ABSTRACT

In the next decade, NASA is prioritizing Moon missions such as safe human transportation, deployment of instrumentations, establishment of habitats, and exploration of native resources to set the stage for future Mars missions. One of the main challenges to achieve these goals, however, is our lack of understanding of the synergistic interactions between the native soil, lunar vehicles, habitats, and EVA suits. In addition to the particle size distributions, surface properties, and compaction characteristics of the surface regolith, the geometry of the particles is of paramount importance for a proper understanding of the settlement properties, distortion characteristics, and orthogonal strength of the particulate medium, which impacts transportation, habitat development, and the regolith’s potential to degrade EVA suits by abrasion based on the angularity of the particles. Therefore, our multi-disciplinary team in this research envisioned using a state of the art optical profilometer equipment supplemented by image analysis techniques to characterize the geometrical features of a lunar regolith simulant, specifically the CSM-LHT-1 highlands type. The distributions of the particle form, angularity, and surface macro-texture of lunar regolith were in turn contrasted with JSC-1 Mars simulants and a calcareous construction aggregate for comparative purposes in this study. The results will be instrumental to better understand the anisotropic nature of the angular particles and its relevance to the strength and deformation characteristics of native soils on extra-terrestrial planetary surfaces.

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REFERENCES

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Ashtiani, R., Baca J., and Wessel J. 2018. “Geotechnical Aspects of the Lunar Regolith Simulants”, Johnson Space Center (JSC), NASA, Houston, TX.
Ashtiani, R., and Rashidi, M. “A Neural Network Based Model for the Estimation of the Anisotropic Parameters of Unbound Aggregate Systems”, Elsevier Journal of Transportation Geotechnics, Vol. 15, pp. 4–12,. (2018).
Ashtiani, R.S. (2022) Class Discriminatory Information for Unbound Granular Layers Using Statistical Pattern Recognition Techniques. Advances in Transportation Geotechnics IV. Lecture Notes in Civil Engineering, vol 164. Springer, Cham.
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Go to Earth and Space 2022
Earth and Space 2022
Pages: 27 - 34

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Published online: Jan 5, 2023

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Caleb J. Carnes [email protected]
Dept. of Civil and Environmental Engineering, United States Air Force Academy, CO. Email: [email protected]
Reza S. Ashtiani [email protected]
Dept. of Civil and Environmental Engineering, United States Air Force Academy, CO. Email: [email protected]
Joel A. Sloan [email protected]
Dept. of Civil and Environmental Engineering, United States Air Force Academy, CO. Email: [email protected]
Melissa S. Beauregard [email protected]
Dept. of Civil and Environmental Engineering, United States Air Force Academy, CO. Email: [email protected]
Kimberly D. De la Harpe [email protected]
Dept. of Physics and Meteorology, United States Air Force Academy, CO. Email: [email protected]

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