Doctor of Philosophy (PhD), Wright State University, 2007, Engineering PhD

Design of the next generation of ion engines can benefit from detailed computer simulations of the plasma in the discharge chamber. In this work a complete particle based approach has been taken to model the discharge chamber plasma.This is the first time that simplifying continuum assumptions on the particle motion have not been made in a discharge chamber model. Because of the long mean free paths of the particles in the discharge chamber continuum models are questionable. The PIC-MCC model developed in this work tracks following particles: neutrals, singly charged ions, doubly charged ions, secondary electrons, and primary electrons. The trajectories of these particles are determined using the Newton-Lorentz's equation of motion including the effects of magnetic and electric fields. Particle collisions are determined using an MCC statistical technique. A large number of collision processes and particle wall interactions are included in the model. The magnetic fields produced by the permanent magnets are determined using Maxwell's equations. The electric fields are determined using an approximate input electric field coupled with a dynamic determination of the electric fields caused by the charged particles. In this work inclusion of the dynamic electric field calculation is made possible by using an inflated plasma permittivity value in the Poisson solver. This allows dynamic electric field calculation with minimal computational requirements in terms of both computer memory and run time. In addition, a number of other numerical procedures such as parallel processing have been implemented to shorten the computational time. The primary results are those modeling the discharge chamber of NASA's NSTAR ion engine at its full operating power. Convergence of numerical results such as total number of particles inside the discharge chamber, average energy of the plasma particles, discharge current, beam current and beam efficiency are obtained. Steady state results for th (open full item for complete abstract)

Committee: James Menart (Advisor) Subjects:

Master of Science, Miami University, 2009, Computer Science and Systems Analysis

Realizing the advantages of simulation-based methodologies requires the use of a software environment that is conducive for modeling, simulation, and analysis. Furthermore, parallel simulation methods must be employed to reduce the time for simulation, particularly for large problems, to enable analysis in reasonable timeframes. Accordingly, this thesis covers the development of a general purpose agent-based, parallel simulation environment called MUSE (Miami University Simulation Environment). MUSE, provides an Application Program Interface (API) for agent-based modeling and a framework for parallel simulation. The API was developed in C++ using its object oriented features. The core parallel simulation capabilities of MUSE were realized using the Time Warp synchronization methodology and the Message Passing Interface (MPI). Experiments show MUSE to be a scalable and efficient simulation environment.

Committee: Dhanajai Rao PhD (Advisor); Mufit Ozden PhD (Committee Member); Lukasz Opyrchal PhD (Committee Member) Subjects: Computer Science

MS, University of Cincinnati, 2003, Engineering : Computer Engineering

Coupled simulations form an important class of simulations that involve the concurrent execution of two (or more) different simulations. A bottleneck is created at synchronization points when one simulation has to wait idle for the other simulation. This scenario appears when the processors are statically distributed between the coupled simulations, not taking into consideration the dynamic change of the workload of each coupled simulations. As the difference between the workloads of the coupled simulation increases, the idle time also increases because the simulation with the larger workload spends more time in computation while the other simulation is waiting for synchronization. Dynamic resource balancing is the solution that we developed to overcome the problem of wasted idle time. We use the dynamic creation and deletion of processes provided by MPI-2 to rebalance the coupled simulation. Our results showed a reduction in waiting time and an improvement in the overall system performance.

Committee: Dr. Karen Tomko (Advisor) Subjects: Computer Science

Doctor of Philosophy, University of Toledo, 2009, Physics

The main objective of the work presented in this thesis is to develop new methods to extend the time and length scales of atomistic kinetic Monte Carlo (KMC) simulations. When all the relevant processes and their activation barriers are known, KMC is an extremely efficient method to carry out atomistic simulations for longer time scales. However, in some cases (ex. low barrier repetitive events) direct KMC simulations may not be sufficient to reach the experimentally relevant length and time scales. Accordingly, we have tested and developed several different parallel KMC algorithms and also developed a dynamic boundary allocation (DBA) method to improve parallel efficiency by reducing number of boundary events. Results for parallel KMC simulations of Ag(111) island coarsening at room temperature carried out using a large database of processes obtained from previous self-learning KMC simulations are also presented. We find that at long times the coarsening behavior corresponds to Ostwald ripening. We also find that the inclusion of concerted small-cluster events has a significant impact on the average island size. In addition, we have also developed a first passage time (FPT) approach to KMC simulations to accelerate KMC simulation of (100) multilayer epitaxial growth with rapid edge diffusion. In our FPT approach, by mapping edge-diffusion to a 1D random walk, numerous diffusive hops are replaced with first-passage time to make one large jump to a new location. As a test, we have applied our method to carry out multilayer growth simulations of three different models. We note that despite the additional overhead, the FPT approach leads to a significant speed-up compared to regular KMC simulations Finally, we present results obtained from KMC simulations of irreversible submonolayer island growth with strain and rapid island relaxation. Our results indicate that in the presence of large strain there is significant anisotropy in qualitative agreement with experiments o (open full item for complete abstract)

Committee: Amar Jacques (Advisor); Amar Jacques (Advisor); Collins Robert (Committee Member); Bigioni Terry (Committee Member); Anderson-huang Lawrence (Committee Member); Kvale Thomas (Committee Member) Subjects: Physics