Thesis (M.S.)--University of Wisconsin--Madison. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 83-85).

Thesis (M. Sc.)--University of Canterbury, 2009. / Typescript (photocopy). Includes bibliographical references (leaves 145-161). Also available via the World Wide Web.

Ground deformation due to volcanic magma intrusion is recognised as an important precursor of eruptive activity at a volcano. The Global Positioning System (GPS) is ideally suited for this application by being able to measure three-dimensional coordinate changes of the monitoring points over time. Due to the highly disturbed ionosphere in equatorial regions, particularly during times of maximum solar activity, a deformation monitoring network consisting entirely of single-frequency GPS receivers cannot deliver baseline solutions at the desired accuracy level. In this thesis, a mixed-mode GPS network approach is proposed in order to optimise the existing continuous single-frequency deformation monitoring system on the Papandayan volcano in West Java, Indonesia. A sparse network of dual-frequency GPS receivers surrounding the deformation zone is used to generate empirical 'correction terms' in order to model the regional ionosphere. These corrections are then applied to the single-frequency data of the inner network to improve the accuracy of the results by modelling the residual atmospheric biases that would otherwise be neglected. This thesis reviews the characteristics of existing continuously operating GPS deformation monitoring networks. The UNSW-designed mixed-mode GPS-based volcano deformation monitoring system and the adopted data processing strategy are described, and details of the system's deployment in an inhospitable volcanic environment are given. A method to optimise the number of observations for deformation monitoring networks where the deforming body itself blocks out part of the sky, and thereby significantly reduces the number of GPS satellites being tracked, is presented. The ionosphere and its effects on GPS signals, with special consideration for the situation in equatorial regions, are characterised. The nature of the empirically-derived 'correction terms' is investigated by using several data sets collected over different baseline lengths, at various geographical locations, and under different ionospheric conditions. Data from a range of GPS networks of various sizes, located at different geomagnetic latitudes, including data collected on Gunung Papandayan, were processed to test the feasibility of the proposed mixed-mode deformation monitoring network approach. It was found that GPS baseline results can be improved by up to 50% in the midlatitude region when the 'correction terms' are applied, although the performance of the system degrades in close proximity to the geomagnetic equator during a solar maximum.

Thesis (Ph. D.)--University of New South Wales, 2003. / Also available online.

Thesis (Ph. D.)--University of Texas at El Paso, 2009. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

Thesis (Ph. D.)--University of Oregon, 2004. / Vita. Includes bibliographical references (leaves 178-188). Also available for download via the World Wide Web; free to University of Oregon users.

Thesis (Ph. D.)--University of Oregon, 2004. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 178-188). Also available for download via the World Wide Web; free to University of Oregon users.

No / Quite recently, considerable attention has been paid to solar flare prediction because extreme solar eruptions could affect our daily life activities and on different technologies. Therefore, this paper presents a novel method of the development of improved second-generation of the Automated Solar Activity Prediction system (ASAP). The suggested algorithm improves the ASAP system by expanding a period of training vector and generating new machine learning rules to be more successful. Two neural networks are responsible for determining whether the sunspots group will release flare as well as determining if the flare is an M-class or X-class. Several measurement criteria are applied to determine the extent of system performance also all results are provided in this paper. Furthermore, the quadratic score (QR) is used as a metric criterion to compare between the prediction of the proposed algorithm with the Space Weather Prediction Center (SWPC) between 2012 and 2013. The results exhibit that the proposed algorithm outperforms the old ASAP system. Keywords: Solar flares, Machine Learning, Neural network, Space, Prediction, weather.

Mount St. Helens returned to an active eruptive state March 20, 1980. Since then explosive and dome building eruptions have caused major topographic changes to the mountain and surrounding drainages. Monitoring of the southern side of the mountain by six tiltmeters at distances between 6 km and 12 km was conducted during the period of July 1, 1980 to December 31, 1980. Records obtained from the tiltmeters were analyzed and compared to data from precision geodetic surveys.

Volcanic eruptions pose hazards to life and insfrastructure, and contribute to the resurfacing of earth and other planetary bodies. Lavas and magmas are multi-phase suspensions of silicate melts (liquids), solid crystals, and vapor bubbles, and solidify into glass and rock upon cooling. The interactions between phases place important controls on the dynamics and timescales of magma and lava transport and emplacement. The purpose of this thesis is to explore the role of multiphase interactions in controlling eruption dynamics and inform conceptual and numerical models for hazard prediction. In Chapters 1 and 2, centimeter to meter scale analog experiments are used to explore the multi-phase rheological properties and flow behaviors of bubble- and particle-bearing suspensions. Optical imaging of dam-break experiments presented in Chapter 1 expand existing experimental parameter ranges for lava analogs to higher bubble concentrations than existing datasets (up to 82% by volume bubbles and 37% by volume particles). I develop a constitutive relationship for threephase relative viscosity, and demonstrate that at the low strain-rate conditions relevant to many natural lava flows, accounting for the rheological effect of bubbles can result in the prediction of slower runout speeds. Chapter 2 expands upon the work of Chapter 1 using different analog materials observed using nuclear magnetic resonance imaging (MRI) phase-contrast velocimetry (PCV) to measure velocity in the flow interior of three-phase dam-break experiments. I find that for high-aspect ratio particles (sesame seeds), phase segregation into shear bands readily occurs, even at low particle fraction (20%) and results in strain localization. I suggest that the presence of shear bands can lead to faster flow runout than predicted using assumptions of bulk rheology. Chapter 3 analyzes thermal infrared (IR) time-lapse photography and videography of Hawaiian to Strombolian explosive activity during the 2021 eruption of Cumbre Vieja volcano, La Palma, Canary Islands, Spain. Images are analyzed to find time series of apparent plume radius, velocity, and apparent volume flux of high-temperature gas and lava. I compare with other measures of eruptive activity, including remote observations of plume height, SO₂ flux, effusive flux, tremor, and events at the volcano edifice including edifice collapses and the opening of new vents. I find correlations between tremor and explosive flux, but no correlation with SO2 flux or effusive flux, which I interpret as evidence of bubble segregation, highlighting the role of phase segregation and temporal variability in material properties in natural systems. Finally, in Chapter 4, I develop a novel finite element model to explore the interaction between a viscous flow with a solidified crust, and the effect of these interactions on lava flow and lava dome emplacement. I develop a model that couples a temperature-dependent viscous interior with an elastic shell flowing into air, water, or dense atmospheres. The model expands upon existing numerical simulations used in volcanology to have direct applications to lava flows and domes on the sea floor, which accounts for a large portion of the volcanism on Earth, and volcanism on other planetary bodies. Additionally, the formation of levees or solidified flow fronts that fracture and lead to a restart of flow. These lava flow breakouts pose a significant hazard, but there are currently no volcanological community codes capable of using a physics-based approach to predict the timing or location of breakouts. The model in Chapter 4 is the first to allow for assessment of the likelihood of failure at the scale of a flow lobe. Chapter 4 describes the model formulation and verification, and validation against centimeter-scale molten basalt experiments. The dissertation as a whole integrates work using a variety of methods including analog experiments, observations of natural eruptions, and numerical simulations to contribute to our understanding of the effects of multi-phase interactions on volcanic eruptions.