Steel Informatics aims to review the application of data-driven computing techniques related to the design of steel, including phase transformation, composition-process-property correlation, and different processing techniques, particularly deformation and joining. This book initiates with fundamentals of informatics followed by a description of applications of statistical analyses in defining the different attributes of steel. The proceeding chapters of this book cover recent applications of statistical, machine learning, expert systems, and optimization algorithms in the domains of iron and steel making, casting, deformation, phase transformation and heat treatment, microstructure analysis, and design of steel.
Features:
• Exclusive title focussing on informatics in steel design.
• Covers related statistics as well as artificial intelligence and machine learning aspects.
• Explains metallurgical aspects lucidly for the data scientists, steel researchers, and industries.
• Discusses all aspects of steel technology.
• Describes pertinent tools used for related computations.
This book is useful for researchers, professionals, and graduate students in metallurgy, materials science, steel and welding, and computational materials science.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Shubhabrata Datta is presently working as Research Professor in the Department of Mechanical Engineering, and Coordinator of the Centre for Composites and Advanced Materials at SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India. His research interests are in the domain of Materials Informatics, Alloy Design, Composites and Biomaterials.
Subhas Ganguly is an Associate Professor in the Department of Metallurgical and Materials Engineering, National Institute of Technology, Raipur, India. His research interests include Artificial Intelligence and Machine learning in Materials Engineering, Computational Optimization and Data Science for Metallurgical problems, Advance Steel and Alloy Design, Phase Transformation and Friction Stir Welding.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Steel Informatics aims to review the application of data-driven computing techniques related to thedesign of steel, including phase transformation, composition-process-property correlation, and different processing techniques, particularly deformation and joining. This book initiates with fundamentals of informatics followed by adescription of applications of statistical analyses in defining the different attributes of steel. The proceeding chapters of this book cover recent applications of statistical, machine learning, expert systems, and optimization algorithms in the domains of iron and steel making, casting, deformation, phase transformation and heat treatment, microstructure analysis, and design of steel.Features:- Exclusive title focussing on informatics in steel design.- Covers related statistics as well as artificial intelligence and machine learning aspects.- Explains metallurgical aspects lucidly for the data scientists, steel researchers, and industries.- Discusses all aspects of steel technology.- Describes pertinent tools used for related computations.This book is useful for researchers, professionals, and graduate students in metallurgy, materials science, steel and welding, and computational materials science. 220 pp. Englisch. N° de réf. du vendeur 9780367569235
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Shubhabrata Datta is presently working as Research Professor in the Department of Mechanical Engineering, and Coordinator of the Centre for Composites and Advanced Materials at SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, I. N° de réf. du vendeur 1581114458
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