Engineering topics

Grava, Cesare

Publications and source records attributed to Grava, Cesare.

3 records

NASA NTRS2016

Contributions of Solar Wind and Micrometeoroids to Molecular Hydrogen in the Lunar Exosphere

We investigate the density and spatial distribution of the H2 exosphere of the Moon assuming various source mechanisms. Owing to its low mass, escape is non-negligible for H2. For high-energy source mechanisms, a high percentage of the released molecules escape lunar gravity. Thus, the H2 spatial distribution for high-energy release processes reflects the spatial distribution of the source. For low energy release mechanisms, the escape rate decreases and the H2 redistributes itself predominantly to reflect a thermally accommodated exosphere. However, a small dependence on the spatial distribution of the source is superimposed on the thermally accommodated distribution in model simulations, where density is locally enhanced near regions of higher source rate. For an exosphere accommodated to the local surface temperature, a source rate of 2.2 g s-1 is required to produce a steady state density at high latitude of 1200 cm-3. Greater source rates are required to produce the same density for more energetic release mechanisms. Physical sputtering by solar wind and direct delivery of H2 through micrometeoroid bombardment can be ruled out as mechanisms for producing and liberating H2 into the lunar exosphere. Chemical sputtering by the solar wind is the most plausible as a source mechanism and would require 10-50 of the solar wind H+ inventory to be converted to H2 to account for the observations.

Impact↗

NASA NTRS2015

Understanding Temporal and Spatial Variability of the Lunar Helium Atmosphere Using Simultaneous Observations from LRO, LADEE, and ARTEMIS

Simultaneous measurements of helium in the exosphere of the Moon are made from the Lunar Reconnaissance Orbiter (LRO) Lyman Alpha Mapping Project (LAMP) and the Lunar Atmosphere and Dust Environment Explorer (LADEE) Neutral Mass Spectrometer (NMS) through the entire 5-month span of the LADEE mission. In addition, the ARTEMIS mission monitored the solar wind alpha particle flux to the Moon. Modeling the lunar helium exosphere, we relate the LAMP polar observations to the LADEE equatorial observations. Further, using the ARTEMIS alpha flux in the Monte Carlo model reproduces the temporal variations in helium density. Comparing the LAMP data to the LADEE data shows excellent agreement. Comparing those with the ARTEMIS data reveals that the solar wind alpha flux is the primary driver to variability in the helium exosphere throughout the LADEE mission. Using a decay time for exospheric helium of 5 days, we determine that the solar wind contributes 64 +/- 5% of the helium to the lunar exosphere. The remaining 36 +/- 5% is presumed to come from outgassing of radiogenic helium from the interior of the Moon. Furthermore, the model reproduces the measurements if 63 +/- 6% of the incident alpha particles are converted to thermalized helium atoms through the interaction between the alphas and the lunar surface. However, these values are dependent on both inferred source rates from LAMP and LADEE observations and on the assumed time constant of the exospheric decay rate.

Moon↗

NASA NTRS2014

An Analytic Function of Lunar Surface Temperature for Exospheric Modeling

We present an analytic expression to represent the lunar surface temperature as a function of Sun-state latitude and local time. The approximation represents neither topographical features nor compositional effects and therefore does not change as a function of selenographic latitude and longitude. The function reproduces the surface temperature measured by Diviner to within +/-10 K at 72% of grid points for dayside solar zenith angles of less than 80, and at 98% of grid points for nightside solar zenith angles greater than 100. The analytic function is least accurate at the terminator, where there is a strong gradient in the temperature, and the polar regions. Topographic features have a larger effect on the actual temperature near the terminator than at other solar zenith angles. For exospheric modeling the effects of topography on the thermal model can be approximated by using an effective longitude for determining the temperature. This effective longitude is randomly redistributed with 1 sigma of 4.5deg. The resulting ''roughened'' analytical model well represents the statistical dispersion in the Diviner data and is expected to be generally useful for future models of lunar surface temperature, especially those implemented within exospheric simulations that address questions of volatile transport.

moon↗