Statistical Analysis and Modeling of the 3D Morphology and Texture of Lunar Regolith Simulants
Source abstract
Abstract
Abstract Understanding the mechanical behavior of lunar regolith under low-g conditions is essential for processing regolith in the lunar environment. While well understood for many granular materials on Earth, these properties have yet to be studied for lunar regolith. For ground-based experimental investigation of regolith properties, simulants are used, which mimic certain physical or chemical aspects of lunar regolith. However, rheology is significantly influenced by particle size and shape, which has not yet been thoroughly characterized for lunar regolith particles. Moreover, it remains unclear how well common simulants approximate the morphology of lunar regolith particles. In this paper, we quantify the multivariate distributions of size and shape descriptors of actual lunar regolith particles and seven commonly used mare and highlands regolith simulants, using 3D tomographic image data obtained via micro computed tomography. Quantitative analysis confirms that there are large differences in morphology within regolith simulants and between simulants and lunar regolith. This highlights the need to develop regolith simulants with accurate morphologies for experimental investigations of mechanical properties. Alternatively, statistically representative digital models of lunar regolith can be used as input for numerical simulations, enabling simulation studies of morphology-driven mechanical behavior under lunar conditions.
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Research context
OpenAlex topics: Planetary Science and Exploration · Granular flow and fluidized beds · Aeolian processes and effects
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Stochastics, Ulm University , Helmholtzstr. 18, Ulm 89081 ,
Institute for Mechanical Process Engineering and Mineral Processing, TU Bergakademie Freiberg , Agricolastr. 1, Freiberg 09599 ,
Airbus Defence and Space , Claude Dornier Str., Immenstaad 88090 ,
Applied AI and Data Science Unit, University of Southern Denmark , Campusvej 55, Odense 5230 ,
Fraunhofer Institute for Manufacturing Technology and Advanced Materials IFAM , Winterbergstr. 28, Dresden 01277 ,
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