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The continuously growing number of objects orbiting around the Earth is expected to be accompanied by an increasing frequency of objects re-entering the Earth's atmosphere. Many of these re-entries will be uncontrolled, making their prediction challenging and subject to several uncertainties. Traditionally, re-entry predictions are based on the propagation of the object's dynamics using state-of-the-art modelling techniques for the forces acting on the object. However, modelling errors, particularly related to the prediction of atmospheric drag may result in poor prediction accuracies. In this context, we explore the possibility to perform a paradigm shift, from a physics-based approach to a data-driven approach. To this aim, we present the development of a deep learning model for the re-entry prediction of uncontrolled objects in Low Earth Orbit (LEO). The model is based on a modified version of the Sequence-to-Sequence architecture and is trained on the average altitude profile as derived from a set of Two-Line Element (TLE) data of over 400 bodies. The novelty of the work consists in introducing in the deep learning model, alongside the average altitude, three new input features: a drag-like coefficient (B*), the average solar index, and the area-to-mass ratio of the object. The developed model is tested on a set of objects studied in the Inter-Agency Space Debris Coordination Committee (IADC) campaigns. The results show that the best performances are obtained on bodies characterised by the same drag-like coefficient and eccentricity distribution as the training set.

This work presents a mission concept for in-orbit particle collection for sampling and exploration missions towards Near-Earth asteroids. Ejecta is generated via a small kinetic impactor and two possible collection strategies are investigated: collecting the particle along the anti-solar direction, exploiting the dynamical features of the L$_2$ Lagrangian point or collecting them while the spacecraft orbits the asteroid and before they re-impact onto the asteroid surface. Combining the dynamics of the particles in the Circular Restricted Three-Body Problem perturbed by Solar Radiation Pressure with models for the ejecta generation, we identify possible target asteroids as a function of their physical properties, by evaluating the potential for particle collection.

In recent years, due to the constant increase of the density of satellites in the space environment, several studies have been focused on the development of active and passive strategies to remove and mitigate space debris. This work investigates the feasibility of developing a reliable and fast approach to analyze the re-entry of a satellite. The numerical model interfaces the long-term orbit propagation obtained through semi-analytical methods with the atmospheric destructive re-entry phase exploiting the concept of overshoot boundary, highlighting the effect that an early break-off of the solar panels can have on the re-entry prediction. The re-entry of ESA's INTEGRAL mission is chosen as a test case to demonstrate the efficiency of the model in producing a complete simulation of the re-entry. The simulation of the destructive re-entry phase is produced using an object-oriented approach, paying attention to the demisability process of the most critical components of the space system., Comment: 10 pages, 9 figures, pre-proof of accepted article in Journal of Space Safety Engineering

The paper presents a re-entry analysis of Geosynchronous Orbit (GSO) satellites on disposal trajectories that enhance the effects of the Earth oblateness and lunisolar perturbations. These types of trajectories can lead to a natural re-entry of the spacecraft within 20 years. An analysis was performed to characterise the entry conditions for these satellites and the risk they can pose for people on the ground if disposal via re-entry is used. The paper first proposes a methodology to interface the long-term propagation used to study the evolution of the disposal trajectories and the destructive re-entry simulations used to assess the spacecraft casualty risk. This is achieved by revisiting the concept of overshoot boundary. The paper also presents the demisability and casualty risk analysis for a representative spacecraft configuration, showing that the casualty risk is greater than the 10$^{-4}$ threshold and that further actions should be taken to improve the compliance of these satellites in case of disposal via re-entry is used.

This work proposes a continuum-based approach for the propagation of uncertainties in the initial conditions and parameters for the analysis and prediction of spacecraft re-entries. Using the continuity equation together with the re-entry dynamics, the joint probability distribution of the uncertainties is propagated in time for specific sampled points. At each time instant, the joint probability distribution function is then reconstructed from the scattered data using a gradient-enhanced linear interpolation based on a simplicial representation of the state space. Uncertainties in the initial conditions at re-entry and in the ballistic coefficient for three representative test cases are considered: a three-state and a six-state steep Earth re-entry and a six-state unguided lifting entry at Mars. The paper shows the comparison of the proposed method with Monte Carlo based techniques in terms of quality of the obtained marginal distributions and runtime as a function of the number of samples used.

In the past few years, the interest towards the implementation of design-for-demise measures has increased steadily. Most mid-sized satellites currently launched and already in orbit fail to comply with the casualty risk threshold of 0.0001. Therefore, satellites manufacturers and mission operators need to perform a disposal through a controlled re-entry, which has a higher cost and increased complexity. Through the design-for-demise paradigm, this additional cost and complexity can be removed as the spacecraft is directly compliant with the casualty risk regulations. However, building a spacecraft such that most of its parts will demise may lead to designs that are more vulnerable to space debris impacts, thus compromising the reliability of the mission. In fact, the requirements connected to the demisability and the survivability are in general competing. Given this competing nature, trade-off solutions can be found, which favour the implementation of design-for-demise measures while still maintaining the spacecraft resilient to space debris impacts. A multi-objective optimisation framework has been developed by the authors in previous works. The framework's objective is to find preliminary design solutions considering the competing nature of the demisability and the survivability of a spacecraft since the early stages of the mission design. In this way, a more integrated design can be achieved. The present work focuses on the improvement of the multi-objective optimisation framework by including constraints. The paper shows the application of the constrained optimisation to two relevant examples: the optimisation of a tank assembly and the optimisation of a typical satellite configuration., Comment: Pre-print submitted to the Journal of Space Safety Engineering

The space environment around the Earth is populated by more than 130 million objects of 1 mm in size and larger, and future predictions shows that this amount is destined to increase, even if mitigation measures are implemented at a far better rate than today. These objects can hit and damage a spacecraft or its components. It is thus necessary to assess the risk level for a satellite during its mission lifetime. Few software packages perform this analysis, and most of them employ time-consuming ray-tracing methodology, where particles are randomly sampled from relevant distributions. In addition, they tend not to consider the risk associated with the secondary debris clouds. The paper presents the development of a vulnerability assessment model, which relies on a fully statistical procedure: the debris fluxes are directly used combining them with the concept of the vulnerable zone, avoiding the random sampling the debris fluxes. A novel methodology is presented to predict damage to internal components. It models the interaction between the components and the secondary debris cloud through basic geometric operations, considering mutual shielding and shadowing between internal components. The methodologies are tested against state-of-the-art software for relevant test cases, comparing results on external structures and internal components., Comment: Article accepted for pubblication in Advances in Space Research

Among the mitigation measures introduced to cope with the space debris issue there is the de-orbiting of decommissioned satellites. Guidelines for re-entering objects call for a ground casualty risk no higher than 0.0001. To comply with this requirement, satellites can be designed through a design-for-demise philosophy. Still, a spacecraft designed to demise has to survive the debris-populated space environment for many years. The demisability and the survivability of a satellite can both be influenced by a set of common design choices such as the material selection, the geometry definition, and the position of the components. Within this context, two models have been developed to analyse the demise and the survivability of satellites. Given the competing nature of the demisability and the survivability, a multi-objective optimisation framework was developed, with the aim to identify trade-off solutions for the preliminary design of satellites. As the problem is nonlinear and involves the combination of continuous and discrete variables, classical derivative based approaches are unsuited and a genetic algorithm was selected instead. The genetic algorithm uses the developed demisability and survivability criteria as the fitness functions of the multi-objective algorithm. The paper presents a test case, which considers the preliminary optimisation of tanks in terms of material, geometry, location, and number of tanks for a representative Earth observation mission. The configuration of the external structure of the spacecraft is fixed. Tanks were selected because they are sensitive to both design requirements: they represent critical components in the demise process and impact damage can cause the loss of the mission because of leaking and ruptures. The results present the possible trade off solutions, constituting the Pareto front obtained from the multi-objective optimisation., Comment: Paper accepted for publication in Aerospace Science and Technology