lunar basalts
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Icarus ◽  
2021 ◽  
pp. 114836
Author(s):  
Kevin Robertson ◽  
Ralph Milliken ◽  
Carle Pieters ◽  
Leif Tokle ◽  
Leah Cheek ◽  
...  

2021 ◽  
Author(s):  
John Hamilton

<p>Hawai`i Island has had a pivotal role in human Lunar Exploration by virtue of its high-fidelity science and technical field sites.  The geologic and historically recent volcanic landscape along with the geochemical simularity of Hawaiian basalts with Lunar basalts have made Hawaii a prime location for field test simulations.   This presentation will briefly highlight the legacy Apollo astronaut geology training. The  post-Shuttle <em>In-Situ</em> Resource Utilization (ISRU) field tests on equipment &  techniques for lunar oxygen production will be covered along with mission simulations for NASA’s RESOLVE and VIPER lunar polar missions.  Google Lunar X-Prize (GLXP) field trials have also occurred.  Finally educational aspects with University level robotic mining competitions (Lunabotics/RMC/PRISM) will be shown.</p> <p>            The geo-technical properties of the tephra (basalt sand) at the field site(s) will be explored, and shown to provide a good lunar simulant for laboratory use and experimentation. Samples are still currently available for researchers.</p>


2021 ◽  
Author(s):  
Lev Chepigo ◽  
Ivan Lygin ◽  
Andrey Bulychev ◽  
Kuznetsov Kirill

<p>Taking into account sphericity is one of the most relevant questions of interest for gravity researchers today. It’s especially important in data analysis of regional surveys and satellite missions.</p><p>Modern satellite missions are characterized by high accuracy of measurements, as well as a high degree of detail, which makes it possible to construct detailed grid density models of Earth and Moon, however, when automating this process, the following problems arise:</p><p>- long duration of the inversion process;</p><p>- need for a large amount of RAM when using standard approaches to solving the linear inverse problem of gravity prospecting for grid models;</p><p>- high sensitivity of gravity inversion algorithms to the upper cells;</p><p>The first problem can be solved by inverting of gravity in the spectral domain using the fast Fourier transform. In this case, the time complexity of the inversion algorithms is reduced by times, which significantly accelerates the selection of the model.     </p><p>To reduce the memory used, it is necessary to memorize the gravity spectrum for only one cell for each pair of coordinates depth - latitude, since cells with at the same depth and latitude have the same gravitational effects, shifted by the step of cells in the grid model.</p><p>Finally, to increase the sensitivity of the inversion algorithms to deep cells, you can use the variable parameter of the gradient descent step (learning rate in machine learning), depending on the depth as an exponential or any other function, in combination with regularization.</p><p>The proposed approach was applied to the data of the GRAIL mission, and as a result, a density model of the Moon was constrained with the following grid steps: 0.5<sup>o</sup> in latitude, 0.7<sup>o</sup> (pi / 512) in longitude and 10 km in depth.</p><p>The fitted model was used to estimate the possible parameters of the sources of lunar mascons. It stands to mention the differences in the geometry of the mascon sources, which can be divided into two groups: isometric sources and sources with channels ascending to the surface, through which, probably, lunar basalts entered the surface.</p><p>The proposed approach allows constrain density models of celestial bodies fast enough using a personal computer (less than an hour for a model with the parameters mentioned above), and also takes into account the weak sensitivity of standard inversion algorithms to deep cells.</p>


2021 ◽  
Vol 176 (3) ◽  
Author(s):  
Laura J. A. Rzehak ◽  
Sebastian Kommescher ◽  
Florian Kurzweil ◽  
Peter Sprung ◽  
Felipe P. Leitzke ◽  
...  

AbstractEquilibria between Ti oxides and silicate melt lead to Ti isotope fractionation in terrestrial samples, with isotopically light Ti oxides and isotopically heavy coexisting melt. However, while Ti is mostly tetravalent in terrestrial samples, around 10% of the overall Ti is trivalent at fO2 relevant to lunar magmatism (~ IW-1). The different valences of Ti in lunar samples, could additionally influence Ti stable isotope fractionation during petrogenesis of lunar basalts to an unknown extent. We performed an experimental approach using gas mixing furnaces to investigate the effect of Ti oxide formation at different fO2 on Ti stable isotope fractionation during mare basalt petrogenesis. Two identical bulk compositions were equilibrated simultaneously during each experiment to guarantee comparability. One experiment was investigated with the EPMA to characterize the petrology of experimental run products, whereas the second experiment was crushed, and fabricated phases (i.e., oxides, silicates and glass) were handpicked, separated and digested. An aliquot of each sample was mixed with a Ti double-spike, before Ti was separated from matrix and interfering elements using a modified HFSE chemistry. Our study shows fO2-dependent fractionation within seven samples from air to IW-1, especially ∆49Tiarmalcolite-melt and ∆49Tiarmalcolite-orthopyroxene become more fractionated from oxidized to reduced conditions (− 0.092 ± 0.028-  − 0.200 ± 0.033 ‰ and  − 0.089 ± 0.027- − 0.250 ± 0.049 ‰, respectively), whereas ∆49Tiorthopyroxene-melt shows only a minor fractionation (− 0.002 ± 0.017-0.050 ± 0.025 ‰). The results of this study show that Ti isotope fractionation during mare basalt petrogenesis is expected to be redox dependent and mineral-melt fractionation as commonly determined for terrestrial fO2 may not be directly applied to a lunar setting. This is important for the evaluation of Ti isotope fractionation resulting from lunar magmatism, which takes place under more reducing conditions compared to the more oxidized terrestrial magmatism.


2021 ◽  
Author(s):  
Eric Hasenstab ◽  
Carsten Münker ◽  
Maxwell Thiemens ◽  
Peter Sprung ◽  
Erik Strub
Keyword(s):  

2020 ◽  
pp. 13-18 ◽  
Author(s):  
S. Kommescher ◽  
R.O.C. Fonseca ◽  
F. Kurzweil ◽  
M.M. Thiemens ◽  
C. Münker ◽  
...  

2019 ◽  
Vol 266 ◽  
pp. 144-162 ◽  
Author(s):  
Jessica J. Barnes ◽  
Ian A. Franchi ◽  
Francis M. McCubbin ◽  
Mahesh Anand

2019 ◽  
Vol 12 (9) ◽  
pp. 701-706 ◽  
Author(s):  
James M. Brenan ◽  
James E. Mungall ◽  
Neil R. Bennett

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