Statistical Analysis and Modeling of the 3D Morphology and Texture of Lunar Regolith Simulants

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.

Authors

Institutions

Publication Details

Journal
Microscopy and Microanalysis
Published
2026-02-23
DOI
https://doi.org/10.1093/mam/ozag013
Primary Topic
Planetary Science and Exploration
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Statistical Analysis and Modeling of the 3D Morphology and Texture of Lunar Regolith Simulants

Orkun Furat, Achim Seidel, Urs Alexander Peuker, Ralf Ditscherlein et al.
Microscopy and Microanalysis
Planetary Science and Exploration
article

Statistical Analysis and Modeling of the 3D Morphology and Texture of Lunar Regolith Simulants

Orkun Furat, Achim Seidel, Urs Alexander Peuker, Ralf Ditscherlein, Lisa Ditscherlein, Georg Pöhle, Tehya Birch, Matthias Weber, Volker Schmidt, Markus Franz
article en

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.

Microscopy and MicroanalysisVol. 32(2)
Airbus (Italy) (IT), University of Southern Denmark (DK), Helmholtz-Institute Ulm (DE), Fraunhofer Institute for Manufacturing Technology and Advanced Materials (DE), TU Bergakademie Freiberg (DE)
Life below water
Openalex Percentile: Top 23%
Planetary Science and Exploration
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.