2007
DOI: 10.1016/j.jmmm.2006.11.217
|View full text |Cite
|
Sign up to set email alerts
|

Low silicon non-grain-oriented electrical steel: Linking magnetic properties with metallurgical factors

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
19
0
2

Year Published

2009
2009
2024
2024

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 41 publications
(23 citation statements)
references
References 14 publications
0
19
0
2
Order By: Relevance
“…However, even the present data set, extensive they might be, appears inadequate in building such a model: through regression and/or brute numerical methods (such as artificial neural network or ANN. 65) Efforts of future research will indeed be focused in such direction: success, as in any applied research, can never be guaranteed. Hence the authors felt that the research community, in general, needs to be briefed about the interesting constitutive relationships between the degradation in magnetic properties with strain hardening exponent and different aspects of quantifiable microstructural changes.…”
Section: Discussionmentioning
confidence: 99%
“…However, even the present data set, extensive they might be, appears inadequate in building such a model: through regression and/or brute numerical methods (such as artificial neural network or ANN. 65) Efforts of future research will indeed be focused in such direction: success, as in any applied research, can never be guaranteed. Hence the authors felt that the research community, in general, needs to be briefed about the interesting constitutive relationships between the degradation in magnetic properties with strain hardening exponent and different aspects of quantifiable microstructural changes.…”
Section: Discussionmentioning
confidence: 99%
“…In the latter case, it was observed from a large number of commercial samples, that there were significant variations in magnetic permeability and power loss in spite of the fact that only the silicon concentration varied (0?04-0?52 wt-%) between the samples, all of which had insignificant inclusion contents. 16 The variations were imagined to be due to microstructure, so a neural network model was created with grain size, crystallographic texture and silicon as inputs. The necessary data were measured deliberately for the purposes of neural network modelling.…”
Section: Category 2 Examplementioning
confidence: 99%
“…Therefore, depending on the steel grade and its application, the amount of Si + Al can vary from low [24] to high concentrations [25].…”
Section: Introductionmentioning
confidence: 99%