2,804 research outputs found

    The Comet Interceptor Mission

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    Here we describe the novel, multi-point Comet Interceptor mission. It is dedicated to the exploration of a little-processed long-period comet, possibly entering the inner Solar System for the first time, or to encounter an interstellar object originating at another star. The objectives of the mission are to address the following questions: What are the surface composition, shape, morphology, and structure of the target object? What is the composition of the gas and dust in the coma, its connection to the nucleus, and the nature of its interaction with the solar wind? The mission was proposed to the European Space Agency in 2018, and formally adopted by the agency in June 2022, for launch in 2029 together with the Ariel mission. Comet Interceptor will take advantage of the opportunity presented by ESA’s F-Class call for fast, flexible, low-cost missions to which it was proposed. The call required a launch to a halo orbit around the Sun-Earth L2 point. The mission can take advantage of this placement to wait for the discovery of a suitable comet reachable with its minimum ΔV capability of 600 ms−1. Comet Interceptor will be unique in encountering and studying, at a nominal closest approach distance of 1000 km, a comet that represents a near-pristine sample of material from the formation of the Solar System. It will also add a capability that no previous cometary mission has had, which is to deploy two sub-probes – B1, provided by the Japanese space agency, JAXA, and B2 – that will follow different trajectories through the coma. While the main probe passes at a nominal 1000 km distance, probes B1 and B2 will follow different chords through the coma at distances of 850 km and 400 km, respectively. The result will be unique, simultaneous, spatially resolved information of the 3-dimensional properties of the target comet and its interaction with the space environment. We present the mission’s science background leading to these objectives, as well as an overview of the scientific instruments, mission design, and schedule

    Learning and Control of Dynamical Systems

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    Despite the remarkable success of machine learning in various domains in recent years, our understanding of its fundamental limitations remains incomplete. This knowledge gap poses a grand challenge when deploying machine learning methods in critical decision-making tasks, where incorrect decisions can have catastrophic consequences. To effectively utilize these learning-based methods in such contexts, it is crucial to explicitly characterize their performance. Over the years, significant research efforts have been dedicated to learning and control of dynamical systems where the underlying dynamics are unknown or only partially known a priori, and must be inferred from collected data. However, much of these classical results have focused on asymptotic guarantees, providing limited insights into the amount of data required to achieve desired control performance while satisfying operational constraints such as safety and stability, especially in the presence of statistical noise. In this thesis, we study the statistical complexity of learning and control of unknown dynamical systems. By utilizing recent advances in statistical learning theory, high-dimensional statistics, and control theoretic tools, we aim to establish a fundamental understanding of the number of samples required to achieve desired (i) accuracy in learning the unknown dynamics, (ii) performance in the control of the underlying system, and (iii) satisfaction of the operational constraints such as safety and stability. We provide finite-sample guarantees for these objectives and propose efficient learning and control algorithms that achieve the desired performance at these statistical limits in various dynamical systems. Our investigation covers a broad range of dynamical systems, starting from fully observable linear dynamical systems to partially observable linear dynamical systems, and ultimately, nonlinear systems. We deploy our learning and control algorithms in various adaptive control tasks in real-world control systems and demonstrate their strong empirical performance along with their learning, robustness, and stability guarantees. In particular, we implement one of our proposed methods, Fourier Adaptive Learning and Control (FALCON), on an experimental aerodynamic testbed under extreme turbulent flow dynamics in a wind tunnel. The results show that FALCON achieves state-of-the-art stabilization performance and consistently outperforms conventional and other learning-based methods by at least 37%, despite using 8 times less data. The superior performance of FALCON arises from its physically and theoretically accurate modeling of the underlying nonlinear turbulent dynamics, which yields rigorous finite-sample learning and performance guarantees. These findings underscore the importance of characterizing the statistical complexity of learning and control of unknown dynamical systems.</p

    A Methodology to Enable Concurrent Trade Space Exploration of Space Campaigns and Transportation Systems

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    Space exploration campaigns detail the ways and means to achieve goals for our human spaceflight programs. Significant strategic, financial, and programmatic investments over long timescales are required to execute them, and therefore must be justified to decision makers. To make an informed down-selection, many alternative campaign designs are presented at the conceptual-level, as a set and sequence of individual missions to perform that meets the goals and constraints of the campaign, either technical or programmatic. Each mission is executed by in-space transportation systems, which deliver either crew or cargo payloads to various destinations. Design of each of these transportation systems is highly dependent on campaign goals and even small changes in subsystem design parameters can prompt significant changes in the overall campaign strategy. However, the current state of the art describes campaign and vehicle design processes that are generally performed independently, which limits the ability to assess these sensitive impacts. The objective of this research is to establish a methodology for space exploration campaign design that represents transportation systems as a collection of subsystems and integrates its design process to enable concurrent trade space exploration. More specifically, the goal is to identify existing campaign and vehicle design processes to use as a foundation for improvement and eventual integration. In the past two decades, researchers have adopted terrestrial logistics and supply chain optimization processes to the space campaign design problem by accounting for the challenges that accompany space travel. Fundamentally, a space campaign is formulated as a network design problem where destinations, such as orbits or surfaces of planetary bodies, are represented as nodes with the routes between them as arcs. The objective of this design problem is to optimize the flow of commodities within network using available transport systems. Given the dynamic nature and the number of commodities involved, each campaign can be modeled as a time-expanded, generalized multi-commodity network flow and solved using a mixed integer programming algorithm. To address the challenge of modeling complex concept of operations (ConOps), this formulation was extended to include paths as a set of arcs, further enabling the inclusion of vehicle stacks and payload transfers in the campaign optimization process. Further, with the focus of transportation system within this research, the typical fixed orbital nodes in the logistics network are modified to represent ranges of orbits, categorized by their characteristic energy. This enables the vehicle design process to vary each orbit in the mission as it desires to find the best one per vehicle. By extension, once integrated, arc costs of dV and dT are updated each iteration. Once campaign goals and external constraints are included, the formulated campaign design process generates alternatives at the conceptual level, where each one identifies the optimal set and sequence of missions to perform. Representing transportation systems as a collection of subsystems introduces challenges in the design of each vehicle, with a high degree of coupling between each subsystem as well as the driving mission. Additionally, sizing of each subsystem can have many inputs and outputs linked across the system, resulting in a complex, multi-disciplinary analysis, and optimization problem. By leveraging the ontology within the Dynamic Rocket Equation Tool, DYREQT, this problem can be solved rapidly by defining each system as a hierarchy of elements and subelements, the latter corresponding to external subsystem-level sizing models. DYREQT also enables the construction of individual missions as a series of events, which can be directly driven and generated by the mission set found by the campaign optimization process. This process produces sized vehicles iteratively by using the mission input, subsystem level sizing models, and the ideal rocket equation. By conducting a literature review of campaign and vehicle design processes, the different pieces of the overall methodology are identified, but not the structure. The specific iterative solver, the corresponding convergence criteria, and initialization scheme are the primary areas for experimentation of this thesis. Using NASA’s reference 3-element Human Landing System campaign, the results of these experiments show that the methodology performs best with the vehicle sizing and synthesis process initializing and a path guess that minimizes dV. Further, a converged solution is found faster using non-linear Gauss Seidel fixed point iteration over Jacobi and set of convergence criteria that covers vehicle masses and mission data. To show improvement over the state of the art, and how it enables concurrent trade studies, this methodology is used at scale in a demonstration using NASA’s Design Reference Architecture 5.0. The LH2 Nuclear Thermal Propulsion (NTP) option is traded with NH3and H2O at the vehicle-level as a way to show the impacts of alternative propellants on the vehicle sizing and campaign strategy. Martian surface stay duration is traded at the campaign-level through two options: long-stay and short-stay. The methodology was able to produce four alternative campaigns over the course of two weeks, which provided data about the launch and aggregation strategy, mission profiles, high-level figures of merit, and subsystem-level vehicle sizes for each alternative. Expectedly, with their lower specific impulses, alternative NTP propellants showed significant growth in the overall mass required to execute each campaign, subsequently represented the number of drop tanks and launches. Further, the short-stay campaign option showed a similar overall mass required compared to its long-stay counterpart, but higher overall costs even given the fewer elements required. Both trade studies supported the overall hypothesis and that integrating the campaign and vehicle design processes addresses the coupling between then and directly shows the impacts of their sensitivities on each other. As a result, the research objective was fulfilled by producing a methodology that was able to address the key gaps identified in the current state of the art.Ph.D

    The Multiview Observatory for Solar Terrestrial Science (MOST)

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    We report on a study of the Multiview Observatory for Solar Terrestrial Science (MOST) mission that will provide comprehensive imagery and time series data needed to understand the magnetic connection between the solar interior and the solar atmosphere/inner heliosphere. MOST will build upon the successes of SOHO and STEREO missions with new views of the Sun and enhanced instrument capabilities. This article is based on a study conducted at NASA Goddard Space Flight Center that determined the required instrument refinement, spacecraft accommodation, launch configuration, and flight dynamics for mission success. MOST is envisioned as the next generation great observatory positioned to obtain three-dimensional information of large-scale heliospheric structures such as coronal mass ejections, stream interaction regions, and the solar wind itself. The MOST mission consists of 2 pairs of spacecraft located in the vicinity of Sun-Earth Lagrange points L4 (MOST1, MOST3) and L5 (MOST2 and MOST4). The spacecraft stationed at L4 (MOST1) and L5 (MOST2) will each carry seven remote-sensing and three in-situ instrument suites. MOST will also carry a novel radio package known as the Faraday Effect Tracker of Coronal and Heliospheric structures (FETCH). FETCH will have polarized radio transmitters and receivers on all four spacecraft to measure the magnetic content of solar wind structures propagating from the Sun to Earth using the Faraday rotation technique. The MOST mission will be able to sample the magnetized plasma throughout the Sun-Earth connected space during the mission lifetime over a solar cycle.Comment: 42 pages, 19 figures, 8 tables, to appear in J. Atmospheric and Solar Terrestrial Physic

    The dynamics and control of large space structures with distributed actuation

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    Future large space structures are likely to be constructed at much greater length-scales, and lower areal mass densities than has been achieved to-date. This could be enabled by ongoing developments in on-orbit manufacturing, whereby large structures are 3D-printed in space from raw feedstock materials. This thesis proposes and analyses a number of attitude control strategies which could be adopted for this next generation of ultra-lightweight, large space structures. Each of the strategies proposed makes use of distributed actuation, which is demonstrated early in the thesis to reduce structural deformations during attitude manoeuvres. All of the proposed strategies are considered to be particularly suitable for structures which are 3d-printed on-orbit, due to the relative simplicity of the actuators and ease with which the actuator placement or construction could be integrated with the on-orbit fabrication of the structure itself. The first strategy proposed is the use of distributed arrays of magnetorquer rods. First, distributed torques are shown to effectively rotate highly flexible structures. This is compared with torques applied to the centre-of-mass of the structure, which cause large surface deformations and can fail to enact a rotation. This is demonstrated using a spring-mass model of a planar structure with embedded actuators. A torque distribution algorithm is then developed to control an individually addressable array of actuators. Attitude control simulations are performed, using the array to control a large space structure, again modelled as a spring-mass system. The attitude control system is demonstrated to effectively detumble a representative 75×75m flexible structure, and perform slew manoeuvres, in the presence of both gravity-gradient torques and a realistic magnetic field model. The development of a Distributed Magnetorquer Demonstration Platform is then presented, a laboratory-scale implementation of the distributed magnetorquer array concept. The platform consists of 48 addressable magnetorquers, arranged with two perpendicular torquers at the nodes of a 5×5 grid. The control algorithms proposed previously in the thesis are implemented and tested on this hardware, demonstrating the practical feasibility of the concept. Results of experiments using a spherical air bearing and Helmholtz cage are presented, demonstrating rest-to-rest slew manoeuvres and detumbling around a single axis using the developed algorithms. The next attitude control strategy presented is the use of embedded current loops, conductive pathways which can be integrated with a spacecraft support structure and used to generate control torques through interaction with the Earth’s magnetic field. Length-scaling laws are derived by determining what fraction of a planar spacecraft’s mass would need to be allocated to the conductive current loops in order to produce a torque at least as large as the gravity gradient torque. Simulations are then performed of a flexible truss structure, modelled as a spring-mass system, for a range of structural flexibilities and a variety of current loop geometries. Simulations demonstrate rotation of the structure via the electromagnetic force on the current carrying elements, and are also used to characterise the structural deformations caused by the various current loop geometries. An attitude control simulation is then performed, demonstrating a 90◦ slew manoeuvre of a 250×250 m flexible structure through the use of three orthogonal sets of current loops embedded within the spacecraft. The final concept investigated in this thesis is a self-reconfiguring OrigamiSat, where reconfiguration of the proposed OrigamiSat is triggered by changes in the local surface optical properties of an origami structure to harness the solar radiation pressure induced acceleration. OrigamiSats are origami spacecraft with reflective panels which, when flat, operate as a conventional solar sail. Shape reconfiguration, i.e. “folding” of the origami design, allows the OrigamiSat to change operational modes, performing different functions as per mission requirements. For example, a flat OrigamiSat could be reconfigured into the shape of a parabolic reflector, before returning to the flat configuration when required to again operate as a solar sail, providing propellant-free propulsion. Shape reconfiguration or folding of OrigamiSats through the use of surface reflectivity modulation is investigated in this thesis. First, a simplified, folding facet model is used to perform a length-scaling analysis, and then a 2d multibody dynamics simulation is used to demonstrate the principle of solar radiation presure induced folding. A 3d multibody dynamics simulation is then developed and used to demonstrate shape reconfiguration for different origami folding patterns. Here, the attitude dynamics and shape reconfiguration of OrigamiSats are found to be highly coupled, and thus present a challenge from a control perspective. The problem of integrating attitude and shape control of a Miura-fold pattern OrigamiSat through the use of variable reflectivity is then investigated, and a control algorithm developed which uses surface reflectivity modulation of the OrigamiSat facets to enact shape reconfiguration and attitude manoeuvres simultaneously

    Аванпроект далекомагістрльного пасажирського літака місткістю до 380 пасажирів

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    Робота публікується згідно наказу Ректора НАУ від 27.05.2021 р. №311/од "Про розміщення кваліфікаційних робіт здобувачів вищої освіти в репозиторії університету". Керівник роботи: доцент, к.т.н. Краснопольський Володимир СергійовичThis qualification paper is dedicated to the design of a long-range passenger aircraft with a seating capacity of up to 380 persons is the primary goal of this qualifying work. In the present investigation, engineering calculations were applied for identifying the meant aircraft's fundamental geometry and layout measures as well as the comparative examination of prototype aircraft to determine which design parameters were the most suitable and rational. A brand-new system for loading passenger luggage is presented by the special part. The purpose of the work is to make managing luggage easier for employees, speed up loading and unloading, and improve productivity in the baggage area. The work's results were made obtainable for use in the aviation industry and in specific aviation education programs.Ця кваліфікаційна робота присвячена розробці далекомагістрального пасажирського літака з максимальною вмістимістю 380 осіб. У цьому дослідженні було використано метод порівняльного аналізу прототипів літаків для вибору найнеобхідніших та обґрунтованих параметрів проектування літака. Крім того, були використані інженерні розрахунки для отримання основних геометричних та компонувальних характеристик проектуваного літака. У спеціальній частині цієї роботи презентовано новий механізм для навантаження пасажирського багажу, який має велике значення у зменшенні трудових навантажень на працівників, скороченні часу, необхідного для завантаження та розвантаження, а також підвищенні ефективності роботи у відділенні багажу. Практичне значення цієї кваліфікаційної роботи проявляється у поліпшенні продуктивності та швидкості роботи у відділенні багажу на довгих перельотах. Результати, які були представлені, можуть бути застосовані в навчальному процесі на спеціальностях, пов'язаних з авіацією, а також у авіаційній індустрії
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