Three-dimensional simulation of gas and dust in Io’s Pele plume

McDoniel, William; Goldstein, David; Varghese, Philip L.; Trafton, Laurence M.

doi:10.1016/j.icarus.2015.03.019

Cited by 20 publications

(12 citation statements)

References 28 publications

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“…If supersonic vents generate the plumes, the reduced height of a shocked plume and the increased number densities in the canopy correspond well with current observations ( Roth et al, 2014a ). This suggests a single large vent ( D vent = ∼74 m) or many small vents located very close together ( McDoniel et al, 2015 ) are reasonable configurations. In both cases the total mass flow would be on the order of 10 0 0 kg/s.…”

Section: Discussionmentioning

confidence: 88%

“…Due to the wedge-shaped domain, cells nearest the symmetry axis have very small volumes and therefore contain relatively few computational particles, leading to poor statistics for cell-averaged quantities. Boosting the number of simulated particles or employing weighting schemes mitigates this effect ( McDoniel et al, 2015 ).…”

Section: Stagingmentioning

confidence: 99%

“…Provided that the channels have a variable cross sectional area, this could result in exit velocities of ∼10 0 0 m/s ( Yeoh et al, 2015 ). On other low gravity bodies like the Galilean moon Io, volcanic plumes have vent exit velocities of 500-10 0 0 m/s ( McDoniel et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

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DSMC simulation of Europa water vapor plumes

Berg

Goldstein

Varghese

et al. 2016

Icarus

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Section: Discussionmentioning

confidence: 88%

Section: Stagingmentioning

confidence: 99%

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DSMC simulation of Europa water vapor plumes

Berg

Goldstein

Varghese

et al. 2016

Icarus

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“…4. Particle Balancing (perhaps first applied to DSMC in [9] and used in codes like UT's PLANET [12] or Sandia's SPARTA [http://sparta.sandia.gov]): Another popular balancing method uses particle count as a proxy for load. Processor boundaries are drawn such that each processor owns space containing roughly equal numbers of particles.…”

Section: State Of the Artmentioning

confidence: 99%

A Timer-Augmented Cost Function for Load Balanced DSMC

McDoniel

Bientinesi

2019

Lecture Notes in Computer Science

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Due to a hard dependency between time steps, large-scale simulations of gas using the Direct Simulation Monte Carlo (DSMC) method proceed at the pace of the slowest processor. Scalability is therefore achievable only by ensuring that the work done each time step is as evenly apportioned among the processors as possible. Furthermore, as the simulated system evolves, the load shifts, and thus this load-balancing typically needs to be performed multiple times over the course of a simulation. Common methods generally use either crude performance models or processor-level timers. We combine both to create a timer-augmented cost function which both converges quickly and yields well-balanced processor decompositions. When compared to a particle-based performance model alone, our method achieves 2x speedup at steady-state on up to 1024 processors for a test case consisting of a Mach 9 argon jet impacting a solid wall.

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“…Using this qualitative analogy, I proposed that umbrella-shaped plumes, such as those from Pele or Prometheus, were pressure balanced and that the irregularly shaped plumes, such as the one that erupted from Loki, were overpressured (Kieffer 1982a). Continued observations over the decades have produced higher-resolution data about the structure and temporal behavior of the Ionian plumes, and models using ever more sophisticated supercomputer simulations have been able to incorporate rarefied gas dynamics, phase changes, particle loading, and three-dimensional vent geometries to explain plume structure (e.g., McDoniel et al 2015).…”

Section: Laval Nozzlesmentioning

confidence: 99%