Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.770182
Title: Novel Cellular-Automata (CA) based modelling and optimization for recrystallization and grain growth in materials : theory and applications
Author: Aflyatunova, Daliya
ISNI:       0000 0004 7651 5350
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2018
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Abstract:
The mechanical properties of alloys depend on their microstructure, or grain sizes, which are obtained during processes of the grain growth and recrystallization. However, experiments do not allow to observe all details of the process and there is no theoretical model to predict these. This is why computer modelling allows for the prediction of microstructure. Cellular Automata (CA) is known to be used to for the simulation of the grain growth. However, (CA)-based models usually work only on the specific range of parameter, because there is no linear relationship exists between cellular automata and the physical parameters. This thesis describes a newly developed space and time realistic Cellular Automata technique for the solving of various differential equations. It has been shown that the model is capable of solving the associated differential equations, which describe grain boundary movement, but with the errors that are related to the square grid. The newly suggested type of neighbourhoods allowed to eliminate the effects of the grid and obtain better prediction results.
Supervisor: Mahfouf, Mahdi ; Panoutsos, George Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.770182  DOI: Not available
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