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Full-Text Articles in Physical Sciences and Mathematics
Computer Simulations Of Diffusional Isotope Effects And Dynamical Properties Of Silicate Melts, Haiyang Luo
Computer Simulations Of Diffusional Isotope Effects And Dynamical Properties Of Silicate Melts, Haiyang Luo
LSU Doctoral Dissertations
Silicate melts have served as transport agents in the chemical and thermal evolution of Earth. Diffusional isotope effect in silicate melts is the key to interpret isotope variations in lots of geological samples. Isotopic mass dependence of diffusion is commonly expressed as (Di/Dj)=(mj/mi)^β, where Di and Dj are diffusion coefficients of two isotopes whose masses are mi and mj. However, how the dimensionless empirical parameter β depends on temperature, pressure, and composition remains poorly constrained. Viscosity and electrical conductivity are two fundamental dynamical properties of silicate melts needed to constrain melt distribution in Earth's interior but remain unclear for most …
Inference Of Surface Velocities From Oblique Time Lapse Photos And Terrestrial Based Lidar At The Helheim Glacier, Franklyn T. Dunbar Ii
Inference Of Surface Velocities From Oblique Time Lapse Photos And Terrestrial Based Lidar At The Helheim Glacier, Franklyn T. Dunbar Ii
Graduate Student Theses, Dissertations, & Professional Papers
Using time dependent observations derived from terrestrial LiDAR and oblique
time-lapse imagery, we demonstrate that a Bayesian approach to glacial motion es-
timation provides a concise way to incorporate multiple data products into a single
motion estimation procedure effectively producing surface velocity estimates with
an associated uncertainty. This approach brings both improved computational effi-
ciency, and greater scalability across observational time-frames when compared to
existing methods. To gauge efficacy, we apply these methods to a set of observa-
tions from the Helheim Glacier, a critical actor in contemporary mass loss trends
observed in the Greenland Ice Sheet. We find that …
Volcan De Fuego: A Machine Learning Approach In Understanding The Eruptive Cycles Using Precursory Tilt Signals, Kay Sivaraj
Volcan De Fuego: A Machine Learning Approach In Understanding The Eruptive Cycles Using Precursory Tilt Signals, Kay Sivaraj
Dissertations, Master's Theses and Master's Reports
Volcan de Fuego is an active stratovolcano located in the Central Guatemalan segment of the 1100 m long Central America Volcanic Arc System (CAVAS). Fuego-Acatenango massif consists of at least four major vents of which the Fuego summit vent is the most active and the youngest member. The volcano exhibits primarily Strombolian and Vulcanian behavior along with occasional paroxysms and pyroclastic flows. Historically, Fuego has produced basaltic-andesitic rocks with more recent eruptions progressively trending towards maficity. Several studies have used short-term deployments of broadband seismometers, infrasound, and long-term remote sensing techniques to characterize the mechanism of Fuego. In our study, …