5,743 research outputs found

    Evolutionary Optimization for Active Debris Removal Mission Planning

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    Active debris removal missions require an accurate planning for maximizing mission payout, by reaching the maximum number of potential orbiting targets in a given region of space. Such a problem is known to be computationally demanding and the present paper provides a technique for preliminary mission planning based on a novel evolutionary optimization algorithm, which identifies the best sequence of debris to be captured and/or deorbited. A permutation-based encoding is introduced, which may handle multiple spacecraft trajectories. An original archipelago structure is also adopted for improving algorithm capabilities to explore the search space. As a further contribution, several crossover and mutation operators and migration schemes are tested in order to identify the best set of algorithm parameters for the considered class of optimization problems. The algorithm is numerically tested for a fictitious cloud of debris in the neighborhood of Sun-synchronous orbits, including cases with multiple chasers

    Technology for the Future: In-Space Technology Experiments Program, part 2

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    The purpose of the Office of Aeronautics and Space Technology (OAST) In-Space Technology Experiments Program In-STEP 1988 Workshop was to identify and prioritize technologies that are critical for future national space programs and require validation in the space environment, and review current NASA (In-Reach) and industry/ university (Out-Reach) experiments. A prioritized list of the critical technology needs was developed for the following eight disciplines: structures; environmental effects; power systems and thermal management; fluid management and propulsion systems; automation and robotics; sensors and information systems; in-space systems; and humans in space. This is part two of two parts and contains the critical technology presentations for the eight theme elements and a summary listing of critical space technology needs for each theme

    CAMELOT - computational-analytical multi-fidelity low-thrust optimisation toolbox

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    CAMELOT (Computational-Analytical Multi-fidelity Low-thrust Optimisation Toolbox) is a toolbox for the fast preliminary design and optimisation of low-thrust trajectories. It solves highly complex combinatorial problems to plan multi-target missions characterised by long spirals including different perturbations. In order to do so, CAMELOT implements a novel multi-fidelity approach combining analytical surrogate modelling and accurate computational estimations of the mission cost. Decisions are then made by using two pptimisation engines included in the toolbox, a single objective global optimiser and a combinatorial optimisation algorithm. CAMELOT has been applied to a variety of applications: from the design of interplanetary trajectories to the optimal deorbiting of space debris, from the deployment of constellations to on-orbit servicing. In this paper the main elements of CAMELOT are described and two space mission design problems solved using the toolbox are described

    Space resources. Volume 1: Scenarios

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    A number of possible future paths for space exploration and development are presented. The topics covered include the following: (1) the baseline program; (2) alternative scenarios utilizing nonterrestrial resources; (3) impacts of sociopolitical conditions; (4) common technologies; and issues for further study
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