Development and optimisation of ultra-efficient and power dense ice protection system for future aircraft systems

About the Project

This PhD project lies within the discipline of atmospheric icing science, specifically at the intersection of aircraft systems design, thermal management, and artificial intelligence/machine learning. It focuses on electrothermal ice protection systems (ETIPS), which prevent hazardous ice accretion on wings, rotors, engine inlets and other critical surfaces using embedded electrical heating. ETIPS technology is highly relevant due to the global shift toward More Electric and hybrid-electric aircraft configurations due to superior energy efficiency, lower emissions and better integration with composite structures. Optimising their performance with AI/ML is critical for meeting reducing power consumption, and enabling safer, more sustainable operations in icing conditions for next-generation commercial, regional and unmanned platforms.

The aim of this research project is to develop novel methods to optimise de-ice ETIPS, which will replace current manual and slow processes. It is envisaged that the PhD research will develop a range of novel agent based AI/ML techniques and neural networks to enable the exploration of this high-dimensional design space. This will be combined with traditional gradient-based optimisation approaches. This capability will enable for the first time to get a fast and accurate understanding of the de-ice ETIP design space.

As part of this project, you will join a multidisciplinary team with experience in multiscale, experimental and numerical icing simulations, aerodynamics, systems design and optimisation. The sponsor for this project is AeroTex UK LLP, a SME based in the UK, that specialises in aircraft icing with research projects focussing on the fundamentals of ice accretion physics, the practicalities of ice protection system design, and the icing certification process.

The project will integrate high-fidelity multi-physics simulations with AI/ML surrogate models and multi-objective optimisation algorithms to efficiently explore the complex ETIPS design space. This will enable rapid exploration of heater layouts, zoning strategies, and power-density distributions. New machine-learning-driven strategies will support adaptive scheduling, predictive control, and semi-autonomous operation of ETIPS under highly variable icing conditions. These novel operational methods will improve robustness and energy efficiency of the system.

The PhD offers the candidate a unique opportunity to work directly with AeroTex UK LLP and benefit from their vast experience in icing science and engineering to develop advanced ice protection systems. AeroTex UK will provide access to their state-of-the-art icing codes and train the candidate on their use. The PhD candidate will be able to attend international conferences and workshops along with attending specialist MSc modules if required. The programme includes regular reviews and presentations with the industrial partners.

The student will acquire highly sought-after expertise in the application of advanced AI/ML techniques (including surrogate modelling, reinforcement learning, and multi-objective optimisation) to complex aerospace engineering problems. They will develop strong capabilities in multiphysics simulation, thermal systems design, data-driven optimisation, and high-performance computing. Key transferable skills include machine learning development, uncertainty quantification, collaborative research, technical communication, and the ability to translate AI solutions into real-world engineering systems. These skills would make the student a future leader in the aerospace sector and broader intelligent systems industries, positioning the graduate strongly for research, innovation, or academic careers.

Funding Notes

Sponsored by EPSRC and Cranfield University, this studentship will provide a bursary of up to £ 25,183 (tax free) plus fees* for four years.

To be eligible for this funding, applicants must be classified as a Home fee status student. Eligibility for Home fee status is determined with reference to UK Department for Education rules. As a guiding principle UK or Irish nationals who are ordinarily resident in either the UK or Republic of Ireland pay Home tuition fees. All other students (including those from the Channel Islands and Isle of Man) pay Overseas fees.