Numerical integration errors in deep space orbit determination

Il progetto di tesi è stato sviluppato durante il periodo di tirocinio svolto all’interno del “Laboratorio di Radio Scienza ed Esplorazione Planetaria” da un'esperienza da cui prende il nome lo stesso elaborato: ”Numerical integration errors in deep space orbit determination”. Lo scopo del sopraccitato laboratorio è stato quello di studiare in modo approfondito il problema kepleriano dei due corpi, per poi passare ad un’analisi del problema dei tre corpi e successivamente a n corpi (con particolare attenzione alle orbite dei satelliti medicei di Giove). Lo studio è stato affiancato ad un costante utilizzo della piattaforma di programmazione Matlab per l’elaborazione e la stesura di codici per il calcolo di traiettorie orbitali ed errori numerici. Infatti, il fulcro del lavoro è stato proprio il confronto di vari integratori e degli errori numerici derivanti dall’integrazione. Nella tesi, dapprima, viene introdotto il sistema Gioviano, vengono presentati i satelliti medicei, delineate le caratteristiche fisiche fondamentali e i principali motivi che portano ad avere particolare interesse nel conoscere lo sviluppo orbitale di tale sistema. In seguito, l'elaborato, dopo una dettagliata descrizione teorica del problema dei due corpi, presenta un codice per la rappresentazione di orbite kepleriane e il calcolo dei relativi errori commessi dal metodo numerico rispetto a quello analitico. Nell'ultimo capitolo, invece, il problema è esteso a più corpi dotati di massa e a tal proposito viene proposto un codice per la rappresentazione delle orbite descritte nel tempo da n corpi, date le condizioni iniziali, e il calcolo dei rispettivi errori nel sistema di riferimento (r,t,n). In merito a ciò, vengono infine testati diversi integratori per cercare quello con le migliori performance e sono poi analizzati alcuni parametri in input al problema per verificare sotto quali condizioni l’integratore lavora meglio.

Automatic classification of stellar orbits in axisymmetric potentials

Within the classification of orbits in axisymmetric stellar systems, we present a new algorithm able to automatically classify the orbits according to their nature. The algorithm involves the application of the correlation integral method to the surface of section of the orbit; fitting the cumulative distribution function built with the consequents in the surface of section of the orbit, we can obtain the value of its logarithmic slope m which is directly related to the orbit’s nature: for slopes m ≈ 1 we expect the orbit to be regular, for slopes m ≈ 2 we expect it to be chaotic. With this method we have a fast and reliable way to classify orbits and, furthermore, we provide an analytical expression of the probability that an orbit is regular or chaotic given the logarithmic slope m of its correlation integral. Although this method works statistically well, the underlying algorithm can fail in some cases, misclassifying individual orbits under some peculiar circumstances. The performance of the algorithm benefits from a rich sampling of the traces of the SoS, which can be obtained with long numerical integration of orbits. Finally we note that the algorithm does not differentiate between the subtypes of regular orbits: resonantly trapped and untrapped orbits. Such distinction would be a useful feature, which we leave for future work. Since the result of the analysis is a probability linked to a Gaussian distribution, for the very definition of distribution, some orbits even if they have a certain nature are classified as belonging to the opposite class and create the probabilistic tails of the distribution. So while the method produces fair statistical results, it lacks in absolute classification precision.

Study of a wind-wave numerical model and its integration with ocean and oil-spill numerical models

The ability to represent the transport and fate of an oil slick at the sea surface is a formidable task. By using an accurate numerical representation of oil evolution and movement in seawater, the possibility to asses and reduce the oil-spill pollution risk can be greatly improved. The blowing of the wind on the sea surface generates ocean waves, which give rise to transport of pollutants by wave-induced velocities that are known as Stokes’ Drift velocities. The Stokes’ Drift transport associated to a random gravity wave field is a function of the wave Energy Spectra that statistically fully describe it and that can be provided by a wave numerical model. Therefore, in order to perform an accurate numerical simulation of the oil motion in seawater, a coupling of the oil-spill model with a wave forecasting model is needed. In this Thesis work, the coupling of the MEDSLIK-II oil-spill numerical model with the SWAN wind-wave numerical model has been performed and tested. In order to improve the knowledge of the wind-wave model and its numerical performances, a preliminary sensitivity study to different SWAN model configuration has been carried out. The SWAN model results have been compared with the ISPRA directional buoys located at Venezia, Ancona and Monopoli and the best model settings have been detected. Then, high resolution currents provided by a relocatable model (SURF) have been used to force both the wave and the oil-spill models and its coupling with the SWAN model has been tested. The trajectories of four drifters have been simulated by using JONSWAP parametric spectra or SWAN directional-frequency energy output spectra and results have been compared with the real paths traveled by the drifters.