Parallelization of a relaxation scheme modelling the bedload transport of sediments in shallow water flow

In this work we are interested in numerical simulations for bedload erosion processes. We present a relaxation solver that we apply to moving dunes test cases in one and two dimensions. In particular we retrieve the so-called anti-dune process that is well described in the experiments. In order to be able to run 2D test cases with reasonable CPU time, we also describe and apply a parallelization procedure by using domain decomposition based on the classical MPI library.Comment: 19 page

Autonomous orbit determination and navigation for formations of CubeSats beyond LEO

This paper investigates the use of the Time Of Arrival (TOA) and Doppler shift to allow a small formation of CubeSats to navigate beyond low Earth orbit (LEO). The idea is to use a one way communication, from one or more ground station to two or more CubeSats, to reconstruct an estimation of the position and velocity of the formation with respect to Earth. The paper considers the use of the difference in TOA and Doppler measurements to mitigate the error introduced by the onboard clock. These measurements are combined with inter-satellite distance and velocity measurements based on a two-way communication between pairs of spacecraft. The paper will provide an estimation of the error in position and velocity that can be obtained by a combination of these measurements. The reference case for these analyses will be a mission to the Moon

Study of the Lorentz force on debris with high area-to-mass ratios

The presence of plasma in Low Earth Orbit and above can be the cause of electrostatic charging on space objects with a conductive surface, which then become subject to the Lorentz force induced by the magnetic field. This paper investigates it effects on the trajectory of orbital debris with a high area-to-mass ratio, as their course is particularly influenced by non-gravitational perturbations such as atmospheric drag or solar radiation pressure. Depending on the altitude (low or medium) and the available data, different charging models have been coupled with an orbit propagator, featuring a range of non-Keplerian accelerations and both three and six degrees-of-freedom dynamics. In particular, there has been a focus on long-term effects by simulating charged versus non-charged objects over the time span of years or decades

De-orbiting and re-entry analysis with generalised intrusive polynomial expansions

Generalised Intrusive Polynomial Expansion (GIPE) is a novel method for the propagation of multidimensional compact sets through dynamical systems. It generalises the more widely-known Taylor Differential Algebra in that it allows the use of generic polynomial representations of a multi-dimensional set. In particular the paper proposes the use of truncated Tchebycheff series. Unlike Taylor expansions, that are not generally convergent, Tchebycheff expansions provide fast uniform convergence with relaxed continuity and smoothness requirements, guaranteeing near-minimax approximation. This methodology has proven to be competitive for uncertainty propagation in orbital dynamics, especially when dealing with a large number of uncertain variables. Moreover, it provides the user with a complete polynomial representation of the uncertain region at any point of the propagation, allowing remarkable gain of insight into the underlying properties of the uncertain dynamics. The paper presents the application of the GIPE approach to the end-of-life analysis of Low Earth Orbit satellites, with special emphasis on the case of the de-orbiting and re-entry of GOCE and the de-orbiting of objects with high area to mass ratio. The effect of various sources of uncertainty on the end-of-life dynamics is thus analysed, such as the drag model or the accuracy of the initial orbit determination

Analysis of the de-orbiting and re-entry of space objects with high area to mass ratio

This paper presents a preliminary analysis of the de-orbiting and re-entry dynamics of space objects with a large area to mass ratio. Two different classes of objects are considered: fragments of satellites (like solar panels and pieces of thermal blankets) and complete nano-satellites with passive de-orbiting devices like a drag sail. Different sources of uncertainty are considered including atmospheric density variability with latitude and solar cycles, aerodynamic properties of the object, light pressure, initial conditions. The coupling of the uncertainty in the aerodynamic forces and attitude motion is investigated to understand if low fidelity three degrees of freedom models can be used in place of more expensive high fidelity models to make predictions on the re-entry time. Modern uncertainty propagation and quantification tools are used to assess the effect of uncertainty on the re-entry time and study the dependency on a number of key parameters

Artificial intelligence in support to space traffic management

This paper presents an Artificial Intelligence-based decision support system to assist ground operators to plan and implement collision avoidance manoeuvres. When a new conjunction is expected, the system provides the operator with an optimal manoeuvre and an analysis of the possible outcomes. Machine learning techniques are combined with uncertainty quantification and orbital mechanics calculations to support an optimal and reliable management of space traffic. A dataset of collision avoidance manoeuvres has been created by simulating a range of scenarios in which optimal manoeuvres (in the sense of optimal control) are applied to reduce the collision probability between pairs of objects. The consequences of the execution of a manoeuvre are evaluated to assess its benefits against its cost. Consequences are quantified in terms of the need for additional manoeuvres to avoid subsequent collisions. By using this dataset, we train predictive models that forecast the risk of avoiding new collisions, and use them to recommend alternative manoeuvres that may be globally better for the space environment

A Power Series Expansion based Method to compute the Probability of Collision for Short-term Space Encounters

Rapport LAAS n° 15072This article provides a new method for computing the probability of collision between two spherical space objects involved in a short-term encounter under Gaussian-distributed uncertainty. In this model of conjunction, classical assumptions reduce the probability of collision to the integral of a two-dimensional Gaussian probability density function over a disk. The computational method presented here is based on an analytic expression for the integral, derived by use of Laplace transform and D-finite functions properties. The formula has the form of a product between an exponential term and a convergent power series with positive coefficients. Analytic bounds on the truncation error are also derived and are used to obtain a very accurate algorithm. Another contribution is the derivation of analytic bounds on the probability of collision itself, allowing for a very fast and - in most cases - very precise evaluation of the risk. The only other analytical method of the literature - based on an approximation - is shown to be a special case of the new formula. A numerical study illustrates the efficiency of the proposed algorithms on a broad variety of examples and favorably compares the approach to the other methods of the literature

Interpreting the cosmic far-infrared background anisotropies using a gas regulator model

Cosmic far-infrared background (CFIRB) is a powerful probe of the history of star formation rate (SFR) and the connection between baryons and dark matter across cosmic time. In this work, we explore to which extent the CFIRB anisotropies can be reproduced by a simple physical framework for galaxy evolution, the gas regulator (bathtub) model. This model is based on continuity equations for gas, stars, and metals, taking into account cosmic gas accretion, star formation, and gas ejection. We model the large-scale galaxy bias and small-scale shot noise self-consistently, and we constrain our model using the CFIRB power spectra measured by Planck. Because of the simplicity of the physical model, the goodness of fit is limited. We compare our model predictions with the observed correlation between CFIRB and gravitational lensing, bolometric infrared luminosity functions, and submillimetre source counts. The strong clustering of CFIRB indicates a large galaxy bias, which corresponds to haloes of mass 1012.5 M⊙ at z = 2, higher than the mass associated with the peak of the star formation efficiency. We also find that the far-infrared luminosities of haloes above 1012 M⊙ are higher than the expectation from the SFR observed in ultraviolet and optical surveys

A risk-aware architecture for resilient spacecraft operations

In this paper we discuss a resilient, risk-aware software architecture for onboard, real-time autonomous operations that is intended to robustly handle uncertainty in space-craft behavior within hazardous and unconstrained environments, without unnecessarily increasing complexity. This architecture, the Resilient Spacecraft Executive (RSE), serves three main functions: (1) adapting to component failures to allow graceful degradation, (2) accommodating environments, science observations, and spacecraft capabilities that are not fully known in advance, and (3) making risk-aware decisions without waiting for slow ground-based reactions. This RSE is made up of four main parts: deliberative, habitual, and reflexive layers, and a state estimator that interfaces with all three. We use a risk-aware goal-directed executive within the deliberative layer to perform risk-informed planning, to satisfy the mission goals (specified by mission control) within the specified priorities and constraints. Other state-of-the-art algorithms to be integrated into the RSE include correct-by-construction control synthesis and model-based estimation and diagnosis. We demonstrate the feasibility of the architecture in a simple implementation of the RSE for a simulated Mars rover scenario

GTOC 9 : Results from University of Strathclyde (team Strath++)

The design and planning of space trajectories is a challenging problem in mission analysis. In the last years global optimisation techniques have proven to be a valuable tool for automating the design process that otherwise would mostly rely on engineers’ expertise. The paper presents the optimisation approach and problem formulation proposed by the team Strathclyde++ to address the problem of the 9th edition of the Global Trajectory Optimisation Competition. While the solution approach is introduced for the design of a set of multiple debris removal missions, the solution idea can be generalised to a wider set of trajectory design problems that have a similar structure