Author

Thomas Percy

Date of Award

2015

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Mechanical and Aerospace Engineering

Committee Chair

David B. Landrum

Committee Member

Robert A. Frederick

Committee Member

Kathleen Hawk

Committee Member

Kunning G. Xu

Committee Member

Matthew W. Turner

Subject(s)

Space debris

Abstract

The accumulation of 50 years’ worth of man-made space objects has increased the risk of catastrophic collisions. Continuing to operate in a business-as-usual manner will one day render regions of LEO unusable. The landscape of future LEO satellite operations is complicated by the evolving nature of space policy and the emergence of the CubeSat which has the potential to radically shift the current LEO satellite market. Long-term population modeling is required to predict population growth, support policy decisions, and inform industry best practices. Many space agencies around the world have high-fidelity analysis codes to serve this function but they are complex and computationally expensive. The Simplified LEO Orbital Object Population (SLOOP) model has been developed to provide a broader user base a simplified, reasonably accurate prediction tool for rapidly evaluation future scenarios. Expanding on previous simplified population models for LEO, new algorithms for evaluating fragment and intact object populations over time were developed. These algorithms add spatial fidelity and allow the evaluation of LEO as a series of layers rather than one large region of space. This addition enables more specific evaluations of LEO populations. Differential equations and coefficients that represent various contributors to the orbital object populations were investigated and modified. To support this development, a new comprehensive orbital object database was created, integrating several data sources. A new model of atmospheric density was created to fill a gap in available data and help quantify natural orbit decay times at high LEO altitudes. Comparisons of the SLOOP model with benchmark data from current high-fidelity models show only a +/- 5% error over a 100 year simulation. This level of agreement indicates that, for the first time, a simplified model can direct higher-fidelity studies by identifying trends with reasonably high accuracy in a fraction of the run time. A sample SLOOP analysis evaluating the impact of deploying large CubeSat constellations shows the power of the model to rapidly evaluate future operating scenarios. Overall, the data presented shows that with enhanced algorithms, improved use of demographic data, and faster simulations, the SLOOP model fills an important role in orbital debris analysis.

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