Three-dimensional direct simulation Monte-Carlo modeling of the coma of comet 67P/Churyumov-Gerasimenko observed by the VIRTIS and ROSINA instruments on board Rosetta

Feb 1, 2016·
Nicolas Fougere
Nicolas Fougere
,
et. al
· 0 min read
Abstract
Since its rendezvous with comet 67P/Churyumov-Gerasimenko (67P), the Rosetta spacecraft has provided invaluable information contributing to our understanding of the cometary environment. On board, the VIRTIS and ROSINA instruments can both measure gas parameters in the rarefied cometary atmosphere, the so-called coma, and provide complementary results with remote sensing and in situ measurement techniques, respectively. The data from both ROSINA and VIRTIS instruments suggest that the source regions of H2O and CO2 are not uniformly distributed over the surface of the nucleus even after accounting for the changing solar illumination of the irregularly shaped rotating nucleus. The source regions of H2O and CO2 are also relatively different from one another. The use of a combination of a formal numerical data inversion method with a fully kinetic coma model is a way to correlate and interpret the information provided by these two instruments to fully understand the volatile environment and activity of comet 67P. Methods. In this work, the nonuniformity of the outgassing activity at the surface of the nucleus is described by spherical harmonics and constrained by ROSINA-DFMS data. This activity distribution is coupled with the local illumination to describe the inner boundary conditions of a 3D direct simulation Monte-Carlo (DSMC) approach using the Adaptive Mesh Particle Simulator (AMPS) code applied to the H2O and CO2 coma of comet 67P. We obtain activity distribution of H2O and CO2 showing a dominant source of H2O in the Hapi region, while more CO2 is produced in the southern hemisphere. The resulting model outputs are analyzed and compared with VIRTIS-M/-H and ROSINADFMS measurements, showing much better agreement between model and data than a simpler model assuming a uniform surface activity. The evolution of the H2O and CO2 production rates with heliocentric distance are derived accurately from the coma model showing agreement between the observations from the different instruments and ground-based observations. We derive the activity distributions for H2O and CO2 at the surface of the nucleus described in spherical harmonics, which we couple to the local solar illumination to constitute the boundary conditions of our coma model. The model presented reproduces the coma observations made by the ROSINA and VIRTIS instruments on board the Rosetta spacecraft showing our understanding of the physics of 67P’s coma. This model can be used for further data analyses, such as dust modeling, in a future work.
Type
Publication
Astronomy & Astrophysics, 588(134)
Status
Peer-reviewed Open access
publications
Nicolas Fougere
Authors
Senior Manager Role Portfolio

Nicolas Fougere helps global manufacturers turn emerging technology into commercial strategy. As Senior Manager for the Fluids Portfolio at Dassault Systèmes, he sets the 3-year strategy for a multi-product CFD portfolio, owns the productization and pricing models decisions, and leads the portfolio’s shift toward AI enabled simulation.

He came into this role after eight years in technical sales, where he served as account lead for some of the company’s largest customers. That work gave him a close view of how large organizations actually decide to adopt new technology, which is a big part of why his current strategy work tends to hold up once it meets a real customer.

Earlier still, he worked on mission analysis and simulation research supporting NASA and the European Space Agency’s Rosetta mission, and published more than 40 peer-reviewed papers along the way. His engineering and scientific degrees are from the University of Michigan.

What distinguishes Nicolas is the ability to move fluidly between deep technical work and business decision-making, from a simulation review with engineers to a pricing or roadmap discussion with executives. That range is increasingly what organizations need when deciding whether a simulation or AI investment is worth making.