The 3D Direct Simulation Monte Carlo Study of Europa’s Gas Plume

Abstract

Europa has been spotted as having water outgassing activities by space- and ground-based telescopes as well as reanalysis of the Galileo data. We adopt a 3D Direct Simulation Monte Carlo (DSMC) model to investigate the observed plume characteristics of Europa assuming that supersonic expansion originated from the subsurface vent. With a parametric study of the total gas production rate and initial gas bulk velocity, the gas number density, temperature and velocity information of the outgassing plumes from various case studies were derived. Our results show that the plume gases experience acceleration through mutual collisions and adiabatic cooling when exiting from the surface. The central part of the plume with relatively large gas production rates (1029 and 1030 H2O s−1) was found to sustain thermal equilibrium and near continuum condition. Column density maps integrated along two different viewing angles are presented to demonstrate the importance of the projection effect on remote sensing diagnostics. Finally, the density profiles at different altitudes are provided to prepare for observations of Europa’s plumes including upcoming spacecraft missions such as JUICE and Europa Clipper.

In-situ detection of Europa’s water plumes is harder than previously thought

“…These studies show that H 2 O molecules could be detected by the NIM instrument from a plume anywhere on the surface. However, simulations by Berg et al (2016a) and more recently by Tseng et al (2022), which included particleparticle collisions between H 2 O neutrals resulted in a canopy shock forming within the plume, as particles falling back to the surface collide with rising material. This limits the altitude and extent of the plume.…”

Development of methodology for scenario analysis of investment projects of enterprises of the mineral resource complex

“…One of the key elements of the project risk management system is quantitative methods for their assessment [13,14]. Among them, the most well-known methods are: sensitivity analysis of project performance criteria; discount rate adjustments; analysis of indicators of the limiting level; analysis of project development scenarios; building a "decision tree"; simulation statistical modeling (Monte Carlo method) [15][16][17].…”