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A technology reference study for a multiple near-Earth object (NEO) rendezvous mission with solar sailcraft is currently carried out by the authors of this paper. The investigated mission builds on previous concepts, but adopts a strong micro-spacecraft philosophy based on the DLR/ESA Gossamer technology. The main scientific objective of the mission is to explore the diversity of NEOs. After direct interplanetary insertion, the solar sailcraft should—within less than 10 years—rendezvous three NEOs that are not only scientifically interesting, but also from the point of human spaceight and planetary defense. In this paper, the objectives of the study are outlined and a preliminary potential mission profile is presented.
A technology reference study for a displaced Lagrange point space weather mission is presented. The mission builds on previous concepts, but adopts a strong micro-spacecraft philosophy to deliver a low mass platform and payload which can be accommodated on the DLR/ESA Gossamer-3 technology demonstration mission. A direct escape from Geostationary Transfer Orbit is assumed with the sail deployed after the escape burn. The use of a miniaturized, low mass platform and payload then allows the Gossamer-3 solar sail to potentially double the warning time of space weather events. The mission profile and mass budgets will be presented to achieve these ambitious goals.
A technology reference study for a solar polar mission is presented. The study uses novel analytical methods to quantify the mission design space including the required sail performance to achieve a given solar polar observation angle within a given timeframe and thus to derive mass allocations for the remaining spacecraft sub-systems, that is excluding the solar sail sub-system. A parametric, bottom-up, system mass budget analysis is then used to establish the required sail technology to deliver a range of science payloads, and to establish where such payloads can be delivered to within a given timeframe. It is found that a solar polar mission requires a solar sail of side-length 100–125 m to deliver a ‘sufficient value’ minimum science payload, and that a 2.5 μm sail film substrate is typically required, however the design is much less sensitive to the boom specific mass.
Enceladus explorer - A maneuverable subsurface probe for autonomous navigation through deep ice
(2012)
There is significant interest in sampling subglacial environments for geobiological studies, but they are difficult to access. Existing ice-drilling technologies make it cumbersome to maintain microbiologically clean access for sample acquisition and environmental stewardship of potentially fragile subglacial aquatic ecosystems. The IceMole is a maneuverable subsurface ice probe for clean in situ analysis and sampling of glacial ice and subglacial materials. The design is based on the novel concept of combining melting and mechanical propulsion. It can change melting direction by differential heating of the melting head and optional side-wall heaters. The first two prototypes were successfully tested between 2010 and 2012 on glaciers in Switzerland and Iceland. They demonstrated downward, horizontal and upward melting, as well as curve driving and dirt layer penetration. A more advanced probe is currently under development as part of the Enceladus Explorer (EnEx) project. It offers systems for obstacle avoidance, target detection, and navigation in ice. For the EnEx-IceMole, we will pay particular attention to clean protocols for the sampling of subglacial materials for biogeochemical analysis. We plan to use this probe for clean access into a unique subglacial aquatic environment at Blood Falls, Antarctica, with return of a subglacial brine sample.
The Saturnian moon Enceladus with its extensive water bodies underneath a thick ice sheet cover is a potential candidate for extraterrestrial life. Direct exploration of such extraterrestrial aquatic ecosystems requires advanced access and sampling technologies with a high level of autonomy. A new technological approach has been developed as part of the collaborative research project Enceladus Explorer (EnEx). The concept is based upon a minimally invasive melting probe called the IceMole. The force-regulated, heater-controlled IceMole is able to travel along a curved trajectory as well as upwards. Hence, it allows maneuvers which may be necessary for obstacle avoidance or target selection. Maneuverability, however, necessitates a sophisticated on-board navigation system capable of autonomous operations. The development of such a navigational system has been the focal part of the EnEx project. The original IceMole has been further developed to include relative positioning based on in-ice attitude determination, acoustic positioning, ultrasonic obstacle and target detection integrated through a high-level sensor fusion. This paper describes the EnEx technology and discusses implications for an actual extraterrestrial mission concept.
Attitude and Orbital Dynamics Modeling for an Uncontrolled Solar-Sail Experiment in Low-Earth Orbit
(2015)
Searching optimal continuous-thrust trajectories is usually a difficult and time-consuming task. The solution quality of traditional optimal-control methods depends strongly on an adequate initial guess because the solution is typically close to the initial guess, which may be far from the (unknown) global optimum. Evolutionary neurocontrol attacks continuous-thrust optimization problems from the perspective of artificial intelligence and machine learning, combining artificial neural networks and evolutionary algorithms. This chapter describes the method and shows some example results for single- and multi-phase continuous-thrust trajectory optimization problems to assess its performance. Evolutionary neurocontrol can explore the trajectory search space more exhaustively than a human expert can do with traditional optimal-control methods. Especially for difficult problems, it usually finds solutions that are closer to the global optimum. Another fundamental advantage is that continuous-thrust trajectories can be optimized without an initial guess and without expert supervision.