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Propagation of uncertainty in astrodynamics réf:T2018SI102

Description

The Space Debris Modelling and Risk Assessment Office (DSO/DV/ISL) is responsible in the field of astrodynamics for research, modelling, R&D and engineering related to space surveillance, space debris, and the French Space Operations Act for projects under development and in operation.

Modelling and risk calculation studies of space debris (in orbit or on atmospheric re-entry) are of growing interest due to the increase in the number of objects orbiting the Earth. The characteristics of such objects (exact position, shape, mass, etc.) are generally less well-known than in the case of controlled satellites. Consequently, they need to be taken into account in all calculations made. Numerous studies (training courses, R&T actions, etc.) linked to the propagation of uncertainty have been carried out in recent years to improve our knowledge of modern techniques of taking account of uncertainties.

During this course:
- You will carry out a bibliographical analysis of various methods of propagation of uncertainty, in particular methods of propagation that involve establishing a metamodel (Polynomial Chaos Expansion [PCE], Taylor Differential Algebra [TDA] and Kriging methods) as well as methods to be applied for non-deterministic problems.
- You will understand and use the results of previous work (training courses, R&T), in particular software bricks that have been developed.
- You will test these methods on different concrete cases such as calculating the risk of collision in orbit, atmospheric re-entry, the propagation of simple orbit or coupled with attitude, etc. It may be possible to develop specific methods (mainly Java and Scilab).
- You will suggest and implement improvements to current methods of propagation of uncertainty.

Desired profile

You should be a final year student at engineering school or university seeking an end-of-course internship and interested in topics related to space surveillance and debris. You should have previously studied astrodynamics. In addition, you should have a good knowledge of IT programming tools (in particular Java) and an interest in digital simulation.
You should be independent, willing to take the initiative, enjoy working in a team and be familiar with Java and Scilab programming languages.

Structure description

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