Yakushina, E.
81  Ergebnisse:
Personensuche X
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3

Deep learning enhanced Watershed for microstructural analys..:

Fotos, G. ; Campbell, A. ; Murray, P..
Journal of Materials Science.  58 (2023)  36 - p. 14390-14410 , 2023
 
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4

Automated analysis of platelet microstructures using a feat..:

Campbell, A. ; Murray, P. ; Yakushina, E....
Journal of Materials Science.  57 (2022)  2 - p. 1448-1461 , 2022
 
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6

Influence of Sheet Conditions on In-Plane Strain Evolution ..:

Blackwell, P. ; Yakushina, E. ; Kwame, J.S
Journal of Materials and Applications.  10 (2021)  1 - p. 15-26 , 2021
 
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7

Effect of Machining Induced Microstructure Changes on the E..:

, In: Forming the Future; The Minerals, Metals & Materials Series,
Kwame, J. S. ; Yakushina, E. ; Blackwell, P. - p. 2695-2704 , 2021
 
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10

Examining Failure Behaviour of Commercially Pure Titanium D..:

Blackwell, P. ; Yakushina, E. ; Kwame, J.S
Journal of Materials and Applications.  9 (2020)  1 - p. 32-37 , 2020
 
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11

Prediction of Hole Expansion Ratio of Titanium Alloys Using..:

Blackwell, P. ; Yakushina, E. ; Kwame, J. S.
Journal of Modeling and Optimization.  12 (2020)  2 - p. 125-137 , 2020
 
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12

Optimisation of laser assisted forming conditions for impro..:

Yakushina, E ; McArthur, M ; Canavan, M
IOP Conference Series: Materials Science and Engineering.  672 (2019)  1 - p. 012066 , 2019
 
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13

The influence of the microstructure morphology of two phase..:

Yakushina, E. ; Reshetov, A. ; Semenova, I....
Materials Science and Engineering: A.  726 (2018)  - p. 251-258 , 2018
 
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14

An evaluation of H13 tool steel deformation in hot forging ..:

Marashi, J. ; Yakushina, E. ; Xirouchakis, P...
Journal of Materials Processing Technology.  246 (2017)  - p. 276-284 , 2017
 
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15

Automated microstructural analysis of titanium alloys using..:

Campbell, A ; Murray, P ; Yakushina, E..
IOP Conference Series: Materials Science and Engineering.  179 (2017)  - p. 012011 , 2017
 
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