PhD Student: Structural Longevity for advanced marine vehicles in extreme environments
University of Southampton - Fluid Dynamics, Computational Engineering, Materials & Surface Engineering, Structures & Solid Mechanics
|Funding for:||UK Students, EU Students|
|Funding amount:||The funding covers EU/UK fees and stipend in line with EPSRC rates|
|Placed on:||28th September 2016|
|Closes:||28th December 2016|
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Project Reference: CMEES-FSI-132
Project Theme: Fluid Dynamics, Computational Engineering, Materials & Surface Engineering, Structures & Solid Mechanics
A particularly challenging environment exists for assets in the sea. The response of vessels or platforms are complicated by their condition and their operational parameters at the time and long term predictions of their residual structural capacity have to be made in the face of these complex uncertainties. This doctoral research therefore seeks to apply reliability methods for enhanced design and operational decision making in this complex maritime environment utilising state of the art NDI techniques and in-service monitoring to determine through life structural capacity.
This project is supported by the RNLI who are particularly interested in the derivation of an approach to reliably predict long term performance in extreme environments with particular reference to damage tolerance and progressive failure of their composite vessels. This adds to the novelty of the doctoral research as the prediction of failure modes and the utility of failure models for anisotropic materials within reliability methods is little reported. As such, it’s proposed that the long term predictions are made using limit-state based reliability analysis techniques where failure modes related to strength degradation of composites are considered. Time dependent reliability analysis will be required for both component and system level assessment. Where the system level leads to large design spaces, sampling techniques will be employed. To generate improved reliability estimates, it’s anticipated that condition monitoring data is used in conjunction with Bayesian updating.
Proficiency with finite element analysis and programming languages is required.
Ideal candidates would have a minimum UK equivalent of 2:1 undergraduate degree in relevant engineering sciences, mathematics or physics.
Interviews will be held at the end of November 2016.
If you wish to discuss any details of the project informally, please contact Dr James Blake, Fluid Structure Interactions research group, Email:email@example.com, Tel: +44 (0) 2380 599544.
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South East England