Integrating with Renewable Energy Sources: Low Pressure Steam Turbine Last Stage Blade Durability
The increased deployment of renewable energy sources requires integration with conventional power plant to back-fill the inevitable dips in supply. This has meant that the cyclic loading on turbine blade components in conventional power plant has sharply increased (due to two-shifting and load following, producing many additional stop-start cycles). A particular challenge for large steam turbine units is ensuring the integrity of the low pressure turbine last stage blades. Increased incidences of fatigue cracking in the root region of the turbine blades are seen due to these additional cyclic loads. The aim of this PhD is to improve the fatigue endurance of the martensitic stainless steel materials used in the turbine blade root in a fully predictable/tailored fashion. This will require consideration of the effects of practical heat treatment procedures applied during manufacture and assessing approaches for improving the fatigue endurance in specific locations in the blade root using predictable and effective surface treatments that do not materially affect the shape of the component. The development of validated fatigue lifing predictions that can be applied easily to in-service surface conditions and appropriate notch geometry measurements in critical stress locations is a key deliverable.
The key aims of the PhD will be:
• Establishing the crack initiation and growth processes through the short crack to long crack regime in the notch features in representative service materials
• Evaluating the effects of heat treatments on this fatigue initiation and growth behaviour in the martensitic stainless steels
• Consideration of how the local geometry variations in the blade (i.e. the varying constraint and notch root sampling volumes) affects the time to defect initiation and subsequent propagation behaviour
• Quantifying the benefits of different candidate surface treatments that improve the fatigue resistance, with a mechanistic insight that informs optimisation approaches
• The definition of a lifing model that takes the above into account – with the aim of predicting scatter in lifetimes in terms of expected microstructure variations, thus developing a digital twin of representative microstructural features and notch geometries/surface conditions
This PhD programme will offer you an excellent training opportunity and develop you as a skilled structural integrity specialist. The supervisory team at Southampton have a long standing reputation in the field of fatigue evaluations in a range of turbomachinery applications and you will join a well-established team, with a critical mass of researchers working in allied fields. https://www.southampton.ac.uk/engineering/about/staff/pasr1.page?
The access to highly specialised mechanical testing capabilities (e.g. full-field experimental mechanics capabilities, thermal imaging, digital image correlation https://www.southampton.ac.uk/engineering/research/facilities/360/tsrl_360.page) and top of the range X-ray CT facilities https://www.southampton.ac.uk/muvis/index.page
together with high level optical and electron microscopy techniques makes Southampton an excellent environment for the proposed research.
If you wish to discuss any details of the project informally, please contact Professor Philippa Reed, Engineering Materials Research Group, Email: [Email Address Removed], Tel: +44 (0) 2380 593763.
This 3 year studentship covers Home-rate tuition fees and provides an annual tax-free stipend at the standard EPSRC rate, which is £15,009 for 2019/20.
To apply, click Visit Website below and then click Apply Here. Select the programme - PhD in Engineering and the Environment. Please enter the title of the PhD Studentship in the application form. The selection process will take into account the strength of the whole application, including academic qualifications, personal statement, CV and references. For further guidance, please contact [email protected]
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FTE Category A staff submitted: 192.23
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