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2018 | OriginalPaper | Buchkapitel

Data-Driven Self-consistent Clustering Analysis of Heterogeneous Materials with Crystal Plasticity

verfasst von : Zeliang Liu, Orion L. Kafka, Cheng Yu, Wing Kam Liu

Erschienen in: Advances in Computational Plasticity

Verlag: Springer International Publishing

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Abstract

To analyze complex, heterogeneous materials, a fast and accurate method is needed. This means going beyond the classical finite element method, in a search for the ability to compute, with modest computational resources, solutions previously infeasible even with large cluster computers. In particular, this advance is motivated by composites design. Here, we apply similar principle to another complex, heterogeneous system: additively manufactured metals.

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Metadaten
Titel
Data-Driven Self-consistent Clustering Analysis of Heterogeneous Materials with Crystal Plasticity
verfasst von
Zeliang Liu
Orion L. Kafka
Cheng Yu
Wing Kam Liu
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-60885-3_11

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