Probabilistic neural network identification of an alloy for direct laser deposition

A neural network tool was used to discover a new nickel-base alloy for direct laser deposition most likely to satisfy targets of processability, cost, density, phase stability, creep resistance, oxidation, fatigue life, and resistance to thermal stresses. The neural network tool can learn property-p...

Full description

Bibliographic Details
Main Authors: B.D. Conduit, T. Illston, S. Baker, D. Vadegadde Duggappa, S. Harding, H.J. Stone, G.J. Conduit
Format: Article
Language:English
Published: Elsevier 2019-04-01
Series:Materials & Design
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127519300814
Description
Summary:A neural network tool was used to discover a new nickel-base alloy for direct laser deposition most likely to satisfy targets of processability, cost, density, phase stability, creep resistance, oxidation, fatigue life, and resistance to thermal stresses. The neural network tool can learn property-property relationships, which allows it to use a large database of thermal resistance measurements to guide the extrapolation of just ten data entries of alloy processability. The tool was used to propose a new alloy, and experimental testing confirms that the physical properties of the proposed alloy are better tailored to the target application than other available commercial alloys. Keywords: Nickel, Direct laser deposition, Alloy, Neural network
ISSN:0264-1275