variation in component performance and the refinement of chemical composition tolerances. It has been found that the inclusion of misfit strain within the current model formulation does not have a significant affect upon predicted long term particle coarsening behaviour. Model predictions show good agreement with experimental data. In particular, the model predicts a reduced growth rate of the mean particle size during the transition from bimodal to unimodal distributions. (C) 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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