The School of Engineering at University of Edinburgh is currently building a first-in-class EPSRC funded structural composites research facility (FASTBLADE) for fatigue testing of tidal turbine blades. This facility is used to a) determine the static loading performance of the blade (stiffness-deflection curve plus full strain mapping of the surface in strategic sections of the blade, b) perform a cyclic loading test to 10 million cycles in cantilever mode. The data gained from FASTBLADE operating in ‘dry’ mode will enable a major step-change in knowledge; however, it is limited by its restrictive and approximate loading conditions compared with service. This is because FASTBLADE will load blades at multiple discrete loading points along a blade’s service, whereas in reality, blades are subject to continuous water loading under immersion, the hydrodynamic forces acting in multiple vectors simultaneously, and other boundary layer flow effects that cannot be captured. In this sense, the two loading scenarios are significantly different, so that ideally the discrete fatigue test must be modified to approximate the ocean loading conditions as closely as possible. To enable this to happen, the loading states and events in both scenarios must be minutely understood and compared to make the dry discrete loading test as representative of ocean loading during service as possible and this will be undertaken in this PhD research.
This research will be undertaken in four parts; A: Classification/Confirmation of Ocean Operating State for a Full Scale Turbine Blade, B: Confirmation of Optimal Design for a Blade Fatigue Loading Study, C: Stress Simulation of Various Loading Point Configurations for discrete-point fatigue testing at FASTBLADE, D: Design and Construction of Discrete Load Introduction Saddles based on stress analysis in C. E: Implementation of Discrete Load Introduction Saddles in a Dynamic Test at FASTBLADE. F: Analysis of Test Performance and Blade Condition in vicinity of load introduction points. G: Comparison (where possible) with condition of ocean exposed tidal blades (inspection for cracks, damage, failure mode).
The research team at the University of Edinburgh has access to a comprehensive world class site measurement datasets of tidal currents in the Fall of Warness, Orkney. The first part of this project will predict tidal blade loads in operation using the site measured data. In the second part, ocean loading data in the form of time spectra of continuous surface loading on full scale blades will be converted into a Discrete Point Loading Plan so that four or five laboratory actuators can representatively reproduce a distribution of forces and bending moments that would be experienced in the ocean environment. In the third part of the research the loading spectra generated in Part I, converted to a discrete point loading plan in Part II will be implemented on a 10th scale prototype, and later on a full scale blade during testing at FASTBLADE. Full loading and failure data from the test will be compared with predicted models of stress development and crack initiation and propagation, and verify whether the test is behaving as expected by the stress simulation.
The student will join the Centre for Doctoral Training (CDT) in Wind and Marine Energy Systems and Structures (WAMESS). Please see https://edin.ac/2zvpMb2 for more information on the programme of study including the list of taught courses.
Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree.
The applicant should have an undergraduate or postgraduate degree in Mathematics, Physics, Engineering or equivalent, and a fluid mechanics/hydrodynamics/structural mechanics background at undergraduate level.
Further information on English language requirements for EU/Overseas applicants.
Tuition fees + stipend available for Home students or EU students who have been resident in the UK for 3 years (International students not eligible).
Applications are also welcomed from self-funded students, including international students.