Deadline: Applications will be accepted at any time until the position is filled.

There is an ever increasing interest in exploiting ocean resources at greater depths. At these depths composite materials have a larger separation, in terms of benefits, from traditional steel structures as they offer lower maintenance costs, low weight and high durability. However, there are limited current examples of using composites for these applications meaning that empirical knowledge and specific computational tools are limited. As an example of this lack of knowledge current design guidance gives fatigue safety factors in a range of 15-50. Development of more accurate computational tools will allow an increase in safety and/or reduction of the structure.  

A key aspect to increasing the usage of flexible composite risers is the ability to assess the reliability of such structures. Importance Sampling Simulation is becoming the preferred method to assess structures which ideally requires a fast and accurate structural modelling method. Whilst Finite Element Methods can provide an accurate solution to these problems they are slow to run. It is therefore proposed to investigate the use of multiscale modelling to investigate the reliability of such structures. This will involve the development of: a full-scale model to be run in conjunction with fluid mechanics simulations, a higher resolution model to investigate the fatigue hotspot near the seabed and a more local model to simulate the fatigue growth.

If you wish to discuss any details of the project informally, please contact Adam Sobey, Fluid Structure Interactions group, Email: ajs502<στο>soton.ac.uk, Tel: +44 (0) 2380 59 7773.

Funding information: This project is in competition with others for the associated funding. The funding covers EU/UK fees and stipend. 

This project is run through participation in the EPSRC Centre for Doctoral Training in Next Generation Computational Modelling (http://ngcm.soton.ac.uk). For details of our 4 Year PhD programme, please see http://www.findaphd.com/search/PhDDetails.aspx?CAID=331&LID=2652.