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Enhanced Environmental Modules for Intelligent Digital Twins in Air Traffic Management (ATM)

City, University of London - Department of Engineering

Qualification Type: PhD
Location: London
Funding for: UK Students
Funding amount: Tuition fees (Home) and a tax-free stipend of £21,000/year and an additional £4,000 available for travel, conferences and publications.
Hours: Full Time
Placed On: 4th December 2023
Closes: 2nd January 2024

Overview

The successful candidate enhance existing digital twin platforms of air traffic by the development of advanced environmental AI modules. These can then be used to assess the environmental impact of ATM concepts in the short, medium and long term at airports. The aviation industry has been under intense pressure to improve their environmental footprint in support of Target Net Zero policies adopted by multiple national bodies and international regulators. The implementation solution will embrace digitization, automation and Artificial Intelligence (AI) to improve the Key Performance Indicators (KPI) identified with environmental impact being the main focus. However, trade-off studies will also be embraced in a way to prioritise preferences and understand sensitivity and uncertainty. By improving the capabilities of the environmental modules within a digital twin of the air traffic sector, a more comprehensive understanding of the holistic effect of any change in ATC operations can be obtained.

The project is fully supported by the air traffic service provider for the UK and the eastern part of the north Atlantic, NATS. This will offer unparalleled insights into state-of-the-art procedures and systems and will entail significant on-site engagement and time spent at the City-NATS Air Traffic Environmental Research Group (ATERG) at Fareham on the South Coast. There are established working relations which will be a part of this work including links with The Alan Turing Institute for AI and other UK/EU institutions.

Research hypothesis:

It is proposed that the value of a Digital Twin of Multi-modal ATC would be greatly enhanced if there was a dedicated model to assess environmental impacts of new technologies or procedures.

High level objectives:

  1. Study the State of the Art of Decision Support in Automation using digital twin and carry out case studies;
  2. Determine optimal and AI-driven methodology to integrate environmental factors into traffic management decisions;
  3. Develop and deliver a tool able to support strategic ATCO decisions on flow management level.

Eligibility and requirements 

The candidate should have a e.g. first or upper second-class BEng/MEng (or equivalent, or higher) degree in Aeronautical Engineering or Aviation, Mechanical Engineering, Computer Science or similar. They should demonstrate aptitude for original research, innovative thinking and impact-based solutions and validation.

Scholarship: The studentship is for 3 years and will provide an annual tax-free stipend of £21,000 and tuition fees (Home only). There will be an additional £4,000 available for travel, conferences and publications.

It will be crucial for the successful candidate to work both independently and as part of a team environment. The University will provide access to all the typical facilities and a diverse interactive PhD working environment, while NATS will also provide workspace and ready contact to associated experts as and when necessary, and as mentioned the candidate will be a core member of the City-NATS Air Traffic Environmental Research Group (ATERG).

For an informal discussion, please contact Professor Richard Curran Richard.Curran@city.ac.uk

How to apply

Apply online: 

https://www.city.ac.uk/prospective-students/courses/research/mechanical-engineering-and-aeronautics

Any queries with application process, please contact pgr.sst.enquire@city.ac.uk

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