Journal article
A new framework for computationally efficient structure-structure evolution linkages to facilitate high-fidelity scale bridging in multi-scale materials models
Acta materialia, v 59(2), pp 699-707
01 Jan 2011
Abstract
A novel mathematical framework called materials knowledge systems (MKS) was recently formulated to extract, store and recall computationally efficient hierarchical linkages that are at the core of multi-scale modeling of materials phenomena. A salient feature of this new framework is that it facilitates flow of high-fidelity information in both directions between the constituent length scales, and thereby offers a new strategy for concurrent multi-scale modeling. The viability of this new framework has thus far been largely explored for capturing the mechanical response of composite material systems. This paper extends the MKS framework to applications involving microstructure evolution, where the local states are typically defined in a continuous local state space. In particular, it will be shown that it is possible to obtain an efficient discretization of the local state space to produce a sufficiently accurate description of the linearized structure structure evolution linkages for modeling spinodal decomposition. Furthermore, it will be shown that these linkages can be used successfully to accurately predict the continuous evolution of microstructure over the long time periods involved in such problems. (C) 2010 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
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Details
- Title
- A new framework for computationally efficient structure-structure evolution linkages to facilitate high-fidelity scale bridging in multi-scale materials models
- Creators
- Tony Fast - Drexel Univ, Dept Mat Engn, Philadelphia, PA 19104 USAStephen R. Niezgoda - Drexel UniversitySurya R. Kalidindi - Drexel University
- Publication Details
- Acta materialia, v 59(2), pp 699-707
- Publisher
- Elsevier
- Number of pages
- 9
- Grant note
- N000140510504 / DARPA-ONR; United States Department of Defense; Defense Advanced Research Projects Agency (DARPA); Office of Naval Research
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Materials Science and Engineering
- Web of Science ID
- WOS:000285486300030
- Scopus ID
- 2-s2.0-78449260300
- Other Identifier
- 991021901312304721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Materials Science, Multidisciplinary
- Metallurgy & Metallurgical Engineering