College of Science & Engineering

School/College	University of Strathclyde, Department of Mechanical and Aerospace Engineering
Email	marilena.di-carlo@strath.ac.uk
Twitter	@marilena_sdc

 

Research vision

I am a Research Associate at the Department of Mechanical and Aerospace Engineering of the University of Strathclyde. My research focuses on the development of tools for the design of space missions for small, low-cost, electric-propelled spacecraft.

In recent years, electric propulsion has become a key technology for space exploration. Spacecraft propelled by electric engines can achieve goals that are not possible with traditional chemical engines, because of the reduced mass of propellant that they require.

Examples of missions that I have studied during my research are interplanetary missions to visit several asteroids, and missions to remove multiple space debris from Earth’s orbit. Space debris are the non-operational objects left in Earth’s orbit at the end of their life; these objects could pose a potential threat to future access to space. Therefore, the removal of space debris from Earth’s orbit is necessary in order to avoid a cascade effect where more and more debris are generated by the collision of existing ones.

For my research, I combine optimisation, analytical solutions and artificial intelligence. Combining these tools, I can design missions at different level of fidelity, from an initial fast analysis, to a more accurate refinement to an operational solution.

Expectations from collaboration

I am looking for collaborators in the field of robust optimisation, uncertainty quantification and artificial intelligence. In particular, I would like to investigate the possibility to apply new methods, from each one of these three fields, to the space sector.

I am also hoping to hear from anyone working on the topic of robust trajectory optimisation in space industries and space agencies.

Key Skills

• Space mission analysis,
• design of spacecraft trajectories,
• astrodynamics,
• evolutionary computation

 

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First published: 7 May 2019