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Ramunas Savanevskis
Part II Student
Department of Materials
University of Oxford
Parks Road
Oxford OX1 3PH
UK
Email: partII.student@materials.ox.ac.uk
LinkedIn
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Project Description:
High entropy alloys containing elements that might be readily sourced from waste streams and may provide a sustainable, recyclable utility material – cheap, formable and moderate strength. Quick turnaround and small material volumes are helpful in early stage of alloy design/development. The simple shape and small size possible for bend tests makes them attractive for mechanical properties assessment in these circumstances. However, extracting stress-strain response is not so straight forward, as strain and strain rate varies spatially through the beam.
This project will explore using machine learning surrogate models to extract stressstrain curves from DIC maps of strain evolution during bend tests. Finite element simulations will produce training data sets linked to the known stress-strain response. Then the fast surrogate model will be used for the inverse problem obtaining stress-strain from the experimental bend test data.
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