Thesis (M.S.)--University of Michigan, 1979.

High energy density experiments rely heavily on predictive physics simulations in the design process. Specifically in inertial confinement fusion (ICF), predictive physics simulations, such as in the radiation-hydrodynamics code xRAGE, are computationally expensive, limiting the design process and ability to find an optimal design. Machine learning provides a mechanism to leverage expensive simulation data and alleviate limitations on computational time and resources in the search for an optimal design. Machine learning efficiently identifies regions of design space with high predicted performance as well as regions with high uncertainty to focus simulations, which may lead to unexpected designs with great potential. This dissertation focuses on the application of Bayesian optimization to design optimization for ICF experiments conducted by the double shell campaign at Los Alamos National Lab (LANL). The double shell campaign is interested in implementing graded inner shell layers to their capsule geometry. Graded inner shell layers are expected to improve stability in the implosions with fewer sharp density jumps, but at the cost of lower yields, in comparison to the nominal bilayer inner shell targets. This work explores minimizing hydrodynamic instability and maximizing yield for the graded inner shell targets by building and coupling a multi-fidelity Bayesian optimization framework with multi-dimensional xRAGE simulations for an improved design process. / Doctor of Philosophy / Inertial confinement fusion (ICF) is an active field of research in which a fuel is compressed to extreme temperatures and densities to achieve thermonuclear ignition. Ignition is achieved when the fuel can continuously heat itself and sustain its reactions. These fusion reactions would produce large amounts of energy. Power plants using fusion could solve many of the world's energy concerns with far less pollution than current energy sources. Although ignition has not been achieved in the lab, ICF researchers are actively working towards this goal. At Los Alamos National Lab (LANL), ICF researchers are focused on studying ignition-relevant conditions for "double shell" targets through experiments at laser facilities, such at the National Ignition Facility (NIF). These experiments are extremely expensive to field, design, and analyze. To obtain the maximum information from each experiment, researchers rely on predictive physics simulations, which are computationally intensive, making it difficult to find optimal target designs. In this dissertation, better use of simulations is made by focusing on using machine learning along with simulation data to find optimal target designs. Machine learning allows for efficient use of limited computational time and resources on simulations, such that an optimal target design can be found in a reasonable amount of time before an ICF experiment. This dissertation specifically looks at using Bayesian optimization for design optimization of LANL's double shell capsules with graded material inner shells. Several Bayesian optimization frameworks are presented, along with a discussion of optimal designs and physics mechanisms that lead to high performing capsule designs. The work from this dissertation will create an improved design process for the LANL double shell (and other) campaigns, providing high fidelity optimization of ICF targets.

No description available.

Thesis (Ph. D.)--University of Missouri-Columbia, 2007. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on February 25, 2008) Vita. Includes bibliographical references.

While the search for a practical fusion energy source has been pursued for decades, ultimate success remains elusive, and the need is apparent for continued research into alternative experimental fusion techniques. A method that has received fair attention over the past few years is Inertial Electrostatic Confinement (IEC) fusion, a system in which a convergent ion focus is obtained solely through electrostatic fields. During device operation where the electrostatic field is supported by very high voltages (over 20,000V), the resulting ion focus sustains a dense plasma capable of generating a high rate of fusion reactions and neutron production. However, present limited theoretical knowledge and engineering issues prevent the capacity ofIEC systems to produce net power. Rather, intermediate applications center on using the device as a portable neutron source. The work performed here involves an IEC device using spherical geometry, and includes the introduction of a new variable, the addition of high frequency electromagnetic (EM) fields into its operation. The goal is to predict theoretically, observe and explain any beneficial compressive effects of added microwave EM fields on the potential fusion reaction rate in an experimental reactor. An optical determination of the enhancement is performed while using lower voltages under 1 000V, and is based on the relative intensity of the confined plasma during glow discharge operation. It is hypothesized that imposing EM fields will enhance the potential fusion reaction rate conservatively by a factor of two. Presently, IEC systems operate just under neutron production levels needed for practical applications such as landmine detection and medical isotope production, and any enhancement from EM fields should prove highly beneficial.

Thesis (M.Sc. (Hons.)) -- University of Western Sydney, 2002. / "A thesis submitted as part of the requirements for the degree of Master of Science (Honours)" Bibliography : leaves 175-181.

The effect of single mode initial conditions at the interface of Rayleigh-Taylor(RT) mixing are experimentally examined utilizing the low Atwood number water channel facility at Texas A&M. The water channel convects two separated stratified flows and unifies them at the end of a splitter plate. The RT instability is attained by convecting a cold stream above a warmer stream. Average density calculations are based on long time average optical measurements. The water channel was modifified with a flapper fin like device at the end of the splitter plate which was actuated by a computer controlled servo motor. Other modifications to the experiment were implemented resulting in reduced uncertainty. The experiment examined five different modes in addition to the baseline: 2 cm, 3 cm, 4 cm, 6 cm, and 8 cm wavelengths. The mixing width growth rates were shown to be dependent on initial conditions. Additionally, it appears that the growth rates commence with terminal velocity and are observed to line up with the baseline case.

Thesis (M.S.)--University of Nevada, Reno, 2008. / "August, 2008." Includes bibliographical references (leaves 96-98). Online version available on the World Wide Web.

Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2007. / Abdel-Khalik, Said, Committee Co-Chair ; Ghiaasiaan, Mostafa, Committee Co-Chair ; Jeter, Sheldon, Committee Member.

The steady flow model is applied to ablatively accelerated spherical targets for inertial confinement fusion. A parameter study is conducted which identifies regions of good hydrodynamic efficiency. In the limit of very large acceleration the model is seen to become planar and can be used to treat some large aspect ratio shells. A model of charged particle beam driven ablation is presented. The ablation resulting from this form of energy deposition can resemble laser driven albation in some cases, but qualitatively different behavior occurs in certain regimes of the beam power and range. Laser energy deposition by inverse bremsstrahlung is also included. A procedure for descaling the dimensionless results of the steady flow model is presented. This allows for comparison of the model with experiments and numerical simulations.