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

Access this Article

Search this Article



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.


  • Transactions of the Iron and Steel Institute of Japan  

    Transactions of the Iron and Steel Institute of Japan 38(5), 495-502, 1998-05-15 

    The Iron and Steel Institute of Japan

References:  21

You must have a user ID to see the references.If you already have a user ID, please click "Login" to access the info.New users can click "Sign Up" to register for an user ID.


Page Top