Location:

United Kingdom


Position type:

Full time

11 Apr 2019
30 Jun 2019

Full details:

Reference number: SOU-1132119DA

Project Description

How do we represent more complex shapes during engineering design and analysis? 3D printing, (additive manufacturing) and incorporation of image scan data (from manufacturing and in service) both result in shapes that are not easily captured by arcs and straight lines. How do we interact with geometry when dealing with this data as part of normal engineering workflows?

In this project ideas from photo editing tools and computer animation will be adapted to work with commercial CAD software to add new geometry layers that can represent both variations stemming from manufacture and those arising from wear in service. This will permit the full range of engineering analysis methods to be applied to real part shapes. Combined with the latest GPU hardware, Deep Learning, Data Mining and Artificial Intelligence methods to allow hint based automatic geometry creation, the project will provide insights into the next generation of engineering design software.

If you wish to discuss any details of the project informally, please contact Prof Andy Keane, Computational Engineering and Design Research Group, Email: ajk@soton.ac.uk, Tel: +44 (0) 2380 59 2944.

Funding and Eligibility

This project is funded by Rolls-Royce plc as part of their support to the R-R University technology Centre for Computational Engineering at Southampton. The studentship covers UK/EU level fees. In addition to the basic tax free student stipend of £15,009 pa, R-R will provide a further tax free stipend increment of £9,000 pa. The stipend will rise in subsequent years. Funding for travel to international conferences will be available.

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