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  Stochastic response characterisation and reliability driven optimisation of floating wind turbines

   School of Engineering

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  Dr S Sriramula, Prof Alireza Maheri  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

As the wind turbine installations move to deep-water environments, there is an increasing focus on the design considerations for floating wind turbines (FWTs). The uncertainties existing at various levels in the geometric and material variables, combined with complex probabilistic aerodynamic and hydrodynamic loads lead to many research challenges in studying the stochastic response of FWTs [1-2]. There is a need to develop computationally efficient performance evaluation approaches considering the nonlinear dependencies between the stochastic variables accurately. This, when combined with cost-based considerations, can lead towards optimal design basis.

This PhD research will aim to develop innovative reliability- based optimisation schemes for efficient design of FWT systems. The project will rationally combine outputs from fully coupled simulations with stochastic models, leading to target reliability basis for component optimisation. The performance computations will consider a wide range of failure conditions through suitable surrogate (machine learning) models for efficient system representation. The models will initially focus on existing reliability levels and later extend to consider varying target performance requirements. An understanding of the underlying reliability of these structures is essential for developing rational safety factors and this research will also contribute in this direction.

Selection will be made on academic merit. The successful candidate should have (or expect to achieve) a minimum of a UK Honours degree at 2.1 or above (or equivalent) in Aerospace/ Civil / Marine/ Mechanical engineering.

Essential knowledge: Structural mechanics, numerical analysis, computer programming, optimisation, structural reliability.


Formal applications can be completed online:

• Apply for Degree of Doctor of Philosophy in Engineering

• State name of the lead supervisor as the Name of Proposed Supervisor

• State ‘Self-funded’ as Intended Source of Funding

• State the exact project title on the application form

When applying please ensure all required documents are attached:

• All degree certificates and transcripts (Undergraduate AND Postgraduate MSc-officially translated into English where necessary)

• Detailed CV, Personal Statement/Motivation Letter and Intended source of funding

Informal inquiries can be made to Dr S Sriramula ([Email Address Removed]) with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Postgraduate Research School ([Email Address Removed])

Engineering (12)

Funding Notes

This PhD project has no funding attached and is therefore available to students (UK/International) who are able to seek their own funding or sponsorship. Supervisors will not be able to respond to requests to source funding. Details of the cost of study can be found by visiting


1. Okpokparoro, S., Sriramula, S. (2021), ‘Uncertainty modeling in reliability analysis of floating wind turbine support structures’, Renewable Energy, 165, pp. 88-108.
2. Maheri, A. (2020), 'Multiobjective Optimisation and Integrated Design of Wind Turbine Blades Using WTBM-ANSYS for High Fidelity Structural Analysis', Renewable Energy, 145, pp. 814-834.

Where will I study?

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