High Performance Propagation of Large Object Populations in Earth Orbits

Orbital debris is becoming an increasing problem for space flight missions. New satellite launches, explosions, collisions and other events cause a steady rise in the number of objects orbiting the Earth. It is therefore important to determine the future development of the object population, as well...

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Autor principal: Möckel, Marek
Formato: Online
Idioma:inglês
Publicado em: Logos Verlag Berlin 2021
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Acesso em linha:ONIX_20210408_9783832541651_3
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author Möckel, Marek
author_browse Möckel, Marek
author_facet Möckel, Marek
author_sort Möckel, Marek
collection Directory of Open Access Books
description Orbital debris is becoming an increasing problem for space flight missions. New satellite launches, explosions, collisions and other events cause a steady rise in the number of objects orbiting the Earth. It is therefore important to determine the future development of the object population, as well as the effectiveness of debris mitigation measures, in long-term simulations. Orbital propagation, the calculation of an object's movement in its orbit, poses a challenge for this research due to the high computation times of the complex perturbation models involved. With populations consisting of hundreds of thousands of objects as well as simulation time frames of up to 200 years, these calculations can take up hours of computation time. To speed up this process, the analytical propagator Ikebana is introduced in this work of applied computer science in engineering. The program runs on graphics processing units, hardware designed for massively parallel execution of up to thousands of concurrent threads. This reduces the overall run time for large object populations from hours to minutes. Porting software from a conventional CPU is not a trivial task and involves a number of potential pitfalls and optimization opportunities which are detailed in this work. The propagator is integrated into other applications via a generic, multi-platform interface specifically designed for this task. It allows to develop the propagator separately and integrate it into other tools as a plugin at run time. The interface's architecture serves as a design template for analytical propagation software.
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spelling doab-20.500.12854ir-644602024-04-14T10:27:37Z High Performance Propagation of Large Object Populations in Earth Orbits Möckel, Marek Space Debris GPU Computing High-Performance Computing Orbital Physics Analytical Models thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TR Transport technology and trades::TRC Automotive technology and trades Orbital debris is becoming an increasing problem for space flight missions. New satellite launches, explosions, collisions and other events cause a steady rise in the number of objects orbiting the Earth. It is therefore important to determine the future development of the object population, as well as the effectiveness of debris mitigation measures, in long-term simulations. Orbital propagation, the calculation of an object's movement in its orbit, poses a challenge for this research due to the high computation times of the complex perturbation models involved. With populations consisting of hundreds of thousands of objects as well as simulation time frames of up to 200 years, these calculations can take up hours of computation time. To speed up this process, the analytical propagator Ikebana is introduced in this work of applied computer science in engineering. The program runs on graphics processing units, hardware designed for massively parallel execution of up to thousands of concurrent threads. This reduces the overall run time for large object populations from hours to minutes. Porting software from a conventional CPU is not a trivial task and involves a number of potential pitfalls and optimization opportunities which are detailed in this work. The propagator is integrated into other applications via a generic, multi-platform interface specifically designed for this task. It allows to develop the propagator separately and integrate it into other tools as a plugin at run time. The interface's architecture serves as a design template for analytical propagation software. 2021-04-08T19:39:00Z 2021-04-08T19:39:00Z 2015 book ONIX_20210408_9783832541651_3 9783832541651 https://directory.doabooks.org/handle/20.500.12854/64460 eng image/jpeg Attribution-NonCommercial-NoDerivatives 4.0 International https://www.logos-verlag.de/cgi-bin/engbuchmid?isbn=4165&lng=eng&id= https://www.logos-verlag.de/ebooks/OA/978-3-8325-4165-1.pdf Logos Verlag Berlin Logos Verlag Berlin 10.30819/4165 10.30819/4165 04b263a1-7fba-4491-9eae-1c394ac42fc3 9783832541651 Logos Verlag Berlin 224 Berlin/Germany open access
spellingShingle Space Debris
GPU Computing
High-Performance Computing
Orbital Physics
Analytical Models
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TR Transport technology and trades::TRC Automotive technology and trades
Möckel, Marek
High Performance Propagation of Large Object Populations in Earth Orbits
title High Performance Propagation of Large Object Populations in Earth Orbits
title_full High Performance Propagation of Large Object Populations in Earth Orbits
title_fullStr High Performance Propagation of Large Object Populations in Earth Orbits
title_full_unstemmed High Performance Propagation of Large Object Populations in Earth Orbits
title_short High Performance Propagation of Large Object Populations in Earth Orbits
title_sort high performance propagation of large object populations in earth orbits
topic Space Debris
GPU Computing
High-Performance Computing
Orbital Physics
Analytical Models
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TR Transport technology and trades::TRC Automotive technology and trades
topic_facet Space Debris
GPU Computing
High-Performance Computing
Orbital Physics
Analytical Models
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TR Transport technology and trades::TRC Automotive technology and trades
url ONIX_20210408_9783832541651_3
work_keys_str_mv AT mockelmarek highperformancepropagationoflargeobjectpopulationsinearthorbits