Picture of blood cells

Open Access research which pushes advances in bionanotechnology

Strathprints makes available scholarly Open Access content by researchers in the Strathclyde Institute of Pharmacy & Biomedical Sciences (SIPBS) , based within the Faculty of Science.

SIPBS is a major research centre in Scotland focusing on 'new medicines', 'better medicines' and 'better use of medicines'. This includes the exploration of nanoparticles and nanomedicines within the wider research agenda of bionanotechnology, in which the tools of nanotechnology are applied to solve biological problems. At SIPBS multidisciplinary approaches are also pursued to improve bioscience understanding of novel therapeutic targets with the aim of developing therapeutic interventions and the investigation, development and manufacture of drug substances and products.

Explore the Open Access research of SIPBS. Or explore all of Strathclyde's Open Access research...

An intrusive approach to uncertainty propagation in orbital mechanics based on Tchebycheff polynomial algebra

Riccardi, Annalisa and Tardioli, Chiara and Vasile, Massimiliano (2015) An intrusive approach to uncertainty propagation in orbital mechanics based on Tchebycheff polynomial algebra. In: Astrodynamics 2015. Advances in Astrnautical Sciences . American Astronautical Society, San Diego, California, pp. 707-722. ISBN 9780877036296

Text (Riccardi-etal-AAS-2015-Uncertainty-propagation-in-orbital-mechanics-based-on-Tchebycheff-polynomial-algebra)
Accepted Author Manuscript

Download (13MB)| Preview


    The paper presents an intrusive approach to propagate uncertainty in orbital mechanics. The approach is based on an expansion of the uncertain quantities in Tchebicheff series and a propagation through the dynamics using a generalised polynomial algebra. Tchebicheff series expansions offer a fast uniform convergence with relaxed continuity and smothness requirements. The paper details the proposed approach and illustrates its applicability through a set of test cases considering both parameter and model uncertainties. This novel intrusive technique is then comapred against its non-intrusive counterpart in terms of approximation accuracy and computational cost.