Morris, A., et al., “Far Field Deposition of Scoured Regolith Resulting From Lunar Landings*”, *in *Proceedings of* 27*th Intl. Symposium on Rarefied Gas Dynamics.* Zaragoza, ES, (2012)

Morris, A., et al., “Modeling the Interaction Between a Rocket Plume, Scoured Regolith, and a Plume Deflection Fence”, in Proc. of 13th Earth and Space ASCE Conf. Pasadena, CA, (2012).

In this work, statistical techniques were employed to study the modeling of a hypersonic shock with the Direct Simulation Monte Carlo (DSMC) method, and to gain insight into how the model interacts with a set of physical parameters. Direct Simulation Monte Carlo (DSMC) is a particle based method which is useful for simulating gas dynamics in rarefied and/or highly non-equilibrium flowfields. A DSMC code was written and optimized for use in this research. The code was developed with shock tube simulations in mind, and it includes a number of improvements which allow for the efficient simulation of 1D, hypersonic shocks. Most importantly, a moving sampling region is used to obtain an accurate steady shock profile from an unsteady, moving shock wave. The code is MPI parallel and an adaptive load balancing scheme ensures that the workload is distributed properly between processors over the course of a simulation. Global, Monte Carlo based sensitivity analyses were performed in order to determine which of the parameters examined in this work most strongly affect the simulation results for two scenarios: a 0D relaxation from an initial high temperature state and a hypersonic shock. The 0D relaxation scenario was included in order to examine whether, with appropriate initial conditions, it can be viewed in some regards as a substitute for the 1D shock in a statistica sensitivity analysis. In both analyses sensitivities were calculated based on both the square of the Pearson correlation coefficient and the mutual information. The quantity of interest (QoI) chosen for these analyses was the NO density profile. This vector QoI was broken into a set of scalar QoIs, each representing the density of NO at a specific point in time (for the relaxation) or a specific streamwise location (for the shock), and sensitivities were calculated for each scalar QoI based on both measures of sensitivity. The sensitivities were then integrated over the set of scalar QoIs to determine an overall sensitivity for each parameter. A weighting function was used in the integration in order to emphasize sensitivities in the region of greatest thermal and chemical non-equilibrium. The six parameters which most strongly affect the NO density profile were found to be the same for both scenarios, which provides justification for the claim that a 0D relaxation can in some situations be used as a substitute model for a hypersonic shock. These six parameters are the pre-exponential constants in the Arrhenius rate equations for the N₂ dissociation reaction N₂ + N [reaction in both directions] 3N, the O₂ dissociation reaction O₂ + O [reaction in both directions] 3O, the NO dissociation reactions NO + N [reaction in both directions] 2N + O and NO + O [reaction in both directions] N + 2O, and the exchange reactions N₂ + O [reaction in both directions] NO + N and NO + O [reaction in both directions] O₂ + N. After identification of the most sensitive parameters, a synthetic data calibration was performed to demonstrate that the statistical inverse problem could be solved for the 0D relaxation scenario. The calibration was performed using the QUESO code, developed at the PECOS center at UT Austin, which employs the Delayed Rejection Adaptive Metropolis (DRAM) algorithm. The six parameters identified by the sensitivity analysis were calibrated successfully with respect to a group of synthetic datasets.

- Hypersonic Flow on an Axisymmetric Capsule Using DPLR
- Chaleur – Modifications and Sample Results
- Sensitivity Analysis for DSMC Simulations of a Hypersonic Shock
- Application of Bayesian Statistical Methods for the Analysis of DSMC Simulations of Hypersonic Shocks
- Statistical Methods for the Analysis of DSMC Simulations of Hypersonic Shocks
- Bayesian Inference For The Calibration Of DSMC Parameters
- Application of the MCMC Method for the Calibration of DSMC Parameters
- Bayesian Inference for the Calibration of DSMC Parameters
- Bayesian Inference For The Calibration Of DSMC Parameters
- Bayesian Inference For The Calibration Of DSMC Parameters
- Application of the Metropolis-Hastings Algorithm for the Calibration of DSMC Parameters
- Bayesian Inference for the Calibration of DSMC Parameters
- Application of Bayesian Statistical Methods for the Analysis of DSMC Simulations of Hypersonic Shocks
- Statistical Methods for the Analysis of DSMC Simulations of

Hypersonic Shocks - Application of the MCMC Method for the Calibration of DSMC Parameters

Over the last four billion years, a large amount of cometary material is estimated to have impacted the Moon. Water ice is thought to be the major constituent of comet nuclei, and analysis of hydrogen isotopes present in lunar minerals suggests the possibility of a cometary source for lunar water. We simulate comet impacts on the Moon, with a view to studying the nature of deposition of cometary water in the Moon’s permanently shadowed craters (cold traps), where temperatures are low enough to trap water over geological time scales.

On impact, a comet vaporizes. The dense regions closest to the point of impact are simulated by our collaborators at the Planetary Science Institute in Arizona, using the SOVA hydrocode. We then use a Direct Simulation Monte Carlo (DSMC) code designed to handle rarefied planetary scale flows to track the evolution of the water vapor plume, and the eventual deposition of water molecules in cold traps. We are currently carrying out a parametric study of the influence of various parameters (comet density, impact angle, velocity, location etc.) on the final deposition pattern. Our aim is to investigate whether cometary delivery can account for current observations of hydrogen on the Moon, and the influence of parameters such as impact angle, velocity and location on the extent and nature of final retention of water.

Other publications and presentations

Turbulent spots are arrowhead shaped pockets of turbulent that form in the late stages of laminar to turbulent transition process (red circle in the schematic below). These spots increase in size as they travel downstream and form fully turbulent flow as they merge together. My research is looking at the formation and growth mechanisms of turbulent spot as well as interactions of millimeter scale surface textures with spots. If laminar to turbulent transition can be delayed using surface textures, then drag could be reduced.

The simulations are done using a channel flow spectral DNS code modified with immersed boundary to allow for boundary layer simulations. Re_{x} ranges from about 524,000 to 675,000.

- DNS of Surface Textures to Control the Growth of Turbulent Spots
- Sensitivity Analysis for DSMC Simulations of High-Temperature Air Chemistry
- DNS of Surface Textures to Control the Growth of Turbulent Spots
- DNS of Surface Textures to Control the Growth of Turbulent Spots
- Application of Passive Surface Textures to Control the Growth of Turbulent Spots at Moderately High Reynolds Numbers
- Direct numerical simulations of riblets to constrain the growth of turbulent spots
- DNS of Surface Textures to Control the Growth of Turbulent Spots
- DNS of Surface Textures to Control the Growth of Turbulent Spots

Io has one of the most dynamic atmospheres in the solar system due in part to an orbital resonance with Europa and Ganymede that causes intense tidal heating and volcanism. The volcanism serves to create a myriad of volcanic plumes across Io’s surface that sustain temporally varying local atmospheres. The plumes primarily eject sulfur dioxide (SO_{2}) that condenses on Io’s surface during the relatively cold night. During the day, insolation warms the surface to temperatures where a global partially collisional atmosphere can be sustained by sublimation from SO_{2} surface frosts. Both the volcanic and sublimation atmospheres serve as the source for the Jovian plasma torus which flows past Io at ~57 km/s. The high energy ions and electrons in the Jovian plasma torus interact with Io’s atmosphere causing atmospheric heating, chemical reactions, as well as altering the circumplanetary winds. Energetic ions which impact the surface can sputter material and create a partially collisional atmosphere. Simulations suggest that energetic ions from the Jovian plasma cannot penetrate to the surface when the atmospheric column density is greater than 10^{15} cm^{−2}. These three mechanisms for atmospheric support (volcanic, sublimation, and sputtering) all play a role in supporting Io’s atmosphere but their relative contributions remain unclear.

In the present work, the Direct Simulation Monte Carlo (DSMC) method is used to simulate the interaction of Io’s atmosphere with the Jovian plasma torus and the results are compared to observations. These comparisons help constrain the relative contributions of atmospheric support as well as highlight the most important physics in Io’s atmosphere. These rarefied gas dynamics simulations improve upon earlier models by using a three-dimensional domain encompassing the entire planet computed in parallel. The effects of plasma heating, planetary rotation, inhomogeneous surface frost, molecular residence time of SO_{2} on the exposed non-frost surface, and surface temperature distribution are investigated.

- 2012 Graduate Student Poster Session
- 3D DSMC Simulations of Io’s Unsteady Sublimation-Driven Atmosphere and Its Sensitivity to the Lower Surface Boundary Conditions
- Background Information on Io
- Controlling Parameters
- DSMC Simulation of the Plasma Bombardment on Io’s Sublimated and Sputtered Atmosphere
- Loki – A Lava Lake in Rarefied Circumplanetary Cross Flow
- Modeling the Sublimation-driven Atmosphere of Io with DSMC
- Modeling of SO2 IR Radiation in 19.3um from the Sublimation Atmosphere
- Modeling the Sublimation Atmosphere of Io

Io is the most volcanically active body in the solar system, and its volcanic plumes rise hundreds of kilometers above the surface. They rise far above the atmosphere, and I model this plume expansion into a near-vacuum with Direct Simulation Monte Carlo. I simulate Pele, one of the largest plumes, in 3D using observations of the caldera to guide my choice of source geometry. My goal is to explain the physics behind the deposition pattern and plume structure seen in observations. I also simulate plumes alongside other features of Io’s environment, like its sublimation atmosphere and Jupiter’s plasma torus, to understand how plumes fit into the big picture.

- DSMC Modeling of an Irregular Vent Geometry for Ionian Plumes
- DSMC Modeling of the Pele Plume on Io
- Modeling Gas and Dust Flow in Io’s Pele Plume
- Simulating Irregular Source Geometries for Ionian Plumes
- Three-dimensional Simulation of Gas and Dust in Io’s Pele Plume
- Realistic Simulation of Io’s Pele Plume and its Effects on Io’s Atmosphere

The Cassini spacecraft first detected a plume near the warm south pole of the Saturnian moon Enceladus in 2005. The discovery of the plume not only helped to explain some phenomena that have been puzzling scientists for a long time but also brought about the exciting possibility of finding liquid water on Enceladus, making it a possibly favorable environment for life. Therefore, more flybys have been made over the moon and have yielded spectacular images, details of the plume structure and composition, as well as the possible locations of the plume sources. Observations found that the plume is composed of gas (mostly water vapor) with tiny entrained ice particles. Based on the images and data from Cassini, we construct a hybrid model of the plume. Our model divides the plume into two regimes: the collisional flow in the near-source region and the collisionless flow in the far-field region. The direct simulation Monte Carlo (DSMC) method is used to simulate the collisional gas flow in the near-source region as the gas has only begun to expand and is therefore, still relatively dense and warm. Once the flow becomes collisionless further out, the DSMC output is fed into a computationally less expensive free-molecular model to propagate the flow further into the far field. The simulation results are directly compared to the *in-situ* measurements made by Cassini. Our objective is to attempt to deduce the nature of the plume sources and hopefully, answer the question of whether there is liquid water on Enceladus.