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Modeling the Gas-Grain Plume of Enceladus. θ sp. S. K. Yeoh , T. A. Chapman, D. B. Goldstein, P. L. Varghese, L. M. Trafton The University of Texas at Austin; E-mail: email@example.com. Credit: NASA/JPL. Credit: NASA/JPL. Introduction. Far-field Results vs. Cassini INMS Data. Vent.
S. K. Yeoh, T. A. Chapman, D. B. Goldstein, P. L. Varghese, L. M. Trafton
The University of Texas at Austin; E-mail: firstname.lastname@example.org
Far-field Results vs. Cassini INMS Data
In 2005, Cassini first detected a gas-grain plume over Enceladus’ south pole originating from the tiger-stripe fractures. The discovery not only helped unlock some mysteries, such as the source of Saturn’s E-ring grains  and the origin of the very bright expanses in Enceladus’ south polar region , but also opened doors to new possibilities, including the existence of extra-terrestrial life . Consequently, it has been a very active area of research. Here, we model both the gas and the grain components of Enceladus’ plume to constrain the conditions at the sources.
L-S Fitting Procedure:
1. Density contribution from each individual source, n, along the trajectory is determined via simulation.
2. The total density, ntotal, along the trajectory is obtained as follows:
3. L-S fitting of ntotal to INMS data is performed to obtain optimized set of si.
We simulate the different regimes of the plume using models of different scales that are linked together to obtain the entire plume. Then, simulated flybys are performed and the results are compared with available in-situ data.
FM model uses the DSMC velocity distributions to assign its particles velocities at each point source.
si: Strength of source i
ni: Density contribution of source i along trajectory
Table 3. Optimized Source Strengths (pure gas, θsp = 0)
Free-molecular (FM) Model for Collisionless Far-Field
Velocities of gas molecules and grains are sampled to form velocity distributions.
Direct Simulation Monte Carlo (DSMC) Model for Collisional Near-Field
Figure 2. Least-Squares-Fitted Simulated Water Number Density Distributions along the Cassini E3, E5 and E7 trajectories compared to INMS data  .
Flow becomes collisionless.
Constraining Width of Grain Jets
Collisional flow in the near-field
Vent conditions are used as input to DSMC model for gas; grains are initialized independently.
Table 1. Vent Conditions (Gas-only)
Triple point of Water:
Temperature = 273.16 K
Pressure = 612 Pa
Non-zero spreading angle
Parametric Study Using Model
We vary the parameters one at a time and study their effects on the plume near-field and far-field. Grains are 1-µm in size.
Figure 4. FWHM of the grain jets, normalized by the DSMC domain height (10 km), vs. velocity ratio, rvel.
Table 2. Parameter Values
Near-Field Gas Number Density Contours
References: Baum, W.A., et al., 1981. Saturn’s E Ring: I. CCD Observations of March 1980. Icarus47, 84–96. Porco, C.C., et al., 2006. Cassini Observes the Active South Pole of Enceladus. Science311, 1393–1401. McKay, C.P., et al., 2008. The Possible Origin and Persistence of Life on Enceladus and Detection of Biomarkers in the Plume. Astrobiology8, 909–919. Spitale, J.N., Porco, C.C., 2007. Association of the jets of Enceladus with the warmest regions on its south-polar fractures. Nature449, 695–697.  Smith, H.T., et al., 2010. Enceladus plume variability and the neutral gas densities in Saturn’s magnetosphere. J. Geophys. Res.115, A10252.  Dong, Y., et al., 2011. The water vapor plumes of Enceladus. J. Geophys. Res. 116, A10204.  Waite, J.H., et al., 2006. Cassini Ion and Neutral Mass Spectrometer: Enceladus Plume Composition and Structure. Science311, 1419–1422.  Schmidt, J., et al., 2008. Slow dust in Enceladus’ plume from condensation and wall collisions in tiger stripe fractures. Nature451, 685–688.
Acknowledgements:Work is supported byNASA Cassini Data Analysis Program (CDAP) grants NNX08AP77G and NNH09ZDA001N-CDAP. Computations were performed at theTexas Advanced Computing Center (TACC).
Figure 1. Gas number density contours. Black lines are outlines of grain columns.