Secondary effects in neural network analysis of the mechanical properties of welding alloys for HSLA shipbuilding steels

E. A. Metzbower, J. J. DeLoach, S. H. Lalam and H. K. D. H. Bhadeshia

Abstract

In previous work, we created neural network models for estimating the mechanical properties and toughness of alloys that are designed for the welding of high-strength low-alloy steels of the type intended for the construction of ships. The yield and ultimate strengths, the elongation and reduction-in-area, the Charpy toughness and dynamic tear properties were usefully modelled as a function of the chemical composition and the cooling rate. Ductility and toughness are complex properties; the purpose of the work presented here was to see if they could be modelled better by including the strength as an input.

Mathematical Modelling of Weld Phenomena 6, eds H. Cerjak and H. K. D. H. Bhadeshia, published by Maney, London, 2002. pp. 231-242

Download PDF file of paper.

Download text.

Download presentation.

Welding Metallurgy


PT Group Home Materials Algorithms Any Valid CSS!