Due to the continuous generation of new debris through collisional dynamics, accurately simulating the long-term evolution of a specific orbital environment has become increasingly time-consuming. Traditional deterministic collision detection methods exhibit superlinear complexity, which becomes impractical as the number of orbiting objects grows. Furthermore, the orbital dynamic is simulated with great accuracy even when the collision risk has a much lower frequency. An alternative approach, often regarded as state-of-the-art due to its computational efficiency, is the Cube Algorithm. Despite being probabilistic and based on the kinetic theory of gases, the Cube Algorithm offers linear complexity, making it suitable for long-term debris evolutionary models such as NASA's LEO-to-GEO Environment Debris model. Previous studies have examined the predictive capabilities of this algorithm, but as of now, there is no conclusive evidence validating its predictions against real-world data. Additionally, criticisms have been directed at the Algorithm's binning strategy, which may overlook potential collisions. This research aims to validate the Cube and investigate its possible sources of error. First, an extensive literature review was conducted to contextualize the problem within the scientific community. Then, two fully deterministic simulations of the low-Earth and Sun-synchronous environment were performed using open-source libraries developed by the Advanced Concepts Team of the European Space Agency. The number of collisions was counted deterministically and with the Cube, and the results were compared to identify potential discrepancies. In the second part of the thesis, an investigation into the sources of error in the Cube Algorithm was conducted. This involved analyzing the selection of hyperparameters, the assumptions of the gas kinetic theory, and the overestimation caused by satellites in formation flying. Finally, based on the results obtained from the deterministic simulations, the hyperparameters were reselected to ensure accurate results.
A causa della continua generazione di nuovi detriti attraverso dinamiche collisionarie, simulare accuratamente l'evoluzione a lungo termine di un determinato ambiente orbitale è diventato sempre più dispendioso in termini di tempo. I metodi deterministici di rilevamento delle collisioni presentano una complessità superlineare, che diventa impraticabile con l'aumento del numero di oggetti in orbita. Inoltre, la dinamica orbitale viene simulata con grande accuratezza anche quando il rischio di collisione ha una frequenza molto più bassa. Un approccio alternativo, spesso considerato all'avanguardia per la sua efficienza computazionale, è il Cube Algorithm. Nonostante sia probabilistico e basato sulla teoria cinetica dei gas, il Cube Algorithm offre una complessità lineare, rendendolo adatto ai modelli evolutivi a lungo termine di detriti, come il modello "LEO-to-GEO Environment Debris" della NASA. Studi precedenti hanno esaminato le capacità predittive di questo algoritmo, ma finora non ci sono prove conclusive che ne convalidino le previsioni rispetto ai dati reali. Inoltre, sono state mosse critiche alla strategia di binning spaziale dell'algoritmo, che potrebbe trascurare potenziali collisioni. Questa ricerca mira a validare l'algoritmo e ad investigare le sue possibili fonti di errore. Prima di tutto, è stata condotta una vasta revisione della letteratura per contestualizzare il problema all'interno della comunità scientifica. Successivamente, sono state eseguite due simulazioni completamente deterministiche dell'ambiente in orbita bassa terrestre e in orbita eliosincrona utilizzando librerie open-source sviluppate dal Advanced Concepts Team dell'Agenzia Spaziale Europea. Il numero di collisioni è stato conteggiato sia in modo deterministico che con il Cube, e i risultati sono stati confrontati per identificare eventuali discrepanze. Nella seconda parte della tesi è stata condotta un'indagine sulle fonti di errore dell'algoritmo. Questo ha comportato l'analisi della selezione degli iperparametri, delle assunzioni della teoria cinetica dei gas e della sovrastima nel numero delle collisioni causata dai satelliti in volo di formazione. Infine, basandosi sui risultati ottenuti dalle simulazioni deterministiche, gli iperparametri sono stati nuovamente selezionati per garantire risultati accurati.
Analysis and validation of the Cube Algorithm: assessing gas kinetic theory to model collision risk in long-term debris propagations
Facchinetti, Giovanni
2023/2024
Abstract
Due to the continuous generation of new debris through collisional dynamics, accurately simulating the long-term evolution of a specific orbital environment has become increasingly time-consuming. Traditional deterministic collision detection methods exhibit superlinear complexity, which becomes impractical as the number of orbiting objects grows. Furthermore, the orbital dynamic is simulated with great accuracy even when the collision risk has a much lower frequency. An alternative approach, often regarded as state-of-the-art due to its computational efficiency, is the Cube Algorithm. Despite being probabilistic and based on the kinetic theory of gases, the Cube Algorithm offers linear complexity, making it suitable for long-term debris evolutionary models such as NASA's LEO-to-GEO Environment Debris model. Previous studies have examined the predictive capabilities of this algorithm, but as of now, there is no conclusive evidence validating its predictions against real-world data. Additionally, criticisms have been directed at the Algorithm's binning strategy, which may overlook potential collisions. This research aims to validate the Cube and investigate its possible sources of error. First, an extensive literature review was conducted to contextualize the problem within the scientific community. Then, two fully deterministic simulations of the low-Earth and Sun-synchronous environment were performed using open-source libraries developed by the Advanced Concepts Team of the European Space Agency. The number of collisions was counted deterministically and with the Cube, and the results were compared to identify potential discrepancies. In the second part of the thesis, an investigation into the sources of error in the Cube Algorithm was conducted. This involved analyzing the selection of hyperparameters, the assumptions of the gas kinetic theory, and the overestimation caused by satellites in formation flying. Finally, based on the results obtained from the deterministic simulations, the hyperparameters were reselected to ensure accurate results.File | Dimensione | Formato | |
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2024_07_Facchinetti.pdf
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2024_07_Facchinetti_Executive_Summary.pdf
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https://hdl.handle.net/10589/223504