In this dissertation work we sought to answer questions about the age, composition, and origin of planetary bodies. We implemented multiple approaches to answer these questions. To determine the age of the Clarissa asteroid family we implemented a modified version of SWIFT: a Solar System integration software package by Levison & Duncan (1994) to account for gravitational as well as thermal perturbations. This work constrained the age of the Clarissa asteroid family to be 56 ± 6 My. Next, we used a sum to one constraint weighted least squares (STO WLS) modeling approach to model thermal infrared (TIR) spectra of a suite of primitive asteroid analogs spectrally and volumetrically dominated by fine particulates ( < 38 µm). We determined that an alternative approach to the STO WLS model is needed to analyze asteroid regolith when it is dominated by fine particles ( < 90 µm). Our next approach included the Trojan asteroids (911) Agamemnon, (1172) Aneas, and (624) Hektor, and primitive asteroid (944) Hidalgo whose emissivity spectra share a prominent 10 µm plateau that is also present in cometary comae spectra. We used Multiple Sphere T-Matrix (MSTM) and Hapke reflectance models to model the asteroid spectral features using a mixture of olivine components (Mg-rich and Fe-rich olivine), fine particles (~0.5-1.0 µm), and lunar-like porosities (~74-87%). Finally, we used a light scattering Mie and Monte Carlo radiative transfer approach to model ambient (measured under Earth-like conditions) lunar regolith spectra. This study indicates that additional work needs to be done to develop an integrated thermal and light-scattering model that can replicate the effects of the thermal gradient present under lunar environment conditions because a light-scattering model alone is not able to reproduce the observed changes in the spectra that we see with space weathering.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2245 |
| Date | 01 January 2022 |
| Creators | Lowry, Vanessa |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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