Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel the future of Corrosion-Fatigue engineering.

The application of repetitive loads results in fatigue damage that can propagate and cause catastrophic failures. The ambient conditions around a fatigue crack tip has a dramatic effect on the fate of a component—a part may survive millions of cycles in vacuum and last only a few hundreds of thousands in air and much lower in actively corrosive environments. Although there is a clear synergy between fatigue damage and corrosion, most fatigue prognosis models do not explicitly consider the role of the environment, which is usually reduced to obscured fitting coefficients. This strategy carries large uncertainty and requires vast amount of expensive and time-consuming experimental data. Worse, sometimes the experimental data is simply inaccessible.

The need for cost-efficient research that prevents fatigue failures has pushed towards integrated computational materials engineering approaches that improve competitiveness. These approaches rely on physics-based models that can be validated with experiments and bottom-up models at multiple scales in order to predict the macroscopic response. Hence, this research will investigate the degradation of metallic materials under corrosion-fatigue conditions by integrating multiscale physics-based models combined with mesoscale experimental tests.

This research will study the effects of corrosion-induced changes in composition on fatigue damage in metallic materials. We will employ 3-D crystal plasticity models in order to understand the role of compositional changes in fatigue damage. We will correlate these changes with a realistic degradation from corrosion processes. The simulations will be integrated with mesoscale experimental to evaluate the constitutive response of smooth specimens degraded by corrosion. Given the innovative nature of this research, it will represent a milestone in corrosion-fatigue research and will likely mark a path towards future degradation assessments.

At a glance

  • Application deadlineOngoing
  • Award type(s)PhD
  • Duration of award3 years
  • EligibilityUK, EU, Rest of world
  • Reference numberSATM472 & SATM473


Dr. Gustavo Castelluccio is a leader in Mesoscale Mechanics. His work integrates multiscale models and experiments to discover the fundamental mechanisms responsible for damage and deformation.

About the host University and Through-life Engineering Services (TES) Centre

Cranfield is an exclusively postgraduate university that is a global leader for transformational research and education in technology and management. Research Excellence Framework 2014 (REF) has recognised 81% of Cranfield’s research as world leading or internationally excellent in its quality. Every year Cranfield graduates the highest number of postgraduates in engineering and technology in the UK (Source: Higher Education Statistics Agency Ltd). Cranfield Manufacturing is one of eight major themes at Cranfield University. The manufacturing capability is world leading and combines a multi-disciplinary approach that integrates design, technology and management expertise.

We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of manufacturing research.

The Through-life Engineering Services (TES) Centre are among the world leaders in through-life approaches for high value systems, Condition monitoring, Damage tolerance, Asset management. TES was developed with the support of EPSRC grant of £ 11 million with the aim to develop research excellence and address the research problems in the sector of Through-life Engineering services. TES Centre is providing its state of the art academic and research services to industrial clients such as Boeing, BAE Systems, Rolls-Royce, Meggitt, Thales, MOD, Bombardier, QinetiQ, Thales, Network Rail, Schlumberger and Alstom.

Entry requirements

Applicants should have a first or second class UK honours degree or equivalent in a related discipline, such as computer science, mathematics, or engineering.

The candidate should be self-motivated and have excellent analytical, reporting and communication skills.


Self-funded/partially funded

Please contact the supervisor for more information or explore our funding finder.


Cranfield Doctoral Network

Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This network brings together both research students and staff, providing a platform for our researchers to share ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking opportunities.

How to apply

Before completing the application documentation please contact Dr Gustavo Castelluccio ( for an initial informal discussion about this opportunity. Please include the keyword PhD Studentship-Self Funding in the subject field.

Start date Application deadline  
 30th September 2024  24th July 2024 Apply now 
 27th January 2025  27th November 2024 Apply now

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