Monitoring and control of microstructure evolution in metal processing is essential in developing the right properties in a metal. Microstructure evolution in metal forming processes summarises the wealth of recent research on the mechanisms, modelling and control of microstructure evolution during metal forming processes.
Part one reviews the general principles involved in understanding and controlling microstructure evolution in metal forming. Techniques for modelling microstructure and optimising processes are explored, along with recrystallisation, grain growth, and severe plastic deformation. Microstructure evolution in the processing of steel is the focus of part two, which reviews the modelling of phase transformations in steel, unified constitutive equations and work hardening in microalloyed steels. Part three examines microstructure evolution in the processing of other metals, including ageing behaviour in the processing of aluminium and microstructure control in processing nickel, titanium and other special alloys.
With its distinguished editors and international team of expert contributors, Microstructure evolution in metal forming processes is an invaluable reference tool for metal processors and those using steels and other metals, as well as an essential guide for academics and students involved in fundamental metal research.
Summarises the wealth of recent research on the mechanisms, modelling and control of microstructure evolution during metal forming processesComprehensively discusses microstructure evolution in the processing of steel and reviews the modelling of phase transformations in steel, unified constitutive equations and work hardening in microalloyed steelsExamines microstructure evolution in the processing of other materials, including ageing behaviour in the processing of aluminium

The objective of this publication is to comprehensively discuss the possibilities of producing steels with pre-determined attributes, demanded by the customer to fit exacting specifications. The information presented in the book has been designed to indicate the reasons for the expenses and to aid in the process of overcoming the difficulties and reducing the costs.

In nine detailed chapters, the authors cover topics including: steel as a major contributor to the economic wealth of a country in terms of its capabilities and production current concerns of major steel producers phenomena contributing to the quality of the product information concerning the boundary conditions of the rolling process and initial conditions, put to use by mathematical models the solid state incremental approach and flow formulation parameters and variables - most of which make use of the exponential nature of phenomena that are activated by thermal energy the application of three dimensional analysis to shape rolling the evaluation of parameters by a form of inverse analysis to the flat rolling process knowledge based modeling, using artificial intelligence, expert systems and neural networks

They conclude that when either mathematical or physical modeling of the rolling process is considered and the aim is to satisfy the demands for customers, it is possible to produce what the customer wants, exactly.
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Computational Materials Engineering: Achieving High Accuracy and Efficiency in Metals Processing Simulations describes the most common computer modeling and simulation techniques used in metals processing, from so-called "fast" models to more advanced multiscale models, also evaluating possible methods for improving computational accuracy and efficiency. Beginning with a discussion of conventional fast models like internal variable models for flow stress and microstructure evolution, the book moves on to advanced multiscale models, such as the CAFE method, which give insights into the phenomena occurring in materials in lower dimensional scales. The book then delves into the various methods that have been developed to deal with problems, including long computing times, lack of proof of the uniqueness of the solution, difficulties with convergence of numerical procedures, local minima in the objective function, and ill-posed problems. It then concludes with suggestions on how to improve accuracy and efficiency in computational materials modeling, and a best practices guide for selecting the best model for a particular application.