Remote Sensing for Spatial Electrostatic Characterization using the Multi-Sphere Method

Remote Sensing for Spatial Electrostatic Characterization using the Multi-Sphere Method

Engwerda, H.J.A.

Sundaramoorthy, P.P. (mentor)

Aerospace Engineering

Space Engineering

Space Flight

2017-03-15

Focusing on the rapidly increasing debris population around Earth as well as the scientific and corporate interest in Asteroids, multiple missions for interaction with non-cooperative bodies have been proposed over the last years. Applications such as the Electrostatic Tractor (ET) aiming to reduce the debris populations and missions introducing close proximity or even berthing with bodies in space all require knowledge about the electrostatic characteristics of the target. In order to infer this information in a real-time manner, the Remote Sensing for Electrostatic Characterization (RSEC) method can be applied. By measuring the ambient potential with probes extended from a dedicated spacecraft, an optimization can be performed as to find a best-fit Multi-Sphere Method (MSM) model. onsisting of a set of spheres with a point charge in their middle, this model approximates both the charge and potential of the rotating target. Comparing the in-situ measured potential with the potential obtained from the MSM model, the accuracy of the MSM model can be found and with it the model can be optimized. This thesis provides an extension of the RSEC method to three-dimensional space allowing for multi-axis tumbling motions of the target. Furthermore, simplifications of the model allowing for greater computational speed and simpler application are discussed. In order to validate the model, a Finite Element Analysis (FEA) is performed allowing the RSEC method to be tested for a representative missions scenario where the ET is applied. Based on the results of the FEA simulation, a Surface-MSM (SMSM) is constructed, allowing for multi-axis rotations of the debris, where this would be too computationally expensive with a FEA. The accuracy of force prediction within the ET method is assessed for a representative debris model. Furthermore, insights are offered in the effect of varying model parameters, and the influence of force mis-prediction on reorbiting time and fuel cost is evaluated.

electrostatic
space debris
sensing

http://resolver.tudelft.nl/uuid:37ee82df-d533-41fb-b6b8-a803c939cc4f

Student theses

master thesis

(c) 2017 Engwerda, H.J.A.