A fully-funded PhD studentship is available at Manchester University, working in close collaboration within the Department of Mechanical Engineering, Department of Materials and Department of Engineering for Sustainability and RACE/UKAEA.
RACE (Remote Applications in Challenging Environments, http://www.race.ukaea.uk/) was founded in 2014 as part of the UK Atomic Energy Authority (UKAEA) fusion research and development programme - to create robots for operating in some of the most challenging environments imaginable. UKAEA’s wider mission is to lead the commercial development of fusion power and related technology, and position the UK as a leader in sustainable nuclear energy. Based at Culham Science Centre near Oxford and at a new technology facility in South Yorkshire, UKAEA runs the UK’s fusion research programme and operates the Joint European Torus (JET) fusion experiment on behalf of scientists from 28 European countries. UKAEA is keeping the UK at the forefront of fusion as the world comes together to build the first powerplant-scale experiment, ITER – one step away from the realisation of nuclear fusion as a carbon-neutral energy source. JET serves as a test base for ITER, as well as future fusion demonstration powerplants putting electricity on the grid such as DEMO and UK’s own future STEP powerplant.
Fusion power plants require associated support systems (e.g., water supplies) which will degrade over time because of the effects of corrosion and irradiation under heavily constrained conditions. To guarantee safe and sustainable operations, these systems need to be repaired, when any assembly therein is damaged and failing its designed specifications. In current tokamaks, the repair of (even small) damaged components involves complex maintenance operations where the disassembly and transportation of whole sub-assemblies is often required. Thus, there is a possibility to reduce down-time if remote maintenance can be achieved via in-situ additive materials deposition and modification methods. Over the next decades, fusion tokamaks are expected to form part of the energy mix.
A fully-funded 3.5 yrs PhD studentship is available to investigate and develop laser-based additive handling techniques that allow repairing a partially damaged steel assembly in situ, and which are compatible for future integration in remotely operated robotic systems. Type 316L austenitic stainless steel and P91 ferritic-martensitic steels will be assessed for their suitability for laser-based additive repair processes, with a focus on process optimisation for remote deployability in fusion plants. The aim is to facilitate rapid repairing of sub-assemblies such as pipe components, to reduce the time/cost for remote maintenance.
The project will include the following aspects:
• Experimental and numerical analysis of the effect of cladding orientation on the properties of the repaired component, comparing with baseline top-down cladding.
• Experimental and numerical analysis of the effect of the work-piece initial condition and geometry (including cylindrical pipes) on the properties of the repaired component.
• Optimization of process parameters in the context of robotic deployable solutions.
• Assessment of mechanical properties, microstructure, and residual stress state of additively manufactured samples, with the aim to reduce corrosion and stress corrosion cracking susceptibility.
The candidate will be working with Dr Olivier Allegre, Prof Dirk Engelberg and Prof Paul Mativenga, building on the team expertise in the laser-based manufacturing group. This group at the University of Manchester includes more than 60 researchers, created through a set of significant UKRI/EPSRC grants (e.g. EP/K026348/1, EP/K026429/1, EP/G034745/1 and DT/E010512/1 ; https://www.mace.manchester.ac.uk/lprc/research/ ). The scholarship is part the strategic relationship between the University of Manchester and UKAEA. The student will be supervised by academics at the University of Manchester and RACE robotics experts.
Admissions qualifications
Applicants should have at least 2:1 (or UK equivalent) BEng/MEng (Hons) with a vivid interest in solving engineering challenges (electrical / electronic / mechanical, optic) or the field of mechatronics. The applicants should ideally have a knowledge in modern intelligent control methods robotics, or physics. Knowledge of lasers, optics, or material processing would be beneficial. Demonstrable experimental experience is to a great advantage.
Before you apply
We strongly recommend that you contact the lead supervisor for this project before you apply.
For more information on existing research in this area at Manchester please contact: Dr Olivier Allegre [Email Address Removed]
How to apply
To be considered for this project you’ll need to complete a formal application through our online application portal.
When applying, you’ll need to specify the full name of this project, the name of your supervisor, details of your previous study, and names and contact details of two referees.
Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.
If you have any questions about making an application, please contact our admissions team by emailing [Email Address Removed].
Equality, diversity and inclusion
Equality, diversity and inclusion is fundamental to the success of The University of Manchester and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.
We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.
We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).
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