This thesis deals with the direct simulation Monte Carlo (DSMC) method of analysing gas flows. The DSMC method was initially proposed as a method for predicting rarefied flows where the Navier-Stokes equations are inaccurate. It has now been extended to near continuum flows. The method models gas flows using simulation molecules which represent a large number of real molecules in a probabilistic simulation to solve the Boltzmann equation. Molecules are moved through a simulation of physical space in a realistic manner that is directly coupled to physical time such that unsteady flow characteristics are modelled. Intermolecular collisions and moleculesurface collisions are calculated using probabilistic, phenomenological models. The fundamental assumption of the DSMC method is that the molecular movement and collision phases can be decoupled over time periods that are smaller than the mean collision time. Two obstacles to the wide spread use of the DSMC method as an engineering tool are in the areas of simulation configuration, which is the configuration of the simulation parameters to provide a valid solution, and the time required to obtain a solution. For complex problems, the simulation will need to be run multiple times, with the simulation configuration being modified between runs to provide an accurate solution for the previous run�s results, until the solution converges. This task is time consuming and requires the user to have a good understanding of the DSMC method. Furthermore, the computational resources required by a DSMC simulation increase rapidly as the simulation approaches the continuum regime. Similarly, the computational requirements of three-dimensional problems are generally two orders of magnitude more than two-dimensional problems. These large computational requirements significantly limit the range of problems that can be practically solved on an engineering workstation or desktop computer. The first major contribution of this thesis is in the development of a DSMC implementation that automatically adapts the simulation. Rather than modifying the simulation configuration between solution runs, this thesis presents the formulation of algorithms that allow the simulation configuration to be automatically adapted during a single run. These adaption algorithms adjust the three main parameters that effect the accuracy of a DSMC simulation, namely the solution grid, the time step and the simulation molecule number density. The second major contribution extends the parallelisation of the DSMC method. The implementation developed in this thesis combines the capability to use a cluster of computers to increase the maximum size of problem that can be solved while simultaneously allowing excess computational resources to decrease the total solution time. Results are presented to verify the accuracy of the underlying DSMC implementation, the utility of the solution adaption algorithms and the efficiency of the parallelisation implementation.

This thesis deals with the direct simulation Monte Carlo (DSMC) method of analysing gas flows. The DSMC method was initially proposed as a method for predicting rarefied flows where the Navier-Stokes equations are inaccurate. It has now been extended to near continuum flows. The method models gas flows using simulation molecules which represent a large number of real molecules in a probabilistic simulation to solve the Boltzmann equation. Molecules are moved through a simulation of physical space in a realistic manner that is directly coupled to physical time such that unsteady flow characteristics are modelled. Intermolecular collisions and moleculesurface collisions are calculated using probabilistic, phenomenological models. The fundamental assumption of the DSMC method is that the molecular movement and collision phases can be decoupled over time periods that are smaller than the mean collision time. Two obstacles to the wide spread use of the DSMC method as an engineering tool are in the areas of simulation configuration, which is the configuration of the simulation parameters to provide a valid solution, and the time required to obtain a solution. For complex problems, the simulation will need to be run multiple times, with the simulation configuration being modified between runs to provide an accurate solution for the previous run�s results, until the solution converges. This task is time consuming and requires the user to have a good understanding of the DSMC method. Furthermore, the computational resources required by a DSMC simulation increase rapidly as the simulation approaches the continuum regime. Similarly, the computational requirements of three-dimensional problems are generally two orders of magnitude more than two-dimensional problems. These large computational requirements significantly limit the range of problems that can be practically solved on an engineering workstation or desktop computer. The first major contribution of this thesis is in the development of a DSMC implementation that automatically adapts the simulation. Rather than modifying the simulation configuration between solution runs, this thesis presents the formulation of algorithms that allow the simulation configuration to be automatically adapted during a single run. These adaption algorithms adjust the three main parameters that effect the accuracy of a DSMC simulation, namely the solution grid, the time step and the simulation molecule number density. The second major contribution extends the parallelisation of the DSMC method. The implementation developed in this thesis combines the capability to use a cluster of computers to increase the maximum size of problem that can be solved while simultaneously allowing excess computational resources to decrease the total solution time. Results are presented to verify the accuracy of the underlying DSMC implementation, the utility of the solution adaption algorithms and the efficiency of the parallelisation implementation.

<p>Granular systems are ensembles of inelastic particles which dissipate energy during collisions. Granular systems serve as excellent models for a wide variety of materials such as sand, soils, corn, and powder. A rather remarkable property of granular systems is when excited, whether due to an interstitial fluid or via the boundaries, the granular particlesdisplay fluid-like behavior. As a result, there has been decades of granular research with the overarching goal of formulating a general granular hydrodynamic theory.</p> <p>However, the granular hydrodynamic theory is limited, and the underlying transport coefficients often require modifications which are based on empirical observations, and assuch, are system-specific. It is ideally better to devise a general theory which minimizes the information needed about the systema priori. The main thrust of the work undertaken shown here strives to develop such a model by using kinetic theory as the basis. More specifically, I investigate granular gases via the direct simulation Monte Carlo (DSMC) methodand modify the governing equations. In this thesis, two idealized cases of granular gases areconsidered: the homogeneous cooling state and a boundary-heated gas (or the pure conduc-tion case). In the former, the effects of polydispersity are probed. In the latter, the evolutionof the local hydrodynamics due to strong rarefaction effects are divulged. Additionally, amodified, more generalized constitutive relation for the heat flux is proposed and comparedwith DSMC results. Extensions of the DSMC method for dense granular gases and granulargases composed of non-spherical particles are also discussed.</p>

Thermochemical nonequilibrium widely exists in supersonic combustion, cold plasma and hypersonic flight. The effect can influence heat transfer, surface ablation and aerodynamic loads. One distinct feature of it is the coupling between internal energy excitation and chemical reactions, particularly the vibration-dissociation coupling. The widely used models are empirical and calibrated based on limited experimental data. Advances in theories and computational power have made the first-principle calculation of thermal nonequilibrium reaction rates by methods like quasi-classical trajectory (QCT) almost a routine today. However, the approach is limited by the uncertainties and availability of potential energy surfaces. To the best of our knowledge, there is no study of thermal nonequilibrium transport properties with this approach. Most importantly, non-trivial effort is required to process the QCT data and implement it in flow simulation methods. In this context, the first part of this work establishes the approach to compute transport properties by the QCT method and studies the influence of thermal nonequilibrium on transport properties for N₂-O molecules. The preponderance of the work is the second part, a comprehensive study of the development of a new thermal nonequilibrium reaction model based on reasonable assumptions and approximations. The new model is as convenient as empirical models. By validating against recent QCT data and experimental results, we found the new model can predict nonequilibrium characteristics of dissociation reactions with nearly the same accuracy as QCT calculations do. In general, the results show the potential of the new model to be used as the standard dissociation model for the simulation of thermochemical nonequilibrium flows.

<p> The Virtual Super-resolution Optics with Reconfigurable Swarms (VISORS) mission  aims to produce high-resolution images of solar release sites in the solar corona using a  distributed telescope. The collected data will be used to investigate the existence of underlying  energy release mechanisms. The VISORS telescope is composed of two spacecraft flying in a  formation configuration. The optics spacecraft (OSC) hosts the optic system, while the detector  spacecraft (DSC) is located behind the OSC in alignment with the Sun and houses a detector.  The two modes of operation for the CubeSats are Science Operations Mode and Standby Mode.  In Science Operations Mode, the two spacecraft are at a close distance which may make the plume impingement an issue. The cold gas thruster propulsion systems in both the OSC and  DSC use R-236fa (HFC) refrigerant. The plume from the system is modeled using SPARTA  Direct Simulation Monte Carlo (DSMC) Simulator while the refrigerant itself is modeled using  an equivalent particle that closely matches viscosity and specific heat. This work aims to  investigate plume propagation for two different flow inputs. The DSMC simulations are  performed with the input parameters acquired using the isentropic relations and CFD simulations  of the 2D axisymmetric nozzle flow. Additionally, the DSMC results are compared to the  Boynton-Simons, Roberts-South, and Gerasimov analytical plume models. </p>

Cette thèse traite, dans une première partie, de la propagation unidimensionnelle de fronts de réactions exothermiques, à différentes échelles de description. Dans une approche macroscopique, la quantité de chaleur dégagée par la réaction vient coupler l'équation de convection-réaction-diffusion et les équations de l'hydrodynamique. Ce travail montre l'existence d'un domaine interdit de vitesses de propagation pour un front d'onde chimique stationnaire. Il met en évidence une transition entre une propagation principalement déterminée par les processus de réaction-diffusion, pour de faibles chaleurs de réaction, et une propagation principalement déterminée par les équations de l'hydrodynamique et l'équation d'état du fluide, pour une quantité de chaleur plus importante. Cette bifurcation est illustrée dans les cas d'un gaz parfait et d'un fl uide de van der Waals. La simulation microscopique de la dynamique des particules par la méthode 'Direct Simulation Monte Carlo' (DSMC) permet de retrouver ces résultats pour un gaz dilué. Dans une seconde partie, cette thèse développe un modèle de précipitation d'aiguilles de gypse à partir de grains d'hémihydrate de sulfate de calcium ainsi qu'un algorithme de simulation de la prise du plâtre à une échelle submicrométrique. Les résultats de simulation sont comparés à ceux issus d'une approche déterministe et d'une approche stochastique par une équation maîtresse. En dégageant un ensemble de paramètres ajustables et interprétables physiquement, le modèle permet de proposer une explication de l'effet d'un traitement industriel con dentiel améliorant la cinétique de formation et la morphologie du matériau final.