MS thesis abstract - Lamamy, Julien-Alexandre
|Degree:||Masters of Science|
|File type:||PDF, 2410 kB|
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Enhancing the science return of Mars missions via sample preparation, robotic surface exploration and in orbit fuel production
The future of Mars exploration is challenging from multiple points of view. To enhance their science return, future surface probes will most likely be equipped with complex Sample Preparation And Transfer (SPAT) facilities. Future rovers will need to be able to perform longer traverses and delicate sample acquisition operations. Mars return missions would benefit from a new propulsion system, with better fuel and travel time efficiencies than chemical and electric propulsions, respectively.
A model was developed that optimizes SPAT facilities in terms of productivity and system mass. The SPAT model especially investigates two trade-offs: shared versus specific preparation, and warm versus cold redundancy for SPAT elements. A Mars Surface Exploration (MSE) framework was created to help designers perform preliminary studies on rover missions. MSE applies multidisciplinary design optimization techniques for the analysis of design trade-offs relevant to the rover design community. The Propellant Production In Mars Orbit (PPIMO) is presented as a promising solution for performing return travels to Mars. PPIMO uses the concept of regenerative aerobraking to produce fuel in-situ.
The SPAT model shows that warm redundancy improves productivity by both reducing risk and removing sample throughput bottlenecks. A method is presented for determining the economy of scale the shared preparation architecture must exhibit for it to be competitive in comparison to the distributed architecture. MSE is used to budget the future development costs of rover autonomy, in addition to assessing: the benefits of oversized suspensions, the practicality of solar versus nuclear power for future missions, and the advantages of multi-rover missions. When compared to chemical and electric propulsions, PPIMO propulsion shows a better performance in terms of transportation ratio for payloads larger than 1000 kilograms.