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150508 ||| eng |
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|a 9783319182421
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| 100 |
1 |
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|a Conti, Sergio
|e [editor]
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| 245 |
0 |
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|a Analysis and Computation of Microstructure in Finite Plasticity
|h Elektronische Ressource
|c edited by Sergio Conti, Klaus Hackl
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| 250 |
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|a 1st ed. 2015
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2015, 2015
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| 300 |
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|a XII, 257 p. 78 illus
|b online resource
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| 505 |
0 |
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|a From the Contents: Numerical algorithms for the simulation of finite plasticity with microstructures -- Analytical and numerical aspects of relaxation and regularization in models of crystal plasticity -- Modeling and computation of time-continuous evolution of - Hybrid micro-macro modeling of evolving microstructures in finite plasticity
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| 653 |
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|a Mechanics, Applied
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| 653 |
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|a Computational Mathematics and Numerical Analysis
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| 653 |
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|a Mathematics / Data processing
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| 653 |
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|a Solids
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| 653 |
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|a Solid Mechanics
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| 653 |
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|a Materials / Analysis
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| 653 |
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|a Characterization and Analytical Technique
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| 700 |
1 |
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|a Hackl, Klaus
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Lecture Notes in Applied and Computational Mechanics
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| 028 |
5 |
0 |
|a 10.1007/978-3-319-18242-1
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-319-18242-1?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 620.105
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| 520 |
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|a This book addresses the need for a fundamental understanding of the physical origin, the mathematical behavior, and the numerical treatment of models which include microstructure. Leading scientists present their efforts involving mathematical analysis, numerical analysis, computational mechanics, material modelling and experiment. The mathematical analyses are based on methods from the calculus of variations, while in the numerical implementation global optimization algorithms play a central role. The modeling covers all length scales, from the atomic structure up to macroscopic samples. The development of the models ware guided by experiments on single and polycrystals, and results will be checked against experimental data
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