Details
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | 582739 |
| Fachzeitschrift | Advances in Materials Science and Engineering |
| Jahrgang | 2009 |
| Publikationsstatus | Veröffentlicht - 2009 |
Abstract
Quenching and tempering of precision forged components using their forging heat leads to reduced process energy and shortens the usual process chains. To design such a process, neither the isothermal transformation diagrams (TTT) nor the continuous cooling transformation (CCT) diagrams from literature can be used to predict microstructural transformations during quenching since the latter diagrams are significantly influenced by previous deformations and process-related high austenitising temperatures. For this reason, deformation CCT diagrams for several tempering steels from previous works have been investigated taking into consideration the process conditions of precision forging. Within the scope of the present work, these diagrams are used as input data for predicting microstructural transformations by means of artificial neural networks. Several artificial neural network structures have been examined using the commercial software MATLAB. Predictors have been established with satisfactory capabilities for predicting CCT diagrams for different degrees of deformation within the analyzed range of data.
ASJC Scopus Sachgebiete
- Werkstoffwissenschaften (insg.)
- Allgemeine Materialwissenschaften
- Ingenieurwesen (insg.)
- Allgemeiner Maschinenbau
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in: Advances in Materials Science and Engineering, Jahrgang 2009, 582739, 2009.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Prediction of continuous cooling diagrams for the precision forged tempering steel 50CrMo4 by means of artificial neural networks
AU - Nürnberger, Florian
AU - Schaper, Mirko
AU - Bach, Friedrich Wilhelm
AU - Mozgova, Iryna
AU - Kuznetsov, Kostjantyn
AU - Halikova, Anna
AU - Perederieieva, Olga
PY - 2009
Y1 - 2009
N2 - Quenching and tempering of precision forged components using their forging heat leads to reduced process energy and shortens the usual process chains. To design such a process, neither the isothermal transformation diagrams (TTT) nor the continuous cooling transformation (CCT) diagrams from literature can be used to predict microstructural transformations during quenching since the latter diagrams are significantly influenced by previous deformations and process-related high austenitising temperatures. For this reason, deformation CCT diagrams for several tempering steels from previous works have been investigated taking into consideration the process conditions of precision forging. Within the scope of the present work, these diagrams are used as input data for predicting microstructural transformations by means of artificial neural networks. Several artificial neural network structures have been examined using the commercial software MATLAB. Predictors have been established with satisfactory capabilities for predicting CCT diagrams for different degrees of deformation within the analyzed range of data.
AB - Quenching and tempering of precision forged components using their forging heat leads to reduced process energy and shortens the usual process chains. To design such a process, neither the isothermal transformation diagrams (TTT) nor the continuous cooling transformation (CCT) diagrams from literature can be used to predict microstructural transformations during quenching since the latter diagrams are significantly influenced by previous deformations and process-related high austenitising temperatures. For this reason, deformation CCT diagrams for several tempering steels from previous works have been investigated taking into consideration the process conditions of precision forging. Within the scope of the present work, these diagrams are used as input data for predicting microstructural transformations by means of artificial neural networks. Several artificial neural network structures have been examined using the commercial software MATLAB. Predictors have been established with satisfactory capabilities for predicting CCT diagrams for different degrees of deformation within the analyzed range of data.
UR - http://www.scopus.com/inward/record.url?scp=67650234480&partnerID=8YFLogxK
U2 - 10.1155/2009/582739
DO - 10.1155/2009/582739
M3 - Article
AN - SCOPUS:67650234480
VL - 2009
JO - Advances in Materials Science and Engineering
JF - Advances in Materials Science and Engineering
SN - 1687-8434
M1 - 582739
ER -