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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Development of a Low Earth Orbit Mission Preliminary Analysis Tool / Utveckling av ett verktyg för preliminär analys av rymduppdrag i låg jordbana

Staniscia, Giada January 2019 (has links)
The objective of this project is the development of a mission analysis tool for the nanosatellite company GomSpace Sweden. Although there are many existing software, they can be quite complicated and time consuming to use. The goal of this work is to build a simple app to be used at the earliest stages of space missions in order to obtain key figures of merit quickly and easily. By comparing results, assessing the feasibility of customer needs, analysing how various parameters affect each other, it enables immediate deeper understanding of the implications of the main design decisions that are taken at the very beginning of a mission. The tool shall aid the system engineering process of determining orbit manoeuvre capability specifically for CubeSat electric propulsion systems taking into account the most relevant factors for perturbation in Low Earth Orbit (LEO), i.e. atmospheric drag and Earth’s oblateness effects. The manoeuvres investigated are: orbit raising from an insert orbit to an operating orbit, orbit maintenance, deorbiting within the space debris mitigation guidelines and collision avoidance within the 12 to 24 hours that the system has to react. The manoeuvres cost is assessed in terms of Delta v requirements, propellant mass and transfer times. The tool was developed with MATLAB and packaged as a standalone Linux application. / Målet med detta examensarbete var att utveckla ett verktyg för missionsanalys för nanosatellitföretaget GomSpace Sweden. Det finns många andra mjukvaror för att nå samma mål men de är ofta komplicerade och tidskrävande. Det specifika målet var således att skapa en enkel applikation som kan användas i de tidiga stegen av utformning av rymduppdrag för att snabbt och enkelt få fram viktiga parametrar. Genom att jämföra resultat, uppskatta genomförbarheten av kundbehov och analysera hur olika parametrar påverkar varandra kan omedelbar förståelse erhållas rörande påverkan av designbeslut som tas i början av rymduppdragen. Verktyget ska stödja systemingenjörsprocessen genom att uppskatta banförflyttningskapacitet för elektriska framdrivningssystem för CubeSats och ta i beaktande de mest relevanta faktorerna gällande störningar i låg jordbana (LEO), i.e. atmosfäriskt motstånd och effekterna av Jordens form. De undersökta manövrarna är: banhöjning från injektionsbana till operationell bana, banunderhåll, bansänkning som följer riktlinjerna för rymdskrot och kollisionsundvikande inom de 12 till 24 timmar som systemet har på sig att reagera. Kostnaden för manövrarna är uppskattade genom DeltaV-krav, massan av bränslet och förflyttningstider. Verktyget utvecklades med MATLAB och paketerades som en fristående applikation i Linux.
2

LEVERAGING MACHINE LEARNING FOR ENHANCED SATELLITE TRACKING TO BOLSTER SPACE DOMAIN AWARENESS

Charles William Grey (16413678) 23 June 2023 (has links)
<p>Our modern society is more dependent on its assets in space now more than ever. For<br> example, the Global Positioning System (GPS) many rely on for navigation uses data from a<br> 24-satellite constellation. Additionally, our current infrastructure for gas pumps, cell phones,<br> ATMs, traffic lights, weather data, etc. all depend on satellite data from various constel-<br> lations. As a result, it is increasingly necessary to accurately track and predict the space<br> domain. In this thesis, after discussing how space object tracking and object position pre-<br> diction is currently being done, I propose a machine learning-based approach to improving<br> the space object position prediction over the standard SGP4 method, which is limited in<br> prediction accuracy time to about 24 hours. Using this approach, we are able to show that<br> meaningful improvements over the standard SGP4 model can be achieved using a machine<br> learning model built based on a type of recurrent neural network called a long short term<br> memory model (LSTM). I also provide distance predictions for 4 different space objects over<br> time frames of 15 and 30 days. Future work in this area is likely to include extending and<br> validating this approach on additional satellites to construct a more general model, testing a<br> wider range of models to determine limits on accuracy across a broad range of time horizons,<br> and proposing similar methods less dependent on antiquated data formats like the TLE.</p>
3

3D SOFT MATERIAL PRINTER FOR IN-SPACE MANUFACTURING EXPERIMENT

Albert john Patrick IV (15304819) 04 June 2024 (has links)
<p>    </p> <p>Additive manufacturing (or 3D printing) is one of the manufacturing processes which is currently being explored for its applicability under space boundary conditions, also known as in-space manufacturing. The space boundary conditions specifically affect material properties which in turn affect the printability of materials in space. Printing of soft materials in space is a novel application and the intent of this research was to print the softest of materials: edible materials, as a case study. 3D food printing is a novel food delivery method of using food products to either reproduce as a more aesthetically pleasing product or to print more nutrient-diverse foods. Launch of payload carrier and the boundary conditions of low Earth orbit including a vacuum environment, microgravity, temperature fluctuations, etc. These conditions make printing difficult, and my thesis is to overcome the boundary conditions (except microgravity) using a 3D soft material printer operating within a CubeSat. A CubeSat is a small satellite usually launched as an auxiliary payload used for basic Earth observation and radio communication. The printer must be able to survive launch and operation conditions, print within a simulated space environment, and adhere to the American Society for Testing and Materials (ASTM) specific definition of additive manufacturing. The 3D soft material printer was designed, fabricated, and tested using space and CubeSat boundary conditions for determining optimal design. Testing conditions including: (1) printing under Earth conditions showing it follows ASTM standards, (2) surviving NASA standards for vibration testing for microsatellites under launch conditions, (3) completing a print under a vacuum setting. The results of the testing would prove a small microsatellite could print in the vacuum of space and survive launch parameters. Further work would provide insight into the design of food printers being readily available in smaller sizes and its operability in microgravity condition. </p>

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