738 research outputs found
Further evidence of long-term thermospheric density change using a new method of satellite ballistic coefficient estimation
No full textBuilding on work from previous studies a strong case is presented for the existence of a long-term density decline in the thermosphere. Using a specially developed orbital propagator to predict satellite orbit evolution, combined with a new and accurate method of determining satellite ballistic coefficients, a long-term thermospheric density change has been detected using a different method compared to previous studies. Over a 40-year period between the years 1970 and 2010, thermospheric density has appeared to reduce by a few percent per decade. However, the results do not show the thermospheric density reduction to vary linearly with time. Therefore, by analyzing the derived density data over varying solar activity levels, as well as performing a Fourier spectral analysis to highlight any periodicities, connections with physical phenomena, where possible, are propose
The fast debris evolution model
No full textThe ‘Particles-in-a-box’ (PIB) model introduced by Talent (1992) removed the need for computer-intensive Monte Carlo simulation to predict the gross characteristics of an evolving debris environment. The PIB model was described using a differential equation that allows the stability of the low Earth orbit (LEO) environment to be tested by a straightforward analysis of the equation’s coefficients. As part of an ongoing research effort to investigate more efficient approaches to evolutionary modelling and to develop a suite of educational tools, a new PIB model has been developed. The model, entitled Fast Debris Evolution (FADE), employs a first-order differential equation to describe the rate at which new objects ?10 cm are added and removed from the environment. Whilst Talent (1992) based the collision theory for the PIB approach on collisions between gas particles and adopted specific values for the parameters of the model from a number of references, the form and coefficients of the FADE model equations can be inferred from the outputs of future projections produced by high-fidelity models, such as the DAMAGE model. The FADE model has been implemented as a client-side, web-based service using JavaScript embedded within a HTML document. Due to the simple nature of the algorithm, FADE can deliver the results of future projections immediately in a graphical format, with complete user-control over key simulation parameters. Historical and future projections for the ?10 cm low Earth orbit (LEO) debris environment under a variety of different scenarios are possible, including business as usual, no future launches, post-mission disposal and remediation. A selection of results is presented with comparisons with predictions made using the DAMAGE environment model. The results demonstrate that the FADE model is able to capture comparable time-series of collisions and number of objects as predicted by DAMAGE in several scenarios. Further, and perhaps more importantly, its speed and flexibility allows the user to explore and understand the evolution of the space debris environment<br/
The implementation of cost effective debris protection in unmanned spacecraft
No full textProper characterisation of the survivability of an unmanned spacecraft to debris impact must go beyond just a simple assessment of the probability of penetration. Some penetrative damage may be survivable, particularly if critical internal equipment is arranged judiciously. Consideration of the satellite architecture can be seen as a potentially cost-effective and complementary approach to the more traditional method of adding shielding mass. To quantify the benefits of both strategies, and identify candidate protection solutions for a typical satellite design, a new model called SHIELD has been developed. Competing protection options are evaluated using a survivability metric. Rapid convergence on one or more ‘good' designs can also be achieved with a built-in genetic algorithm search method. SHIELD's potential as a project support tool is illustrated by applying it to the survivability evaluation of a satellite currently under design. The effectiveness of the genetic algorithm is also demonstrated, but on a more idealised spacecraft design
Space debris networks
No full textThere are 3,226 satellites and over 10,000 items of man-made space debris, larger than 10 cm, in orbit around the Earth. Whilst most debris has been generated by explosions, modelling studies suggest that collisions will soon take over as the main debris generating source. Irrespective of its source, debris poses a collision risk to operational satellites and other debris objects. Even a single collision (involving satellites and/or debris) has the potential to create many hundreds of new debris objects which would have long-term negative implications for satellite operators and services.
Space debris mitigation guidelines are currently in place to limit the production of new debris. In addition to these guidelines, Active Debris Removal (ADR) may be needed to reduce the number of debris objects in orbit. However, if debris objects are to be removed by ADR then a robust and quantitative method will be required to identify objects most likely to have a negative impact on the future environment. This requirement arises principally because of the technological challenges and high economic cost of removing these objects.
By treating the space debris environment as a complex system and analysing the data using network and vertex measures, the debris problem can be understood from a new perspective. The aim of the current research is to demonstrate that network theory is an effective approach to analysing space debris environment data. Data from modelling studies are used to represent the space debris environment as networks. Vertices represent debris objects and edges represent the possible future conjunctions between the objects. The networks are analysed using the following measures: degree, strength, assortativity, affinity, clustering, and betweenness centrality.
The results suggest that the space debris environment has a low average degree and is disassortative with hubs. This means that the environment is resilient to random removals as there are only a few vertices, the hubs, which may have a significant effect on the future environment. Furthermore, targeting the vertices with a high degree or betweenness centrality reduces the connectivity of a large space debris network by breaking it into several smaller networks. Therefore, a targeted ADR approach will be necessary if objects are removed from the space debris environmen
Self-induced collision hazard in high and moderate inclination satellite constellations
No full textThe assessment of the hazard posed by space debris to constellations of satellites in low Earth orbit is of growing importance, with the proliferation of proposed and implemented constellation systems with a variety of mission objectives. This applies to current constellation-based commercial communication systems, in particular, since these are typically deployed at altitudes where there is a peak in the space debris environment. An impact risk analysis is performed over a period of up to 1 month after a breakup event using two examples of constellation configurations. The first is similar to the IRIDIUM system, containing around 70 satellites in near-polar orbits at approximately 800km altitude, and the second is a Globalstar-like configuration with 56 satellites at around 1400km altitude, distributed in orbit planes inclined at 52o. The analysis is performed using the SDS software, which applies the probabilistic continuum dynamics technique. This has the benefit of being a self-contained and rigorous method. However, it is found to be not well-suited to 'long-term' analysis, due to the computational effort required. The risk analysis for the chosen examples is presented, as well as an investigation of the robustness of the method when applied to complex and 'long-period' simulations
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