@inbook{6ca41f96ca554b7fa8365c2374c0ec95,
title = "Data-driven self-consistent clustering analysis of heterogeneous materials with crystal plasticity",
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.",
author = "Zeliang Liu and Kafka, {Orion L.} and Cheng Yu and Liu, {Wing Kam}",
note = "Funding Information: Acknowledgements Z.L., O.L.K., C.Y. and W.K.L. warmly thank the support from AFOSR grant No. FA9550-14-1-0032, National Institute of Standards and Technology and Center for Hierarchical Materials Design (CHiMaD) under grant No. 70NANB13Hl94 and 70NANB14H012, and DOE CF-ICME project under grant No. DE-EE0006867. O.L.K. thanks United States National Science Foundation (NSF) for their support through the NSF Graduate Research Fellowship Program (GRFP) under financial award number DGE-1324585. Publisher Copyright: {\textcopyright} Springer International Publishing AG 2018.",
year = "2018",
doi = "10.1007/978-3-319-60885-3_11",
language = "English (US)",
series = "Computational Methods in Applied Sciences",
publisher = "Springer Netherland",
pages = "221--242",
booktitle = "Computational Methods in Applied Sciences",
}