Abstract

The NASA Dawn Mission will determine the surface composition of 4 Vesta and 1 Ceres, providing constraints on their formation and thermal evolution. The payload includes a Gamma Ray and Neutron Detector (GRaND), which will map the surface elemental composition at regional spatial scales. Target elements include the constituents of silicate and oxide minerals, ices, and the products of volcanic exhalation and aqueous alteration. At Vesta, GRaND will map the mixing ratio of end-members of the howardite, diogenite, and eucrite (HED) meteorites, determine relative proportions of plagioclase and mafic minerals, and search for compositions not well sampled by the meteorite collection. The large south polar impact basin may provide an opportunity to determine the composition of Vesta’s mantle and lower crust. At Ceres, GRaND will provide chemical information needed to test different models of Ceres’ origin and thermal and aqueous evolution. GRaND is also sensitive to hydrogen layering and can determine the equivalent H2O/OH content of near-surface hydrous minerals as well as the depth and water abundance of an ice table, which may provide information about the state of water in the interior of Ceres. Here, we document the design and performance of GRaND with sufficient detail to interpret flight data archived in the Planetary Data System, including two new sensor designs: an array of CdZnTe semiconductors for gamma ray spectroscopy, and a loaded-plastic phosphor sandwich for neutron spectroscopy. An overview of operations and a description of data acquired from launch up to Vesta approach is provided, including annealing of the CdZnTe sensors to remove radiation damage accrued during cruise. The instrument is calibrated using data acquired on the ground and in flight during a close flyby of Mars. Results of Mars flyby show that GRaND has ample sensitivity to meet science objectives at Vesta and Ceres. Strategies for data analysis are described and prospective results for Vesta are presented for different operational scenarios and compositional models.

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