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英文书籍《计算材料科学：材料组织及性能的模拟》
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Computational materials science : the simulation of materials microstructures and properties The recent advance of numerical prediction methods in nearly all domains of materials science and engineering has established a new, exciting, interdisciplinary approach which is often referred to as “computational materials science”. It brings together elements from materials science, physics, computer science, mathematics, chemistry, and mechanical engineering. For instance, simulations in the field of materials physics concentrate on the investigation of lattice and defect dynamics at the atomic scale using molecular dynamics and Monte Carlo methods. Materials-related simulations in the field of mechanical engineering focus on large-scale construction problems, using finite element methods where the microstructure is incorporated by using averaging constitutive laws. In contrast to these examples, the classical domain of materials science can be seen in the investigation of lattice defects and their interactions at the mesoscale. Performing simulations on this particular scale is a great challenge, in that it must bridge enormous space and time scales and provide concepts to describe adequately complex many-body interaction phenomena. For this purpose a variety of new concepts has been developed which enables one to handle the interaction of many individual lattice defects in a more or less discrete manner at dimensions above the atomic scale and below the macroscopic scale. These so-called mesoscale simulation methods include deterministic and probabilistic cellular automata with global and local transformation rules, Ginzburg–Landau-type phase field kinetic methods, dislocation dynamics, polycrystal and non-linear crystal plasticity finite element models, geometrical and component models, topological network or vertex models, and multistate kinetic Potts-type Monte Carlo approaches. However, classical techniques such as molecular dynamics, Metropolis Monte Carlo, and conventional finite element simulations are also used extensively. Although an increasing body of excellent conference proceedings, monographs, and journals are available covering particular aspects of computational materials science, no comprehensive overview of that field exists (see General Reading). This contribution aims to fill that gap. It gives a review of modern approaches to the space- and time-discretized simulation of materials microstructures, together with the respective theoretical backgrounds, that currently prevail in materials science. Particular emphasis is placed on the fundamentals of space- and time-discretized simulations of materials microstructures at the mesoscale. The book comprises five Parts. Part I is entitled Introduction and Fundamentals. After the Introduction it concentrates on aspects which are scale-independent, namely, definitions and notions used in modeling and simulation, and fundamentals of solving differential equations. The sequence of the ensuing Parts reflects the spatial and temporal hierarchy of microstructure, i.e., it presents simulation methods at the nanoscopic–microscopic (Part II), microscopic–mesoscopic (Part III), and mesoscopic–macroscopic levels (Part IV). The last chapter provides a review of integrated, i.e., of scale-bridging, modeling and simulation (Part V). Part II (on the nano–micro level) focuses on the various Metropolis Monte Carlo and molecular dynamics approaches. Part III (on the micro– meso level) concentrates on dislocation dynamics, Ginzburg–Landau-type diffuse phase field kinetic methods, cellular automata, multistate and kinetic Potts models, geometrical and component models, and topological network and vertex models. Part IV (on the meso–macro level) presents large-scale finite element and finite difference and polycrystal models. The chapters are complemented by a discussion of typical applications in the field of materials science and representative examples. Due to the fact that it is particularly those simulations that predict microstructure evolution and microstructure–property relations at the micro–mesoscale, the theoretical concepts and methods in Part III are discussed in greater detail and furnished with elementary examples from plasticity, recrystallization and grain growth phenomena, solid-state diffusion, and phase transformation. The Appendices present a list of suggested general reading, some basic aspects of computer science, advanced empirical techniques such as fuzzy logic and artificial neuronal networks, and a brief introduction to percolation theory. The book addresses students at the graduate and undergraduate levels, lecturers, materials scientists and engineers, as well as materials-oriented physicists, chemists, mathematicians, and mechanical engineers. Any offer of criticism, advice, or example that might help to improve this text will be highly appreciated. This book was written during my time at the Institut f¨ur Metallkunde und Metallphysik at Rheinisch-Westf¨alische Technische Hochschule Aachen and at the Department of Materials Science and Engineering at Carnegie Mellon University in Pittsburgh. My warmest thanks are due to my mentors Prof. Dr. G. Gottstein and Prof. Dr. Dr. h.c. K. L¨ucke, who have steadily promoted and profoundly stimulated my work. I am particularly indebted to Prof. Dr. H. Mughrabi, Prof. Dr. D. J. Srolovitz, Dr. U. F. Kocks, and Prof. Dr. A. D. Rollett for discussions and a number of helpful comments. Furthermore, I am grateful to Prof. Dr. D. M. Barnett, Prof. Dr. M. Berveiller, Prof. Dr. W. Blum, Prof. Dr. Y. Br′echet, Prof. Dr. U. Glatzel, Dr. P. Gumbsch, Prof. Dr. J. P. Hirth, Prof. Dr. P. Neumann, Prof. Dr. W. Mao, Prof. Dr. H. Mecking, Dr. D. R¨onnpagel, the late Prof. Dr. J. Schlipf, Prof. Dr. S. Schmauder, Prof. Dr. L. Shvindlerman, Prof. Dr. Z. Sun, Prof. Dr. L. T′oth, and Prof. Dr. P. van Houtte for stimulating discussions and fruitful comments. |
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