Stainless Steel Weld Metal
Author : C. N. MacCowan
Publisher :
Page : 36 pages
File Size : 24,10 MB
Release : 1989
Category :
ISBN : 9781581453416
Author : C. N. MacCowan
Publisher :
Page : 36 pages
File Size : 24,10 MB
Release : 1989
Category :
ISBN : 9781581453416
Author : Damian J. Kotecki
Publisher :
Page : 95 pages
File Size : 45,89 MB
Release : 2007-02-01
Category :
ISBN : 9781581455267
Author : E. W. Pickering
Publisher :
Page : 98 pages
File Size : 40,7 MB
Release : 1986-09-01
Category :
ISBN : 9781581453171
Author : Welding Research Council (U.S.)
Publisher :
Page : 70 pages
File Size : 29,25 MB
Release : 1995
Category : Welding
ISBN :
Author : E. W. Pickering
Publisher :
Page : 98 pages
File Size : 20,60 MB
Release : 1986
Category :
ISBN :
Author : Mrs. J. Honeycombe
Publisher :
Page : pages
File Size : 24,91 MB
Release : 1985
Category : Electric welding
ISBN :
Author : Norman Bailey
Publisher : Elsevier
Page : 299 pages
File Size : 28,42 MB
Release : 1994-05-31
Category : Technology & Engineering
ISBN : 1845698932
This book is chiefly concerned with the conventional fusion welding processes and their problems and will be of value to practical welding engineers, inspectors and metallurgists. The author also has inmind the needs of those concerned with design and specification, recognising the importance of dealing with problems at the design stage.
Author : W. L. Fleischmann
Publisher :
Page : 74 pages
File Size : 46,62 MB
Release : 1953
Category : Ferrite
ISBN :
Author :
Publisher :
Page : 6 pages
File Size : 38,65 MB
Release : 1998
Category :
ISBN :
Predicting the ferrite content in stainless steel welds is desirable in order to assess an alloy's susceptibility to hot cracking and to estimate the as-welding properties. Several methods have been used over the years to estimate the ferrite content as a function of the alloy composition. A new technique is described which uses a neural network analysis to determine the ferrite number. The network was trained on the same data set that was used to generate the WRC-1992 constitution diagram. The accuracy of the neural network predictions is compared to that for the WRC-1992 diagram as well as another recently proposed method. It was found that the neural network model was approximately 20% more accurate than either of the other two methods. In addition, it is suggested that further improvements to the neural network model, including the consideration of process variables, can be made which lead to even better accuracy.
Author : Daniel Frank Spond
Publisher :
Page : 157 pages
File Size : 29,61 MB
Release : 1975
Category :
ISBN :