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The scientific interest in near-Earth asteroids (NEAs) and the classification of some of those as potentially hazardous asteroid for the Earth stipulated the interest in NEA exploration. Close-up observations of these objects will increase drastically our knowledge about the overall NEA population. For this reason, a multiple NEA rendezvous mission through solar sailing is investigated, taking advantage of the propellantless nature of this groundbreaking propulsion technology. Considering a spacecraft based on the DLR/ESA Gossamer technology, this work focuses on the search of possible sequences of NEA encounters. The effectiveness of this approach is demonstrated through a number of fully-optimized trajectories. The results show that it is possible to visit five NEAs within 10 years with near-term solar-sail technology. Moreover, a study on a reduced NEA database demonstrates the reliability of the approach used, showing that 58% of the sequences found with an approximated trajectory model can be converted into real solar-sail trajectories. Lastly, this second study shows the effectiveness of the proposed automatic optimization algorithm, which is able to find solutions for a large number of mission scenarios without any input required from the user.
Enceladus explorer - A maneuverable subsurface probe for autonomous navigation through deep ice
(2012)
This paper describes the results and methods used during the 8th Global Trajectory Optimization Competition (GTOC) of the DLR team. Trajectory optimization is crucial for most of the space missions and usually can be formulated as a global optimization problem. A lot of research has been done to different type of mission problems. The most demanding ones are low thrust transfers with e.g. gravity assist sequences. In that case the optimal control problem is combined with an integer problem. In most of the GTOCs we apply a filtering of the problem based on domain knowledge.
Searching optimal interplanetary trajectories for low-thrust spacecraft is usually a difficult and time-consuming task that involves much experience and expert knowledge in astrodynamics and optimal control theory. This is because the convergence behavior of traditional local optimizers, which are based on numerical optimal control methods, depends on an adequate initial guess, which is often hard to find, especially for very-low-thrust trajectories that necessitate many revolutions around the sun. The obtained solutions are typically close to the initial guess that is rarely close to the (unknown) global optimum. Within this paper, trajectory optimization problems are attacked from the perspective of artificial intelligence and machine learning. Inspired by natural archetypes, a smart global method for low-thrust trajectory optimization is proposed that fuses artificial neural networks and evolutionary algorithms into so-called evolutionary neurocontrollers. This novel method runs without an initial guess and does not require the attendance of an expert in astrodynamics and optimal control theory. This paper details how evolutionary neurocontrol works and how it could be implemented. The performance of the method is assessed for three different interplanetary missions with a thrust to mass ratio <0.15mN/kg (solar sail and nuclear electric).
The recently proposed NASA and ESA missions to Saturn and Jupiter pose difficult tasks to mission designers because chemical propulsion scenarios are not capable of transferring heavy spacecraft into the outer solar system without the use of gravity assists. Thus our developed mission scenario based on the joint NASA/ESA Titan Saturn System Mission baselines solar electric propulsion to improve mission flexibility and transfer time. For the calculation of near-globally optimal low-thrust trajectories, we have used a method called Evolutionary Neurocontrol, which is implemented in the low-thrust trajectory optimization software InTrance. The studied solar electric propulsion scenario covers trajectory optimization of the interplanetary transfer including variations of the spacecraft's thrust level, the thrust unit's specific impulse and the solar power generator power level. Additionally developed software extensions enabled trajectory optimization with launcher-provided hyperbolic excess energy, a complex solar power generator model and a variable specific impulse ion engine model. For the investigated mission scenario, Evolutionary Neurocontrol yields good optimization results, which also hold valid for the more elaborate spacecraft models. Compared to Cassini/Huygens, the best found solutions have faster transfer times and a higher mission flexibility in general.
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.
Flight times to the heliopause using a combination of solar and radioisotope electric propulsion
(2011)
We investigate the interplanetary flight of a low-thrust space probe to the heliopause,located at a distance of about 200 AU from the Sun. Our goal was to reach this distance within the 25 years postulated by ESA for such a mission (which is less ambitious than the 15-year goal set by NASA). Contrary to solar sail concepts and combinations of allistic and electrically propelled flight legs, we have investigated whether the set flight time limit could also be kept with a combination of solar-electric propulsion and a second, RTG-powered upper stage. The used ion engine type was the RIT-22 for the first stage and the RIT-10 for the second stage. Trajectory optimization was carried out with the low-thrust optimization program InTrance, which implements the method of Evolutionary Neurocontrol,using Artificial Neural Networks for spacecraft steering and Evolutionary Algorithms to optimize the Neural Networks’ parameter set. Based on a parameter space study, in which the number of thrust units, the unit’s specific impulse, and the relative size of the solar power generator were varied, we have chosen one configuration as reference. The transfer time of this reference configuration was 29.6 years and the fastest one, which is technically
more challenging, still required 28.3 years. As all flight times of this parameter study were longer than 25 years, we further shortened the transfer time by applying a launcher-provided hyperbolic excess energy up to 49 km2/s2. The resulting minimal flight time for the reference configuration was then 27.8 years. The following, more precise optimization to a launch with the European Ariane 5 ECA rocket reduced the transfer time to 27.5 years. This is the fastest mission design of our study that is flexible enough to allow a launch every
year. The inclusion of a fly-by at Jupiter finally resulted in a flight time of 23.8 years,which is below the set transfer-time limit. However, compared to the 27.5-year transfer,this mission design has a significantly reduced launch window and mission flexibility if the
escape direction is restricted to the heliosphere’s “nose".
Attitude and Orbital Dynamics Modeling for an Uncontrolled Solar-Sail Experiment in Low-Earth Orbit
(2015)
The search for life on Mars and in the Solar System - strategies, logistics and infrastructures
(2018)
The question "Are we alone in the Universe?" is perhaps the most fundamental one that affects mankind. How can we address the search for life in our Solar System? Mars, Enceladus and Europa are the focus of the search for life outside the terrestrial biosphere. While it is more likely to find remnants of life (fossils of extinct life) on Mars because of its past short time window of the surface habitability, it is probably more likely to find traces of extant life on the icy moons and ocean worlds of Jupiter and Saturn. Nevertheless, even on Mars there could still be a chance to find extant life in niches near to the surface or in just discovered subglacial lakes beneath the South Pole ice cap. Here, the different approaches for the detection of traces of life in the form of biosignatures including pre-biotic molecules will be presented. We will outline the required infrastructure for this enterprise and give examples of future mission concepts to investigate the presence of life on other planets and moons. Finally, we will provide suggestions on methods, techniques, operations and strategies for preparation and realization of future life detection missions.