Estimation of the .GAMMA. and .GAMMA.' Lattice Parameters in Nickel-base Superalloys Using Neural Network Analysis.

• Yoshitake S.

  Department of Materials Science and Metallurgy, University of Cambridge

• Narayan V.

  Department of Materials Science and Metallurgy, University of Cambridge

• Harada H.

  National Research Institute for Metals

• Bhadeshia H. K. D. H.

  Mathematical and Physical Sciences Group, Darwin College

• Mackay D. J. C.

  Mathematical and Physical Sciences Group, Darwin College

Bibliographic Information

Other Title

• Estimation of the γ and γ’ lattice parameters in nickel-based superalloys using neural network analysis

Abstract

The lattice constants of the γ and γ' phases of nickel base superalloys have been modelled using a neural network within a Bayesian framework. The analysis is based on datasets compiled from new experiments and the published literature, the parameters being expressed as a non-linear function of some eighteen variables which include the chemical composition and temperature. The analysis permits the estimation of error bars whose magnitude depends on their position in the input space. Of the many models possible, a "committee of models" is found to give the most reliable estimate. The method is demonstrated to be consistent with known metallurgical trends and has been applied towards the study of some experimental alloys.

Journal

• ISIJ International

  ISIJ International 38 (5), 495-502, 1998

  The Iron and Steel Institute of Japan

Keywords

• neural networks
• nickel
• lattice constant

Details

• CRID: 1390282681428692352
• NII Article ID: 10002459549
• NII Book ID: AA10680712
• DOI: 10.2355/isijinternational.38.495
• ISSN: 13475460
• ISSN: 09151559
• Web Site: http://www.jstage.jst.go.jp/article/isijinternational1989/38/5/38_5_495/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed