Long-term Passive Mode Data Measured by the Dynamic Albedo of Neutrons (DAN) Instrument onboard Mars Science Laboratory (MSL) and Comparison to REMS Surface Pressure and Temperature Measurements
Abstract:Since the landing in August 2012, DAN has provided a wealth of scientific data from the successful surface operation in both Active mode and Passive mode. While the main DAN science investigation so far has focused in estimating the contents of water-equivalent-hydrogen (WEH) and chlorine-equivalent-neutron-absorption in the surface, here we will provide/discuss low energy (less than about 1 keV) background neutron environment at the Martian surface as measured by DAN Passive mode operation. Passive mode measurements have been done on almost every sols with durations ranging from 1 hour to ~9 hour, covering different times of a day. Neutrons from the onboard power source Multi Mission Radioisotope Thermonuclear Generator (MMRTG) and induced by Galactic Cosmic Ray (GCR)/Solar Energetic Particles (SEP) interactions with the Martian atmosphere and the surface material contribute to the DAN passive data. An approach to separate out the respective contributions from the DAN total count rates was developed previously (Jun et al., 2013) using the data collected at Rocknest (where the rover stayed from sol 60 to sol 100). The main goal of this paper is to extend the same analysis to other locations encountered during the rover traverse especially to understand the long-term (through Sol 800, covering more than 1 Martian year) behavior of the neutron environment at the Martian surface as measured by DAN in response to variation of the free space GCR/SEP environment. Extensive Monte Carlo transport simulations using Monte Carlo N-Particle eXtended (MCNPX) have been performed to support the analysis and to aid interpretation of the DAN passive data.
In addition, the DAN passive data are compared to the long-term surface temperature and pressure data (both measured and modeled) from Rover Environmental Monitoring Station (REMS) to investigate possible correlation of the DAN data with ambient environmental conditions.