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Solar Sails for Near- and Medium-Term Scientific Deep Space Missions / W. Sebolt ; B. Dachwald
(2005)
Optimization of Interplanetary Rendezvous Trajectories for Solar Sailcraft Using a Neurocontroller
(2002)
Solar sailcraft of the first generation technology development / Seboldt, Wolfgang ; Dachwald, Bernd
(2003)
Within ESA's Cosmic Vision 2015-2025 plan, a mission to explore the Saturnian System, with special emphasis on its two moons Titan and Enceladus, was selected for study, termed TANDEM (Titan and Enceladus Mission). In this paper, we describe an optimized mission design for a TANDEM-derived solar electric propulsion (SEP) mission. We have chosen the SEP mission scenario for the interplanetary transfer of the TANDEM spacecraft because all feasible gravity assist sequences for a chemical transfer between 2015 and 2025 result in long flight times of about nine years. Our SEP system is based on the German RIT ion engine. For our optimized mission design, we have extensively explored the SEP parameter space (specific impulse, thrust level, power level) and have calculated an optimal interplanetary trajectory for each setting. In contrast to the original TANDEM mission concept, which intends to use two launch vehicles and an all-chemical transfer, our SEP mission design requires only a single Ariane 5 ECA launch for the same payload mass. Without gravity assist, it yields a faster and more flexible transfer with a fight time of less than seven years, and an increased payload ratio. Our mission design proves thereby the capability of SEP even for missions into the outer solar system.
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.
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 ”IceMole“ is a novel maneuverable subsurface ice probe for clean in-situ analysis and sampling of subsurface ice and subglacial water/brine. It is developed and build at FH Aachen University of Applied Sciences’ Astronautical Laboratory. A first prototype was successfully tested on the Swiss Morteratsch glacier in 2010. Clean sampling is achieved with a hollow ice screw (as it is used in mountaineering) at the tip of the probe. Maneuverability is achieved with a differentially heated melting head. Funded by the German Space Agency (DLR), a consortium led by FH Aachen currently develops a much more advanced IceMole probe, which includes a sophisticated system for obstacle avoidance, target detection, and navigation in the ice. We intend to use this probe for taking clean samples of subglacial brine at the Blood Falls (McMurdo Dry Valleys, East Antarctica) for chemical and microbiological analysis. In our conference contribution, we 1) describe the IceMole design, 2) report the results of the field tests of the first prototype on the Morteratsch glacier, 3) discuss the probe’s potential for the clean in-situ analysis and sampling of subsurface ice and subglacial liquids, and 4) outline the way ahead in the development of this technology.
We propose a simple parametric OSSD model that describes the variation of the sail film's optical coefficients with time, depending on the sail film's environmental history, i.e., the radiation dose. The primary intention of our model is not to describe the exact behavior of specific film-coating combinations in the real space environment, but to provide a more general parametric framework for describing the general optical degradation behavior of solar sails.