Open Access

ARTICLE

A Novel Framework for Building Materials Knowledge Systems

Surya R. Kalidindi^1,2,3, Stephen R. Niezgoda¹, Giacomo L,i^1,1, Tony Fast¹

1 Department of Materials Science and Engineering, Drexel University, Philadelphia, 19104
2 Department of Mechanical Engineering and Mechanics, Drexel University, Philadelphia 19104
3 Author to whom correspondence should be addressed

Computers, Materials & Continua 2010, 17(2), 103-126. https://doi.org/10.3970/cmc.2010.017.103

Abstract

This paper presents a novel mathematical framework for building a comprehensive materials knowledge system (MKS) to extract, store and recall hierarchical structure-property-processing linkages for a broad range of material systems. This new framework relies heavily on the use of computationally efficient FFT (Fast Fourier Transforms)-based algorithms for data-mining local structure-response-structure evolution linkages from large numerical datasets produced by established modelling strategies for microscale phenomena. Another 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 modelling of materials phenomena. The viability of this new approach is demonstrated in this paper with two selected case studies: (i) rigid-plastic deformation of a two-phase composite material, and (ii) spinodal decomposition of a binary alloy.

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