This textbook describes the content of optimizing and predicting the parameters that influence the cold crack formation in the High Strength Low Alloy Steel 950A. High strength low alloy steel (HSLA) has been in use in workshops since the 1980s. Cold cracking is a common problem associated with welding of HSLA steels. It is thus becoming mandatory to have a novel method of welding to minimize the effects of cold cracking in such steels. The objective of the thesis is to improve the cold cracking resistance of HSLA 950A using the process gas Metal Arc Welding (GMAW). The parameters influencing the cold cracking of HSLA steel are preheating temperature oxide particles content and heat input. These parameters are optimized to achieve high resistance to cold cracking technique using Taguchi and Response surface methodology. The response in this study is taken impact strength. For effectively predict the response using the given input parameters, Artificial Neural Networks (ANN) is used. A three-layer feed-forward back propagation algorithm is used in Ann. Gray Relation Analysis (GRA) technique has been used to perform multi objective optimization.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. N° de réf. du vendeur 26400929664
Quantité disponible : 4 disponible(s)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand. N° de réf. du vendeur 395447391
Quantité disponible : 4 disponible(s)
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This textbook describes the content of optimizing and predicting the parameters that influence the cold crack formation in the High Strength Low Alloy Steel 950A. High strength low alloy steel (HSLA) has been in use in workshops since the 1980s. Cold cracking is a common problem associated with welding of HSLA steels. It is thus becoming mandatory to have a novel method of welding to minimize the effects of cold cracking in such steels. The objective of the thesis is to improve the cold cracking resistance of HSLA 950A using the process gas Metal Arc Welding (GMAW). The parameters influencing the cold cracking of HSLA steel are preheating temperature oxide particles content and heat input. These parameters are optimized to achieve high resistance to cold cracking technique using Taguchi and Response surface methodology. The response in this study is taken impact strength. For effectively predict the response using the given input parameters, Artificial Neural Networks (ANN) is used. A three-layer feed-forward back propagation algorithm is used in Ann. Gray Relation Analysis (GRA) technique has been used to perform multi objective optimization. 116 pp. Englisch. N° de réf. du vendeur 9786203857252
Quantité disponible : 2 disponible(s)
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Etat : New. PRINT ON DEMAND. N° de réf. du vendeur 18400929674
Quantité disponible : 4 disponible(s)
Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Muralidaran V. ManivelDr. V. Manivelmuralidaran completed a Ph.D from Anna University, Chennai, Tamilnadu, India in the field of manufacturing under the guidance of Dr.K. Senthilkumar in February 2020. He is working as an Assistant P. N° de réf. du vendeur 478262442
Quantité disponible : Plus de 20 disponibles
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This textbook describes the content of optimizing and predicting the parameters that influence the cold crack formation in the High Strength Low Alloy Steel 950A. High strength low alloy steel (HSLA) has been in use in workshops since the 1980s. Cold cracking is a common problem associated with welding of HSLA steels. It is thus becoming mandatory to have a novel method of welding to minimize the effects of cold cracking in such steels. The objective of the thesis is to improve the cold cracking resistance of HSLA 950A using the process gas Metal Arc Welding (GMAW). The parameters influencing the cold cracking of HSLA steel are preheating temperature oxide particles content and heat input. These parameters are optimized to achieve high resistance to cold cracking technique using Taguchi and Response surface methodology. The response in this study is taken impact strength. For effectively predict the response using the given input parameters, Artificial Neural Networks (ANN) is used. A three-layer feed-forward back propagation algorithm is used in Ann. Gray Relation Analysis (GRA) technique has been used to perform multi objective optimization.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 116 pp. Englisch. N° de réf. du vendeur 9786203857252
Quantité disponible : 1 disponible(s)
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This textbook describes the content of optimizing and predicting the parameters that influence the cold crack formation in the High Strength Low Alloy Steel 950A. High strength low alloy steel (HSLA) has been in use in workshops since the 1980s. Cold cracking is a common problem associated with welding of HSLA steels. It is thus becoming mandatory to have a novel method of welding to minimize the effects of cold cracking in such steels. The objective of the thesis is to improve the cold cracking resistance of HSLA 950A using the process gas Metal Arc Welding (GMAW). The parameters influencing the cold cracking of HSLA steel are preheating temperature oxide particles content and heat input. These parameters are optimized to achieve high resistance to cold cracking technique using Taguchi and Response surface methodology. The response in this study is taken impact strength. For effectively predict the response using the given input parameters, Artificial Neural Networks (ANN) is used. A three-layer feed-forward back propagation algorithm is used in Ann. Gray Relation Analysis (GRA) technique has been used to perform multi objective optimization. N° de réf. du vendeur 9786203857252
Quantité disponible : 1 disponible(s)