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Study on high-temperature oxidation kinetics of Haynes 282 and Inconel 718 nickel-based superalloys

  • R. N. NnajiEmail author
  • M. A. Bodude
  • L. O. Osoba
  • O. S. I. Fayomi
  • F. E. Ochulor
ORIGINAL ARTICLE

Abstract

High-temperature oxidation studies on nickel-based superalloys have reportedly used weight change measurements to assess the overall oxidation kinetics. In this study, oxidation experiments were conducted under laboratory air from 0 to 10 h at 1050 and 1100 °C in the furnace to investigate the oxidation kinetics of Haynes 282 and Inconel 718 nickel-based superalloys. As observed, Haynes 282 superalloy displayed a linear/quasi-parabolic oxidation behaviour at both test temperatures with (n = 0.65) at 1050 °C and (n = 0.68) at 1100 °C. Notably, the best-fit for Inconel 718 superalloy at 1050 °C after 10 h’ exposure was found to be non-linear and closer to parabolic and/or cubic oxidation behaviour with n = 0.37. However, the best-fit for this same alloy at 1100 °C was observed to be linear/quasi-parabolic with (n = 0.61) after 10 h’ exposure. The morphology and elemental compositions of the surface oxides formed after the oxidation experiments were assessed by scanning electron microscopy (SEM) and X-ray energy dispersive spectroscopy (EDS). Inconel 718 superalloy displayed a relatively slow oxidation kinetics over Haynes 282 at the 1050 °C test temperature under the same experimental conditions. Response surface methodology (RSM) was used to analyse the experimental data and generate regression models for predicting specific weight change in Haynes 282 and Inconel 718 superalloys. ANOVA was used to evaluate the fitness and adequacy of each selected 2FI model. The models’ predictive power was validated based on the close agreement (over 99% R2 values) between the predicted and actual mean specific weight change.

Keywords

Haynes 282 Inconel 718 Nickel-based superalloys Oxidation kinetics Response surface 

Abbreviations

ANOVA

analysis of variance

RSM

response surface methodology

CV

coefficient of variation

CL

confidence level

SD

standard deviation

Notes

Acknowledgments

The authors are grateful to Prof. A. O. Ojo of the Department of Mechanical and Production Engineering, University of Manitoba, Canada, for the provision of test materials to support this study. Special thanks to the Management and staff of MIDWAL ENGINEERING (Metallurgical Engineers and Testing Laboratory), Lekki, Lagos, Nigeria for their technical assistance.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • R. N. Nnaji
    • 1
    Email author
  • M. A. Bodude
    • 1
  • L. O. Osoba
    • 1
  • O. S. I. Fayomi
    • 2
    • 3
  • F. E. Ochulor
    • 1
  1. 1.Department of Metallurgical and Materials EngineeringUniversity of LagosLagosNigeria
  2. 2.Department of Mechanical EngineeringCovenant UniversityOtaNigeria
  3. 3.Department of Chemical, Metallurgical and Materials EngineeringTshwane University of TechnologyPretoriaSouth Africa

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