We propose a combined laboratory, modeling, and data analysis effort that will enhance the otes and ovirs investigations of the asteroid bennu. The primary data analysis and modeling tasks include (1)…

This federal contract award, valued at $547,387.38, was granted by the National Aeronautics and Space Administration (NASA) to The Research Foundation for the State University of New York (SUNY), doing business as Stony Brook University. The award supports a combined laboratory, modeling, and data analysis effort to enhance the investigations of the asteroid Bennu by the OSIRIS-REx mission's OTES and OVIRS instruments. Key tasks include multivariate partial least squares (PLS) modeling of the instrument spectra and radiative transfer modeling, supported by laboratory spectral characterization of mineral mixtures in a simulated asteroid environment. This work directly supports OSIRIS-REx science objectives related to compositional characterization of Bennu's surface and regolith. The award does not utilize any set-aside designations and runs through June 2023.

We propose a combined laboratory, modeling, and data analysis effort that will enhance the otes and ovirs investigations of the asteroid bennu. The primary data analysis and modeling tasks include (1) multi-variate partial least squares (PLS) modeling of otes and ovris spectra, and (2) radiative transfer modeling of otes ovirs spectra. These tasks will be supported by detailed laboratory thermal-IR (TIR; 5-50 microns) emissivity and visible/near-IR (vnir; 0.35-2.5 microns) reflectance spectral characterization of a range of mineral mixtures relevant to b-class asteroids in a simulated asteroid environment chamber. The proposed tasks will contribute to the compositional characterization of bennu's surface and will aid in the characterization of the surface regolith, and therefore is directly relevant to osiris-REX science objectives 2 and 3. Our proposed effort will include supporting the operations of the spectral analysis and regolith development science working groups, as well as the overall mission. Our primary tool for spectral analysis of otes and ovirs data is multi-variate PLS analysis, which permits accurate mineral abundance retrievals for fine-grained particulate mixtures. Fundamental inputs into PLS analysis are large spectral training sets of well characterized mixtures, acquired for a range of grain sizes and mineral abundances under conditions similar to that of the target body. We propose to acquire simulated asteroid environment (SAE) TIR emission and vnir reflectance spectra of a wide range of mixtures of olivine, pyroxene, hydrated silicate, sulfide, and oxide minerals of varying proportions. The mixture proportions will be informed by relevant abundances in CI, and CM chondrites. Training sets will be applied to PLS analysis of otes and ovirs spectra to produce global maps of mineral abundance. A complementary method to PLS analysis of otes and ovirs data is radiative transfer modeling. Our approach will utilize a hybrid t-matrix/hapke model developed by the PI to forward model otes and ovirs spectra using the compositions determined by PLS analysis. This method will tightly constrain the composition of bennu's regolith and other surface materials using both vnir and TIR wavelengths and provide a check for PLS analyses. Our previous work has shown that sample albedo and particle size play critical roles in the acquisition of realistic simulated airless body TIR emission spectra. Therefore, the mineral mixtures we create as part of the PLS training set will be darkened using carbon lamp black to have a visible albedo of 0.05, similar to that of bennu. To make the training sets required for PLS analysis and albedodependent spectral libraries, we will utilize the planetary and asteroid regolith spectroscopy environmental chamber (parsec) apparatus in the center for planetary exploration at stony brook university.