It is well known that birds, bats, insects and fishes can sense environmental flows to perform agile and robust motion. They are also using information about external flows to harvest energy from the environment. The research project at Cranfield is directed towards employing bio-inspired technologies to develop a novel aerial platform and improve existing ones. Read more Read less

Due to recent development in the miniaturization of sensors, actuators, and electronics, the aeroelastic parameters, such as velocity, pressure, and deformations, can be measured and controlled directly in flight. Together with significant capabilities to handle big data sets provided by Artificial Intelligent (AI) technologies this stimulates the research toward a bio-inspired sensing and control enabling a system to adapt to the environment and thus to demonstrate higher performance.

New technologies available in sensing, actuation, materials, electronics as well in AI require re-thinking of collecting, processing data and control approaches to enable bio-inspired flight. New strategies should utilise novel capabilities and tackle challenges arising with a new generation of technologies, improving the system performance. An array of multi-modal (pressure, acceleration) sensors generates big data that should be handled online via AI techniques to observe the time-spacial flow patterns and structural loads; new materials and new micro actuators provide the distributed actions along the wing to improve the system performance.

This project envisages a re-thinking of the sensing paradigm to reflect recent technology advances and shifting it towards bio-inspired methods. These will be achieved via development of distributed multi-modality measurements of external loads acting on the wing and proposing optimal sensor configuration. The control paradigm utilizing distributed multi-modality data to produce distributed control inputs to optimise flow-structure interaction will be designed.

The proposed method is multidisciplinary and lies in the intersection of different domains, namely, aerodynamics, AI, multi-modal distributed sensing, sensor fusion, reduced order modelling, and distributed control.

About Cranfield University

Cranfield is an exclusively postgraduate university that is a global leader for education and transformational research in technology and management.

Cranfield University has been ranked amongst the world’s top universities in the latest QS World University Rankings by Subject.

In the subject area ‘Engineering – Mechanical, Aeronautical and Manufacturing’ Cranfield has been ranked 27th in the world, climbing 18 places from last year’s ranking and attaining top scores in Employer and Academic Reputation.

This PhD will be hosted by the Centre for Autonomous and Cyber-Physical Systems. The Centre for Autonomous and Cyber-Physical Systems is one of the world’s largest centres of postgraduate education and research, with over 200 MSc and PhD students.

The Centre for Autonomous and Cyber-Physical Systems at Cranfield has a leading reputation in autonomous and space systems, established with over 15 years of research in this field. We cover all types of autonomous systems including airborne, ground and marine as well as autonomous space exploration.

We are renowned for being a leading European centre for postgraduate teaching and research in autonomous and cyber-physical systems with approximately 500 alumni members around the world working in the aerospace industry. Over the last two decades we have developed a significant body of research and its applications in autonomous systems.

At a glance

  • Application deadline20 Apr 2023
  • Award type(s)PhD, MSc by Research
  • Duration of awardPhD: 3 years; MSc by Research: 1 year
  • EligibilityUK, EU, Rest of World
  • Reference numberSATM278 for PhD or SATM279 for MSc by Research

Entry requirements

Applicants must have a first- or second-class UK honours degree or equivalent in Maths, Physics, engineering or a related area. Fluid dynamics, aerospace or computer science background would be a distinct advantage as would experience of control, sensor fusion and aerodynamics.

Funding

This is a self-funded opportunity so the student would need to source their own funding. However, bursary can be considered for an exceptional candidate. The application is open to UK and international students.

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

If you are eligible to apply for this research studentship please complete the relevant application form below:

Online application form for PhD 

Online application form for MSc by Research

For further information please contact - Dr Dmitry Ignatyev

E: d.ignatyev@cranfield.ac.uk