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"Mars (Planet) Exploration Data processing."
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Predicting olivine composition using Raman spectroscopy through band shift and multivariate analyses
Olivine group minerals are ubiquitous in extrusive igneous rocks and play an important role in constraining equilibria for samples in the upper mantle and above. All Raman spectra of the olivine group minerals in the solid solution between forsterite (Fo, Mg2SiO4) and fayalite (Fa, Fe2SiO4) have a high-intensity doublet between 800 and 880 cm-1. Previous studies used small sample suites with limited compositional ranges and varying spectrometers to relate energy shifts of these two bands to Mg/Fe contents. In this work, Raman spectra of 93 olivine samples were acquired on either Bruker's 532 nm (laser wavelength) Senterra or BRAVO (785/852.3 nm) spectrometer. This paper compares the two-peak band shift univariate method with two multivariate methods: partial least squares (PLS) and the least absolute shrinkage operator (Lasso). Data sets from several instruments are also examined to assess the most accurate method for predicting olivine composition from a Raman spectrum. Our 181-spectra PLS model is recommended for use when determining olivine composition from a Raman spectrum. For Raman spectra of mixed phases where only the olivine doublet can be identified, composition can best be determined using the position of the peak ca. 838-857 cm-1 through use of the regression equation %Fo = -0.179625x2 + 310.077x -133 717 (where x = DB2 centroid in units of cm-1). In situ methods for predicting mineral composition on planetary surfaces are critically important to extraterrestrial exploration going forward; of these, Raman spectroscopy is likely the best, as shown by the impending deployment of several Raman instruments to Mars (ExoMars and Mars 2020). More broadly, application of machine learning methods to spectral data processing have implications to multiple fields that use spectroscopic data.
Journal Article
ExoMars Trace Gas Orbiter (TGO) Science Ground Segment (SGS)
The ExoMars Trace Gas Orbiter (TGO) Science Ground Segment (SGS), comprised of payload Instrument Team, ESA and Russian operational centres, is responsible for planning the science operations of the TGO mission and for the generation and archiving of the scientific data products to levels meeting the scientific aims and criteria specified by the ESA Project Scientist as advised by the Science Working Team (SWT). The ExoMars SGS builds extensively upon tools and experience acquired through earlier ESA planetary missions like Mars and Venus Express, and Rosetta, but also is breaking ground in various respects toward the science operations of future missions like BepiColombo or JUICE. A productive interaction with the Russian partners in the mission facilitates broad and effective collaboration. This paper describes the global organisation and operation of the SGS, with reference to its principal systems, interfaces and operational processes.
Journal Article
USING THE AUTOMATED SYSTEM ROBUST MODELING FOR STUDY THE SURFACES AND GRAVITY FIELDS PLANETS
Modern versions of the ASRM-2017 (Automated System for Robust Modeling) package provide a solution to a large range of problems associated with modeling surfaces and gravity fields of planets. However, their application requires creation of not only the global models but working models of the local surface areas as well. Currently, these regional geopotential models are in high demand in geology and oil exploration. To solve the problems of this kind, the special algorithms were created and implemented because the methods of developing global models are not always suitable for the development of the model in accordance with the limited surface area. The capability to create and analyze models of local parts of the surface is the main feature of the ASRM-2017. The required calculation accuracy of the model and output data are provided. Mathematical models developed on the basis of the ASRM-2017 may be applied in a wide range of density measurements from regular measuring networks with short distances between the points to irregular networks with the points located far from each other. With increasing distances between points, and irregularity of increasing the accuracy of prediction of constructed mathematical models increases, reaching and exceeding the accuracy of interpolation for some interpolation formulas. The capabilities of modern working version of the software package allow to carry out precise modeling of the planetary parameters distribution (topography, gravitational and magnetic fields, etc.) as on the whole planetary surface and on its local parts. The software can also be used in geology and oil exploration.
Conference Proceeding
Technology today. Episode 439
This documentary, produced by Evan Clark, is about topics such as cosmonaut training, real-time weather graphics, and manned-mission Mars testing.
Streaming Video