Search NASASearch

Engineering topics

Ane Slabic

Publications and source records attributed to Ane Slabic.

Lunar Regolith Simulant User's Guide: Revision A

This guide is titled Lunar Regolith Simulant User's Guide, Rev A, and two points need to be made about the title. First, is the use of the term "regolith". During the Apollo Program, the term "soil" was used for taking a sample of the loose material on the surface, and then cataloging that sample in the lunar curation database as a "soil sample". By the 1980s, the term "regolith" gained favor by lunar scientists. In the Lunar Sourcebook (Heiken et al., 1991), regolith is defined as "a general term for the layer or mantle of fragmental and unconsolidated rock material, whether residual or transported and of highly varied character, that nearly everywhere forms the surface of the land and overlies or covers bedrock". Regolith is a terrestrial term that seems to go back to 1897, according to a recent paper by Huggett (2023). Huggett summed up his paper by writing, "soil and regolith are one in the same". "Regolith" will mostly be used throughout this guide, as it tends to separate in one's mind the unique nature of the Moon's surface when compared to the inherent bias humans have in their mind when they hear and use the word "soil". When referring to Apollo samples, "soil" is used for historical context and in some places the simple term "lunar simulant" is also used. Secondly, Rev A is used in the title because NASA released its first Lunar Regolith Simulant User's Guide in 2010, near the end of NASA's Constellation Program (Schrader et al., 2010). This guide follows in the pattern of that first guide and will be updated on a periodic basis as new simulants are created, characterized and used, and as new information emerges about the Moon's regolith due to new lunar exploration missions, both robotic and human.

Simulant

LIPA: Lunar Ice Perception Algorithm

The highest concentration of Lunar water-ice stores exists within the Permanently Shadowed Regions (PSRs) of the Lunar South Pole. As such, the ability to locate in situ water-ice stores in an accurate, systematic, and safe manner will prove vital for future Lunar activities which rely on hydrogen-based resources. Here we show how the strong absorptive properties of ice can be exploited (by coupling robotics, infrared imaging techniques, and machine learning) so that surface frost located in PSRs can be easily differentiated from the surrounding frozen regolith. Testbeds which simulate an icy lunar landscape were created and then imaged using a mid-wave infrared (MWIR) camera system mounted to a robotic arm (UR5e). Testbeds were imaged under two filter modes (1) wide band mode: whereby imagery captured filled a spectral range of 3.0 - 5.0 μm and (2) narrow band mode: whereby imagery captured were confined to a single central wavelength (CWL) of 3.15 ± 0.03 μm. A CWL of 3.15 μm was chosen due to the highly absorptive nature of ice at that specific wavelength. Images produced under both camera modes were processed in MATLAB. Narrow band images (NB) were subtracted from their wide band (WB) counterparts to produce differenced images (DI) which clearly demonstrated the spatial extent of ice (e.g., WB – NB = DI). Differenced images were used to train a Microsoft Azure model to discriminate between frozen regolith which did and did not contain ice. These works prove promising for future in situ resource utilization (ISRU) missions which employ robotics in combination with camera systems to advance science objectives (e.g., locate water-ice in frozen regolith) on the lunar surface.

Ane Slabic

Examination of Lunar Regolith Simulants By SEM-EDS and Imaging Raman Spectroscopy

The Artemis series lunar missions will include sample returns from the lunar south pole. Lunar regolith simulants (RS) generated in the lab provide opportunities to compare two surface science techniques: scanning electron microscopy (SEM-EDS) and Raman induced surface spectroscopy. The results will also be applicable for supporting future commercial lunar payload services (CLPS) and Artemis surface. Surface characterization contributes to continued development of lunar regolith studies and adds to various regolith databases. In characterizing various lunar regolith simulants, part of the aim should be to standardize techniques and utilize anticipated methods available for astromaterials studied during, or returned from, upcoming missions, particularly samples collected from the Moon’s south pole and permanently shadowed regions (PSRs).. An initial survey of available simulants has been started with Raman scanning process for particle counting the results of which will enrich the NASA-JSC Simulant Development Lab (SDL) simulant properties database and the Colorado School of Mines Planetary Simulant Data Base. An SEM-EDS dataset of raw regolith simulant materials are collected.

Raman Microscopy