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Details of Grant 

EPSRC Reference: EP/V022687/1
Title: Patterns recognition inside shear bands: tailoring microstructure against localisation
Principal Investigator: Borodin, Dr I
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Mechanical Aerospace and Civil Eng
Organisation: University of Manchester, The
Scheme: New Investigator Award
Starts: 01 September 2021 Ends: 31 August 2023 Value (£): 282,347
EPSRC Research Topic Classifications:
Algebra & Geometry Eng. Dynamics & Tribology
Materials testing & eng.
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:
Panel DatePanel NameOutcome
02 Feb 2021 Engineering Prioritisation Panel Meeting 2 and 3 February 2021 Announced
Summary on Grant Application Form
In spite of decades of investigations and a large number of works devoted to localisation phenomena in metals, this area contains challenges in terms of scientific understanding and industrial applications. Our view is that the main reason for the present insufficient understanding is the neglect of structural features' evolution during the supplementary continuous recrystallization process, leading to absence of any effective methodology for localised microstructure representation. Neglecting effects of patterning into the network of structural defects, such as grain boundaries, makes the problem unsolvable with current approaches.

An essential part of the present project is reformulation and adaptation of some well-developed modern mathematical tools for structure recognition along with the application of our own original approach to continuous dynamic recrystallization to fill the discussed gap in material physics. Based on the analysis of discrete complexes and graph (or network) theory we will be studying the defect patterns which contribute to shear localisation and fracture initiation. High-strain-rate deformation conditions, as a limit case, give us a unique opportunity to make this study in the purest possible way to set apart the localisation phenomena from many other contributions, such as bulk diffusion or scale effects.

Modern experimental methodologies such as 3D EBSD and X-ray tomography in conjunction with proposed discrete theoretical analyses for patterns recognition (during the grain boundary network evolution) open inspirational possibilities in order to make a new significant step forward to solve the localisation problem. Subsequently, we will work closely with our industrial partners and HVM Catapult (Advanced Forming Research) centre for bespoke manufacturing of aluminium alloys possessing the "fine-drawn" defect microstructures discovered in the course of this project.
Key Findings
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Organisation Website: http://www.man.ac.uk