Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Evdokia Popova"'
Autor:
David Montes de Oca Zapiain, Hojun Lim, Fadi Abdeljawad, Evdokia Popova, James W. Foulk, Surya R. Kalidindi
Publikováno v:
Integrating Materials and Manufacturing Innovation. 7:97-115
Local features of the internal structure or the microstructure dominate the overall performance of materials. An open problem in materials design with enhanced properties is to accurately identify and quantify salient features of the microstructure a
Publikováno v:
Acta Materialia. 141:230-240
In this work, a data-driven reduced-order model is presented to predict the microscale spatial distribution of the plastic strain rate tensor in an isotropic two-phase composite subjected to an arbitrary macroscopically imposed strain rate tensor. Th
Autor:
Sean R. Agnew, Abhijit Brahme, Yauheni Staraselski, Kaan Inal, Evdokia Popova, Raja K. Mishra
Publikováno v:
Materials & Design. 96:446-457
High temperature deformation processing of magnesium and its alloys is often accompanied by dynamic recrystallization (DRX). Deformation twinning is one of the main deformation mechanisms in HCP metals, but very few works are available in literature
Publikováno v:
Handbook of Materials Modeling ISBN: 9783319429137
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9cd6dd0fdbbdcd1b601d2bfefcf9fb2
https://doi.org/10.1007/978-3-319-42913-7_16-1
https://doi.org/10.1007/978-3-319-42913-7_16-1
Publikováno v:
International Journal of Plasticity. 66:85-102
This study presents a framework to simulate dynamic recrystallization (DRX) in hexagonal closed packed (HCP) metals and alloys using crystal plasticity based finite element model (CPFEM) coupled with a probabilistic cellular automata (CA) approach, a
Autor:
James W. Foulk, Hojun Lim, David Montes de Oca Zapiain, Corey Ernst, Evdokia Popova, David John Littlewood, Suryanarayana Kalidindi, Coleman Alleman, Guy Bergel, Alejandro Mota
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::74ba69161d5bdae06f2b2c76177e0c1c
https://doi.org/10.2172/1399209
https://doi.org/10.2172/1399209
Autor:
Evdokia Popova, Jonathan D. Madison, Theron Rodgers, Ahmet Cecen, Xinyi Gong, Surya R. Kalidindi
A novel data science workflow is developed and demonstrated to extract process-structure linkages (i.e., reduced-order model) for microstructure evolution problems when the final microstructure depends on (simulation or experimental) processing param
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3adfcc1b92466bf54549edcea0fc134
https://europepmc.org/articles/PMC6946012/
https://europepmc.org/articles/PMC6946012/